challenges.tex 86 KB

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  1. \documentclass{llncs}
  2. % XXXX NM: Fold ``bandwidth and usability'' into ``Tor and filesharing'' --
  3. % ``bandwidth and file-sharing''.
  4. \usepackage{url}
  5. \usepackage{amsmath}
  6. \usepackage{epsfig}
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  14. \begin{document}
  15. \title{Challenges in deploying low-latency anonymity (DRAFT)}
  16. \author{Roger Dingledine\inst{1} \and Nick Mathewson\inst{1} \and Paul Syverson\inst{2}}
  17. \institute{The Free Haven Project \email{<\{arma,nickm\}@freehaven.net>} \and
  18. Naval Research Lab \email{<syverson@itd.nrl.navy.mil>}}
  19. \maketitle
  20. \pagestyle{empty}
  21. \begin{abstract}
  22. There are many unexpected or unexpectedly difficult obstacles to
  23. deploying anonymous communications. Drawing on our experiences deploying
  24. Tor (the next-generation onion routing network), we describe social
  25. challenges and technical issues that must be faced
  26. in building, deploying, and sustaining a scalable, distributed, low-latency
  27. anonymity network.
  28. \end{abstract}
  29. \section{Introduction}
  30. % Your network is not practical unless it is sustainable and distributed.
  31. Anonymous communication is full of surprises. This paper discusses some
  32. unexpected challenges arising from our experiences deploying Tor, a
  33. low-latency general-purpose anonymous communication system. We will discuss
  34. some of the difficulties we have experienced and how we have met them (or how
  35. we plan to meet them, if we know). We will also discuss some less
  36. troublesome open problems that we must nevertheless eventually address.
  37. %We will describe both those future challenges that we intend to explore and
  38. %those that we have decided not to explore and why.
  39. Tor is an overlay network for anonymizing TCP streams over the
  40. Internet~\cite{tor-design}. It addresses limitations in earlier Onion
  41. Routing designs~\cite{or-ih96,or-jsac98,or-discex00,or-pet00} by adding
  42. perfect forward secrecy, congestion control, directory servers, integrity
  43. checking, configurable exit policies, and location-hidden services using
  44. rendezvous points. Tor works on the real-world Internet, requires no special
  45. privileges or kernel modifications, requires little synchronization or
  46. coordination between nodes, and provides a reasonable tradeoff between
  47. anonymity, usability, and efficiency.
  48. We first publicly deployed a Tor network in October 2003; since then it has
  49. grown to over a hundred volunteer servers and as much as 80 megabits of
  50. average traffic per second. Tor's research strategy has focused on deploying
  51. a network to as many users as possible; thus, we have resisted designs that
  52. would compromise deployability by imposing high resource demands on server
  53. operators, and designs that would compromise usability by imposing
  54. unacceptable restrictions on which applications we support. Although this
  55. strategy has
  56. its drawbacks (including a weakened threat model, as discussed below), it has
  57. made it possible for Tor to serve many thousands of users, and attract
  58. research funding from organizations so diverse as ONR and DARPA
  59. (for use in securing sensitive communications), and the Electronic Frontier
  60. Foundation (for maintaining civil liberties of ordinary citizens online).
  61. While the Tor design paper~\cite{tor-design} gives an overall view of Tor's
  62. design and goals, this paper describes some policy, social, and technical
  63. issues that we face as we continue deployment.
  64. Rather than trying to provide complete solutions to every problem here, we
  65. lay out the assumptions and constraints that we have observed while
  66. deploying Tor in the wild. In doing so, we aim to create a research agenda
  67. for others to help in addressing these issues. We believe that the issues
  68. described here will be of general interest to projects attempting to build
  69. and deploy practical, useable anonymity networks in the wild.
  70. %While the Tor design paper~\cite{tor-design} gives an overall view its
  71. %design and goals,
  72. %this paper describes the policy and technical issues that Tor faces as
  73. %we continue deployment. Rather than trying to provide complete solutions
  74. %to every problem here, we lay out the assumptions and constraints
  75. %that we have observed through deploying Tor in the wild. In doing so, we
  76. %aim to create a research agenda for others to
  77. %help in addressing these issues.
  78. % Section~\ref{sec:what-is-tor} gives an
  79. %overview of the Tor
  80. %design and ours goals. Sections~\ref{sec:crossroads-policy}
  81. %and~\ref{sec:crossroads-design} go on to describe the practical challenges,
  82. %both policy and technical respectively,
  83. %that stand in the way of moving
  84. %from a practical useful network to a practical useful anonymous network.
  85. %\section{What Is Tor}
  86. \section{Background}
  87. Here we give a basic overview of the Tor design and its properties, and
  88. compare Tor to other low-latency anonymity designs.
  89. \subsection{Tor, threat models, and distributed trust}
  90. \label{sec:what-is-tor}
  91. %Here we give a basic overview of the Tor design and its properties. For
  92. %details on the design, assumptions, and security arguments, we refer
  93. %the reader to the Tor design paper~\cite{tor-design}.
  94. \subsubsection{How Tor works}
  95. Tor provides \emph{forward privacy}, so that users can connect to
  96. Internet sites without revealing their logical or physical locations
  97. to those sites or to observers. It also provides \emph{location-hidden
  98. services}, so that critical servers can support authorized users without
  99. giving adversaries an effective vector for physical or online attacks.
  100. The design provides these protections even when a portion of its own
  101. infrastructure is controlled by an adversary.
  102. To create a private network pathway with Tor, the client software
  103. incrementally builds a \emph{circuit} of encrypted connections through
  104. servers on the network. The circuit is extended one hop at a time, and
  105. each server along the way knows only which server gave it data and which
  106. server it is giving data to. No individual server ever knows the complete
  107. path that a data packet has taken. The client negotiates a separate set
  108. of encryption keys for each hop along the circuit.% to ensure that each
  109. %hop can't trace these connections as they pass through.
  110. Because each server sees no more than one hop in the
  111. circuit, neither an eavesdropper nor a compromised server can use traffic
  112. analysis to link the connection's source and destination.
  113. For efficiency, the Tor software uses the same circuit for all the TCP
  114. connections that happen within the same short period.
  115. Later requests use a new
  116. circuit, to prevent long-term linkability between different actions by
  117. a single user.
  118. Tor also makes it possible for users to hide their locations while
  119. offering various kinds of services, such as web publishing or an instant
  120. messaging server. Using ``rendezvous points'', other Tor users can
  121. connect to these hidden services, each without knowing the other's network
  122. identity.
  123. Tor attempts to anonymize the transport layer, not the application layer, so
  124. application protocols that include personally identifying information need
  125. additional application-level scrubbing proxies, such as
  126. Privoxy~\cite{privoxy} for HTTP. Furthermore, Tor does not permit arbitrary
  127. IP packets; it only anonymizes TCP streams and DNS request, and only supports
  128. connections via SOCKS (see Section~\ref{subsec:tcp-vs-ip}).
  129. Most servers operators do not want to allow arbitary TCP connections to leave
  130. their servers. To address this, Tor provides \emph{exit policies} so that
  131. each server can block the IP addresses and ports it is unwilling to allow.
  132. Servers advertise their exit policies to the directory servers, so that
  133. client can tell which servers will support their connections.
  134. As of January 2005, the Tor network has grown to around a hundred servers
  135. on four continents, with a total capacity exceeding 1Gbit/s. Appendix A
  136. shows a graph of the number of working servers over time, as well as a
  137. vgraph of the number of bytes being handled by the network over time. At
  138. this point the network is sufficiently diverse for further development
  139. and testing; but of course we always encourage and welcome new servers
  140. to join the network.
  141. Tor research and development has been funded by the U.S.~Navy and DARPA
  142. for use in securing government
  143. communications, and by the Electronic Frontier Foundation, for use
  144. in maintaining civil liberties for ordinary citizens online. The Tor
  145. protocol is one of the leading choices
  146. to be the anonymizing layer in the European Union's PRIME directive to
  147. help maintain privacy in Europe. The University of Dresden in Germany
  148. has integrated an independent implementation of the Tor protocol into
  149. their popular Java Anon Proxy anonymizing client.
  150. % This wide variety of
  151. %interests helps maintain both the stability and the security of the
  152. %network.
  153. \subsubsection{Threat models and design philosophy}
  154. The ideal Tor network would be practical, useful and and anonymous. When
  155. trade-offs arise between these properties, Tor's research strategy has been
  156. to insist on remaining useful enough to attract many users,
  157. and practical enough to support them. Only subject to these
  158. constraints do we aim to maximize
  159. anonymity.\footnote{This is not the only possible
  160. direction in anonymity research: designs exist that provide more anonymity
  161. than Tor at the expense of significantly increased resource requirements, or
  162. decreased flexibility in application support (typically because of increased
  163. latency). Such research does not typically abandon aspirations towards
  164. deployability or utility, but instead tries to maximize deployability and
  165. utility subject to a certain degree of inherent anonymity (inherent because
  166. usability and practicality affect usage which affects the actual anonymity
  167. provided by the network \cite{back01,econymics}).}
  168. %{We believe that these
  169. %approaches can be promising and useful, but that by focusing on deploying a
  170. %usable system in the wild, Tor helps us experiment with the actual parameters
  171. %of what makes a system ``practical'' for volunteer operators and ``useful''
  172. %for home users, and helps illuminate undernoticed issues which any deployed
  173. %volunteer anonymity network will need to address.}
  174. Because of this strategy, Tor has a weaker threat model than many anonymity
  175. designs in the literature. In particular, because we
  176. support interactive communications without impractically expensive padding,
  177. we fall prey to a variety
  178. of intra-network~\cite{back01,attack-tor-oak05,flow-correlation04} and
  179. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  180. Tor does not attempt to defend against a global observer. In general, an
  181. attacker who can observe both ends of a connection through the Tor network
  182. can correlate the timing and volume of data on that connection as it enters
  183. and leaves the network, and so link a user to her chosen communication
  184. parties. Known solutions to this attack would seem to require introducing a
  185. prohibitive degree of traffic padding between the user and the network, or
  186. introducing an unacceptable degree of latency (but see Section
  187. \ref{subsec:mid-latency}). Also, it is not clear that these methods would
  188. work at all against a minimally active adversary that can introduce timing
  189. patterns or additional traffic. Thus, Tor only attempts to defend against
  190. external observers who cannot observe both sides of a user's connection.
  191. Against internal attackers who sign up Tor servers, the situation is more
  192. complicated. In the simplest case, if an adversary has compromised $c$ of
  193. $n$ servers on the Tor network, then the adversary will be able to compromise
  194. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  195. initiator chooses hops randomly). But there are
  196. complicating factors:
  197. \begin{tightlist}
  198. \item If the user continues to build random circuits over time, an adversary
  199. is pretty certain to see a statistical sample of the user's traffic, and
  200. thereby can build an increasingly accurate profile of her behavior. (See
  201. \ref{subsec:helper-nodes} for possible solutions.)
  202. \item An adversary who controls a popular service outside of the Tor network
  203. can be certain of observing all connections to that service; he
  204. therefore will trace connections to that service with probability
  205. $\frac{c}{n}$.
  206. \item Users do not in fact choose servers with uniform probability; they
  207. favor servers with high bandwidth or uptime, and exit servers that
  208. permit connections to their favorite services.
  209. \end{tightlist}
  210. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  211. %the last hop is not $c/n$ since that doesn't take the destination (website)
  212. %into account. so in cases where the adversary does not also control the
  213. %final destination we're in good shape, but if he *does* then we'd be better
  214. %off with a system that lets each hop choose a path.
  215. %
  216. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  217. % dest, we would be just as well off with such as system.'' ? If not, why
  218. % not? -nm
  219. % Sure. In fact, better off, since they seem to scale more easily. -rd
  220. % XXXX the below paragraph should probably move later, and merge with
  221. % other discussions of attack-tor-oak5.
  222. See \ref{subsec:routing-zones} for discussion of larger
  223. adversaries and our dispersal goals.
  224. %Murdoch and Danezis describe an attack
  225. %\cite{attack-tor-oak05} that lets an attacker determine the nodes used
  226. %in a circuit; yet s/he cannot identify the initiator or responder,
  227. %e.g., client or web server, through this attack. So the endpoints
  228. %remain secure, which is the goal. It is conceivable that an
  229. %adversary could attack or set up observation of all connections
  230. %to an arbitrary Tor node in only a few minutes. If such an adversary
  231. %were to exist, s/he could use this probing to remotely identify a node
  232. %for further attack. Of more likely immediate practical concern
  233. %an adversary with active access to the responder traffic
  234. %wants to keep a circuit alive long enough to attack an identified
  235. %node. Thus it is important to prevent the responding end of the circuit
  236. %from keeping it open indefinitely.
  237. %Also, someone could identify nodes in this way and if in their
  238. %jurisdiction, immediately get a subpoena (if they even need one)
  239. %telling the node operator(s) that she must retain all the active
  240. %circuit data she now has.
  241. %Further, the enclave model, which had previously looked to be the most
  242. %generally secure, seems particularly threatened by this attack, since
  243. %it identifies endpoints when they're also nodes in the Tor network:
  244. %see Section~\ref{subsec:helper-nodes} for discussion of some ways to
  245. %address this issue.
  246. \subsubsection{Distributed trust}
  247. In practice Tor's threat model is based entirely on the goal of
  248. dispersal and diversity.
  249. Tor's defense lies in having a diverse enough set of servers
  250. to prevent most real-world
  251. adversaries from being in the right places to attack users.
  252. Tor aims to resist observers and insiders by distributing each transaction
  253. over several nodes in the network. This ``distributed trust'' approach
  254. means the Tor network can be safely operated and used by a wide variety
  255. of mutually distrustful users, providing more sustainability and security
  256. than some previous attempts at anonymizing networks.
  257. The Tor network has a broad range of users, including ordinary citizens
  258. concerned about their privacy, corporations
  259. who don't want to reveal information to their competitors, and law
  260. enforcement and government intelligence agencies who need
  261. to do operations on the Internet without being noticed.
  262. No organization can achieve this security on its own. If a single
  263. corporation or government agency were to build a private network to
  264. protect its operations, any connections entering or leaving that network
  265. would be obviously linkable to the controlling organization. The members
  266. and operations of that agency would be easier, not harder, to distinguish.
  267. Instead, to protect our networks from traffic analysis, we must
  268. collaboratively blend the traffic from many organizations and private
  269. citizens, so that an eavesdropper can't tell which users are which,
  270. and who is looking for what information. By bringing more users onto
  271. the network, all users become more secure~\cite{econymics}.
  272. Naturally, organizations will not want to depend on others for their
  273. security. If most participating providers are reliable, Tor tolerates
  274. some hostile infiltration of the network. For maximum protection,
  275. the Tor design includes an enclave approach that lets data be encrypted
  276. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  277. hasn't been read or modified. This even works for Internet services that
  278. don't have built-in encryption and authentication, such as unencrypted
  279. HTTP or chat, and it requires no modification of those services.
  280. %Tor doesn't try to provide steg (but see Section~\ref{subsec:china}), or
  281. %the other non-goals listed in tor-design.
  282. \subsection{Related work}
  283. Tor is not the only anonymity system that aims to be practical and useful.
  284. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  285. open proxies around the Internet, can provide good
  286. performance and some security against a weaker attacker. The Java
  287. Anon Proxy~\cite{web-mix} provides similar functionality to Tor but only
  288. handles web browsing rather than arbitrary TCP\@.
  289. %Some peer-to-peer file-sharing overlay networks such as
  290. %Freenet~\cite{freenet} and Mute~\cite{mute}
  291. Zero-Knowledge Systems' commercial Freedom
  292. network~\cite{freedom21-security} was even more flexible than Tor in
  293. that it could transport arbitrary IP packets, and it also supported
  294. pseudonymous access rather than just anonymous access; but it had
  295. a different approach to sustainability (collecting money from users
  296. and paying ISPs to run servers), and has shut down due to financial
  297. load. Finally, more scalable designs like Tarzan~\cite{tarzan:ccs02} and
  298. MorphMix~\cite{morphmix:fc04} have been proposed in the literature, but
  299. have not yet been fielded. We direct the interested reader to Section
  300. 2 of~\cite{tor-design} for a more in-depth review of related work.
  301. Tor differs from other deployed systems for traffic analysis resistance
  302. in its security and flexibility. Mix networks such as
  303. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  304. gain the highest degrees of anonymity at the expense of introducing highly
  305. variable delays, thus making them unsuitable for applications such as web
  306. browsing. Commercial single-hop
  307. proxies~\cite{anonymizer} present a single point of failure, where
  308. a single compromise can expose all users' traffic, and a single-point
  309. eavesdropper can perform traffic analysis on the entire network.
  310. Also, their proprietary implementations place any infrastucture that
  311. depends on these single-hop solutions at the mercy of their providers'
  312. financial health as well as network security.
  313. %XXXX six-four. crowds. i2p.
  314. %XXXX
  315. have a serious discussion of morphmix's assumptions, since they would
  316. seem to be the direct competition. in fact tor is a flexible architecture
  317. that would encompass morphmix, and they're nearly identical except for
  318. path selection and node discovery. and the trust system morphmix has
  319. seems overkill (and/or insecure) based on the threat model we've picked.
  320. % this para should probably move to the scalability / directory system. -RD
  321. \section{Crossroads: Policy issues}
  322. \label{sec:crossroads-policy}
  323. Many of the issues the Tor project needs to address extend beyond
  324. system design and technology development. In particular, the
  325. Tor project's \emph{image} with respect to its users and the rest of
  326. the Internet impacts the security it can provide.
  327. % No image, no sustainability -NM
  328. With this image issue in mind, this section discusses the Tor user base and
  329. Tor's interaction with other services on the Internet.
  330. \subsection{Communicating security}
  331. A growing field of papers argue that usability for anonymity systems
  332. contributes directly to their security, because how usable the system
  333. is impacts the possible anonymity set~\cite{back01,econymics}. Or
  334. conversely, an unusable system attracts few users and thus can't provide
  335. much anonymity.
  336. This phenomenon has a second-order effect: knowing this, users should
  337. choose which anonymity system to use based in part on how usable
  338. \emph{others} will find it, in order to get the protection of a larger
  339. anonymity set. Thus we might replace the adage ``usability is a security
  340. parameter''~\cite{back01} with a new one: ``perceived usability is a
  341. security parameter.'' From here we can better understand the effects
  342. of publicity and advertising on security: the more convincing your
  343. advertising, the more likely people will believe you have users, and thus
  344. the more users you will attract. Perversely, over-hyped systems (if they
  345. are not too broken) may be a better choice than modestly promoted ones,
  346. if the hype attracts more users~\cite{usability-network-effect}.
  347. So it follows that we should come up with ways to accurately communicate
  348. the available security levels to the user, so she can make informed
  349. decisions. JAP aims to do this by including a
  350. comforting `anonymity meter' dial in the software's graphical interface,
  351. giving the user an impression of the level of protection for her current
  352. traffic.
  353. However, there's a catch. For users to share the same anonymity set,
  354. they need to act like each other. An attacker who can distinguish
  355. a given user's traffic from the rest of the traffic will not be
  356. distracted by other users on the network. For high-latency systems like
  357. Mixminion, where the threat model is based on mixing messages with each
  358. other, there's an arms race between end-to-end statistical attacks and
  359. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  360. But for low-latency systems like Tor, end-to-end \emph{traffic
  361. correlation} attacks~\cite{danezis-pet2004,SS03,defensive-dropping}
  362. allow an attacker who can measure both ends of a communication
  363. to match packet timing and volume, quickly linking
  364. the initiator to her destination. This is why Tor's threat model is
  365. based on preventing the adversary from observing both the initiator and
  366. the responder.
  367. Like Tor, the current JAP implementation does not pad connections
  368. (apart from using small fixed-size cells for transport). In fact,
  369. its cascade-based network topology may be even more vulnerable to these
  370. attacks, because the network has fewer edges. JAP was born out of
  371. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  372. every user had a fixed bandwidth allocation, but in its current context
  373. as a general Internet web anonymizer, adding sufficient padding to JAP
  374. would be prohibitively expensive.\footnote{Even if they could find and
  375. maintain extra funding to run higher-capacity nodes, our experience
  376. suggests that many users would not accept the increased per-user
  377. bandwidth requirements, leading to an overall much smaller user base. But
  378. see Section \ref{subsec:mid-latency}.} Therefore, since under this threat
  379. model the number of concurrent users does not seem to have much impact
  380. on the anonymity provided, we suggest that JAP's anonymity meter is not
  381. correctly communicating security levels to its users.
  382. % because more users don't help anonymity much, we need to rely more
  383. % on other incentive schemes, both policy-based (see sec x) and
  384. % technically enforced (see sec y)
  385. On the other hand, while the number of active concurrent users may not
  386. matter as much as we'd like, it still helps to have some other users
  387. who use the network. We investigate this issue in the next section.
  388. \subsection{Reputability and perceived social value}
  389. Another factor impacting the network's security is its reputability:
  390. the perception of its social value based on its current user base. If Alice is
  391. the only user who has ever downloaded the software, it might be socially
  392. accepted, but she's not getting much anonymity. Add a thousand animal rights
  393. activists, and she's anonymous, but everyone thinks she's a Bambi lover (or
  394. NRA member if you prefer a contrasting example). Add a thousand
  395. random citizens (cancer survivors, privacy enthusiasts, and so on)
  396. and now she's harder to profile.
  397. Furthermore, the network's reputability effects its server base: more people
  398. are willing to run a service if they believe it will be used by human rights
  399. workers than if they believe it will be used exclusively for disreputable
  400. ends. This effect becomes stronger if server operators themselves think they
  401. will be associated with these disreputable ends.
  402. So the more cancer survivors on Tor, the better for the human rights
  403. activists. The more malicious hackers, the worse for the normal users. Thus,
  404. reputability is an anonymity issue for two reasons. First, it impacts
  405. the sustainability of the network: a network that's always about to be
  406. shut down has difficulty attracting and keeping servers, so its diversity
  407. suffers. Second, a disreputable network is more vulnerable to legal and
  408. political attacks, since it will attract fewer supporters.
  409. While people therefore have an incentive for the network to be used for
  410. ``more reputable'' activities than their own, there are still tradeoffs
  411. involved when it comes to anonymity. To follow the above example, a
  412. network used entirely by cancer survivors might welcome some NRA members
  413. onto the network, though of course they'd prefer a wider
  414. variety of users.
  415. Reputability becomes even more tricky in the case of privacy networks,
  416. since the good uses of the network (such as publishing by journalists in
  417. dangerous countries) are typically kept private, whereas network abuses
  418. or other problems tend to be more widely publicized.
  419. The impact of public perception on security is especially important
  420. during the bootstrapping phase of the network, where the first few
  421. widely publicized uses of the network can dictate the types of users it
  422. attracts next.
  423. As an example, some some U.S.~Department of Energy
  424. penetration testing engineers are tasked with compromising DoE computers
  425. from the outside. They only have a limited number of ISPs from which to
  426. launch their attacks, and they found that the defenders were recognizing
  427. attacks because they came from the same IP space. These engineers wanted
  428. to use Tor to hide their tracks. First, from a technical standpoint,
  429. Tor does not support the variety of IP packets one would like to use in
  430. such attacks (see Section~\ref{subsec:tcp-vs-ip}). But aside from this,
  431. we also decided that it would probably be poor precedent to encourage
  432. such use---even legal use that improves national security---and managed
  433. to dissuade them.
  434. %% "outside of academia, jap has just lost, permanently". (That is,
  435. %% even though the crime detection issues are resolved and are unlikely
  436. %% to go down the same way again, public perception has not been kind.)
  437. \subsection{Sustainability and incentives}
  438. One of the unsolved problems in low-latency anonymity designs is
  439. how to keep the servers running. Zero-Knowledge Systems's Freedom network
  440. depended on paying third parties to run its servers; the JAP project's
  441. bandwidth depends on grants to pay for its bandwidth and
  442. administrative expenses. In Tor, bandwidth and administrative costs are
  443. distributed across the volunteers who run Tor nodes, so we at least have
  444. reason to think that the Tor network could survive without continued research
  445. funding.\footnote{It also helps that Tor is implemented with free and open
  446. source software that can be maintained by anybody with the ability and
  447. inclination.} But why are these volunteers running nodes, and what can we
  448. do to encourage more volunteers to do so?
  449. We have not surveyed Tor operators to learn why they are running servers, but
  450. from the information they have provided, it seems that many of them run Tor
  451. nodes for reasons of personal interest in privacy issues. It is possible
  452. that others are running Tor for anonymity reasons, but of course they are
  453. hardly likely to tell us if they are.
  454. Significantly, Tor's threat model changes the anonymity incentives for running
  455. a server. In a high-latency mix network, users can receive additional
  456. anonymity by running their own server, since doing so obscures when they are
  457. injecting messages into the network. But in Tor, anybody observing a Tor
  458. server can tell when the server is generating traffic that corresponds to
  459. none of its incoming traffic.
  460. Still, anonymity and privacy incentives do remain for server operators:
  461. \begin{tightlist}
  462. \item Against a hostile website, running a Tor exit node can provide a degree
  463. of ``deniability'' for traffic that originates at that exit node. For
  464. example, it is likely in practice that HTTP requests from a Tor server's IP
  465. will be assumed to be from the Tor network.
  466. \item People and organizations who use Tor for anonymity depend on the
  467. continued existence of the Tor network to do so; running a server helps to
  468. keep the network operational.
  469. %\item Local Tor entry and exit servers allow users on a network to run in an
  470. % `enclave' configuration. [XXXX need to resolve this. They would do this
  471. % for E2E encryption + auth?]
  472. \end{tightlist}
  473. We must try to make the costs of running a Tor server easily minimized.
  474. Since Tor is run by volunteers, the most crucial software usability issue is
  475. usability by operators: when an operator leaves, the network becomes less
  476. usable by everybody. To keep operators pleased, we must try to keep Tor's
  477. resource and administrative demands as low as possible.
  478. Because of ISP billing structures, many Tor operators have underused capacity
  479. that they are willing to donate to the network, at no additional monetary
  480. cost to them. Features to limit bandwidth have been essential to adoption.
  481. Also useful has been a ``hibernation'' feature that allows a server that
  482. wants to provide high bandwidth, but no more than a certain amount in a
  483. giving billing cycle, to become dormant once its bandwidth is exhausted, and
  484. to reawaken at a random offset into the next billing cycle. This feature has
  485. interesting policy implications, however; see
  486. section~\ref{subsec:bandwidth-and-filesharing} below.
  487. Exit policies help to limit administrative costs by limiting the frequency of
  488. abuse complaints.
  489. %[XXXX say more. Why else would you run a server? What else can we do/do we
  490. % already do to make running a server more attractive?]
  491. %[We can enforce incentives; see Section 6.1. We can rate-limit clients.
  492. % We can put "top bandwidth servers lists" up a la seti@home.]
  493. \subsection{Bandwidth and filesharing}
  494. \label{subsec:bandwidth-and-filesharing}
  495. %One potentially problematical area with deploying Tor has been our response
  496. %to file-sharing applications.
  497. Once users have configured their applications to work with Tor, the largest
  498. remaining usability issue is bandwidth. When websites ``feel slow,'' users
  499. begin to suffer.
  500. Clients currently try to build their connections through servers that they
  501. guess will have enough bandwidth. But even if capacity is allocated
  502. optimally, it seems unlikely that the current network architecture will have
  503. enough capacity to provide every user with as much bandwidth as she would
  504. receive if she weren't using Tor, unless far more servers join the network
  505. (see above).
  506. %Limited capacity does not destroy the network, however. Instead, usage tends
  507. %towards an equilibrium: when performance suffers, users who value performance
  508. %over anonymity tend to leave the system, thus freeing capacity until the
  509. %remaining users on the network are exactly those willing to use that capacity
  510. %there is.
  511. Much of Tor's recent bandwidth difficulties have come from file-sharing
  512. applications. These applications provide two challenges to
  513. any anonymizing network: their intensive bandwidth requirement, and the
  514. degree to which they are associated (correctly or not) with copyright
  515. violation.
  516. As noted above, high-bandwidth protocols can make the network unresponsive,
  517. but tend to be somewhat self-correcting. Issues of copyright violation,
  518. however, are more interesting. Typical exit node operators want to help
  519. people achieve private and anonymous speech, not to help people (say) host
  520. Vin Diesel movies for download; and typical ISPs would rather not
  521. deal with customers who incur them the overhead of getting menacing letters
  522. from the MPAA. While it is quite likely that the operators are doing nothing
  523. illegal, many ISPs have policies of dropping users who get repeated legal
  524. threats regardless of the merits of those threats, and many operators would
  525. prefer to avoid receiving legal threats even if those threats have little
  526. merit. So when the letters arrive, operators are likely to face
  527. pressure to block filesharing applications entirely, in order to avoid the
  528. hassle.
  529. But blocking filesharing would not necessarily be easy; most popular
  530. protocols have evolved to run on a variety of non-standard ports in order to
  531. get around other port-based bans. Thus, exit node operators who wanted to
  532. block filesharing would have to find some way to integrate Tor with a
  533. protocol-aware exit filter. This could be a technically expensive
  534. undertaking, and one with poor prospects: it is unlikely that Tor exit nodes
  535. would succeed where so many institutional firewalls have failed. Another
  536. possibility for sensitive operators is to run a restrictive server that
  537. only permits exit connections to a restricted range of ports which are
  538. not frequently associated with file sharing. There are increasingly few such
  539. ports.
  540. Other possible approaches might include rate-limiting connections, especially
  541. long-lived connections or connections to file-sharing ports, so that
  542. high-bandwidth connections do not flood the network. We might also want to
  543. give priority to cells on low-bandwidth connections to keep them interactive,
  544. but this could have negative anonymity implications.
  545. For the moment, it seems that Tor's bandwidth issues have rendered it
  546. unattractive for bulk file-sharing traffic; this may continue to be so in the
  547. future. Nevertheless, Tor will likely remain attractive for limited use in
  548. filesharing protocols that have separate control and data channels.
  549. %[We should say more -- but what? That we'll see a similar
  550. % equilibriating effect as with bandwidth, where sensitive ops switch to
  551. % middleman, and we become less useful for filesharing, so the filesharing
  552. % people back off, so we get more ops since there's less filesharing, so the
  553. % filesharers come back, etc.]
  554. %XXXX
  555. %in practice, plausible deniability is hypothetical and doesn't seem very
  556. %convincing. if ISPs find the activity antisocial, they don't care *why*
  557. %your computer is doing that behavior.
  558. \subsection{Tor and blacklists}
  559. It was long expected that, alongside Tor's legitimate users, it would also
  560. attract troublemakers who exploited Tor in order to abuse services on the
  561. Internet with vandalism, rude mail, and so on.
  562. %[XXX we're not talking bandwidth abuse here, we're talking vandalism,
  563. %hate mails via hotmail, attacks, etc.]
  564. Our initial answer to this situation was to use ``exit policies''
  565. to allow individual Tor servers to block access to specific IP/port ranges.
  566. This approach was meant to make operators more willing to run Tor by allowing
  567. them to prevent their servers from being used for abusing particular
  568. services. For example, all Tor servers currently block SMTP (port 25), in
  569. order to avoid being used to send spam.
  570. This approach is useful, but is insufficient for two reasons. First, since
  571. it is not possible to force all servers to block access to any given service,
  572. many of those services try to block Tor instead. More broadly, while being
  573. blockable is important to being good netizens, we would like to encourage
  574. services to allow anonymous access; services should not need to decide
  575. between blocking legitimate anonymous use and allowing unlimited abuse.
  576. This is potentially a bigger problem than it may appear.
  577. On the one hand, if people want to refuse connections from you on
  578. their servers it would seem that they should be allowed to. But, a
  579. possible major problem with the blocking of Tor is that it's not just
  580. the decision of the individual server administrator whose deciding if
  581. he wants to post to Wikipedia from his Tor node address or allow
  582. people to read Wikipedia anonymously through his Tor node. (Wikipedia
  583. has blocked all posting from all Tor nodes based on IP address.) If e.g.,
  584. s/he comes through a campus or corporate NAT, then the decision must
  585. be to have the entire population behind it able to have a Tor exit
  586. node or to have write access to Wikipedia. This is a loss for both of us (Tor
  587. and Wikipedia). We don't want to compete for (or divvy up) the NAT
  588. protected entities of the world.
  589. (A related problem is that many IP blacklists are not terribly fine-grained.
  590. No current IP blacklist, for example, allow a service provider to blacklist
  591. only those Tor servers that allow access to a specific IP or port, even
  592. though this information is readily available. One IP blacklist even bans
  593. every class C network that contains a Tor server, and recommends banning SMTP
  594. from these networks even though Tor does not allow SMTP at all. This
  595. coarse-grained approach is typically a strategic decision to discourage the
  596. operation of anything resembling an open proxy by encouraging its neighbors
  597. to shut it down in order to get unblocked themselves.)
  598. %[****Since this is stupid and we oppose it, shouldn't we name names here -pfs]
  599. %[XXX also, they're making \emph{middleman nodes leave} because they're caught
  600. % up in the standoff!]
  601. %[XXX Mention: it's not dumb, it's strategic!]
  602. %[XXX Mention: for some servops, any blacklist is a blacklist too many,
  603. % because it is risky. (Guy lives in apt with one IP.)]
  604. Problems of abuse occur mainly with services such as IRC networks and
  605. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  606. blush this practice might seem to depend on the anachronistic assumption that
  607. each IP is an identifier for a single user, it is actually more reasonable in
  608. practice: it assumes that non-proxy IPs are a costly resource, and that an
  609. abuser can not change IPs at will. By blocking IPs which are used by Tor
  610. servers, open proxies, and service abusers, these systems hope to make
  611. ongoing abuse difficult. Although the system is imperfect, it works
  612. tolerably well for them in practice.
  613. But of course, we would prefer that legitimate anonymous users be able to
  614. access abuse-prone services. One conceivable approach would be to require
  615. would-be IRC users, for instance, to register accounts if they wanted to
  616. access the IRC network from Tor. But in practise, this would not
  617. significantly impede abuse if creating new accounts were easily automatable;
  618. this is why services use IP blocking. In order to deter abuse, pseudonymous
  619. identities need to require a significant switching cost in resources or human
  620. time.
  621. % XXX Mention captchas?
  622. %One approach, similar to that taken by Freedom, would be to bootstrap some
  623. %non-anonymous costly identification mechanism to allow access to a
  624. %blind-signature pseudonym protocol. This would effectively create costly
  625. %pseudonyms, which services could require in order to allow anonymous access.
  626. %This approach has difficulties in practise, however:
  627. %\begin{tightlist}
  628. %\item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  629. % be a shame to require payment in order to make Tor useful, or to make
  630. % non-paying users second-class citizens.
  631. %\item It is hard to think of an underlying resource that would actually work.
  632. % We could use IP addresses, but that's the problem, isn't it?
  633. %\item Managing single sign-on services is not considered a well-solved
  634. % problem in practice. If Microsoft can't get universal acceptance for
  635. % Passport, why do we think that a Tor-specific solution would do any good?
  636. %\item Even if we came up with a perfect authentication system for our needs,
  637. % there's no guarantee that any service would actually start using it. It
  638. % would require a nonzero effort for them to support it, and it might just
  639. % be less hassle for them to block tor anyway.
  640. %\end{tightlist}
  641. The use of squishy IP-based ``authentication'' and ``authorization''
  642. has not broken down even to the level that SSNs used for these
  643. purposes have in commercial and public record contexts. Externalities
  644. and misplaced incentives cause a continued focus on fighting identity
  645. theft by protecting SSNs rather than developing better authentication
  646. and incentive schemes \cite{price-privacy}. Similarly we can expect a
  647. continued use of identification by IP number as long as there is no
  648. workable alternative.
  649. %Fortunately, our modular design separates
  650. %routing from node discovery; so we could implement Morphmix in Tor just
  651. %by implementing the Morphmix-specific node discovery and path selection
  652. %pieces.
  653. %[XXX Mention correct DNS-RBL implementation. -NM]
  654. \section{Crossroads: Design choices}
  655. \label{sec:crossroads-design}
  656. In addition to social issues, Tor also faces some design challenges that must
  657. be addressed as the network develops.
  658. \subsection{Transporting the stream vs transporting the packets}
  659. \label{subsec:stream-vs-packet}
  660. \label{subsec:tcp-vs-ip}
  661. Tor transports streams; it does not tunnel packets. We periodically
  662. run into developers of the old Freedom network~\cite{freedom21-security}
  663. who tell us that anonymizing IP addresses should ``obviously'' be done
  664. at the IP layer. Here are the issues that need to be resolved before
  665. we'll be ready to switch Tor over to arbitrary IP traffic.
  666. \begin{enumerate}
  667. \setlength{\itemsep}{0mm}
  668. \setlength{\parsep}{0mm}
  669. \item \emph{IP packets reveal OS characteristics.} We still need to do
  670. IP-level packet normalization, to stop things like IP fingerprinting
  671. attacks. There likely exist libraries that can help with this.
  672. \item \emph{Application-level streams still need scrubbing.} We still need
  673. Tor to be easy to integrate with user-level application-specific proxies
  674. such as Privoxy. So it's not just a matter of capturing packets and
  675. anonymizing them at the IP layer.
  676. \item \emph{Certain protocols will still leak information.} For example,
  677. DNS requests destined for my local DNS servers need to be rewritten
  678. to be delivered to some other unlinkable DNS server. This requires
  679. understanding the protocols we are transporting.
  680. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  681. approach that can provide security despite
  682. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  683. never publicly specified.
  684. Also, TLS over UDP is not implemented or even
  685. specified, though some early work has begun on that~\cite{dtls}.
  686. \item \emph{We'll still need to tune network parameters}. Since the above
  687. encryption system will likely need sequence numbers (and maybe more) to do
  688. replay detection, handle duplicate frames, etc, we will be reimplementing
  689. some subset of TCP anyway.
  690. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  691. IDS.} Our server operators tell us that exit policies are one of
  692. the main reasons they're willing to run Tor.
  693. Adding an Intrusion Detection System to handle exit policies would
  694. increase the security complexity of Tor, and would likely not work anyway,
  695. as evidenced by the entire field of IDS and counter-IDS papers. Many
  696. potential abuse issues are resolved by the fact that Tor only transports
  697. valid TCP streams (as opposed to arbitrary IP including malformed packets
  698. and IP floods), so exit policies become even \emph{more} important as
  699. we become able to transport IP packets. We also need a way to compactly
  700. characterize the exit policies and let clients parse them to predict
  701. which nodes will allow which packets to exit.
  702. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  703. support hidden service {\tt{.onion}} addresses, and other special addresses
  704. like {\tt{.exit}} for the user to request a particular exit server,
  705. by intercepting the addresses when they are passed to the Tor client.
  706. \end{enumerate}
  707. This list is discouragingly long right now, but we recognize that it
  708. would be good to investigate each of these items in further depth and to
  709. understand which are actual roadblocks and which are easier to resolve
  710. than we think. We certainly wouldn't mind if Tor one day is able to
  711. transport a greater variety of protocols.
  712. [XXX clarify our actual attitude here. -NM]
  713. To be fair, Tor's stream-based approach has run into practical
  714. stumbling blocks as well. While Tor supports the SOCKS protocol,
  715. which provides a standardized interface for generic TCP proxies, many
  716. applications do not support SOCKS. Supporting such applications requires
  717. replacing the networking system calls with SOCKS-aware
  718. versions, or running a SOCKS tunnel locally, neither of which is
  719. easy for the average user---even with good instructions.
  720. Even when applications do use SOCKS, they often make DNS requests
  721. themselves. (The various versions of the SOCKS protocol include some where
  722. the application tells the proxy an IP address, and some where it sends a
  723. hostname.) By connecting to the DNS server directly, the application breaks
  724. the user's anonymity and advertises where it is about to connect.
  725. So in order to actually provide good anonymity, we need to make sure that
  726. users have a practical way to use Tor anonymously. Possibilities include
  727. writing wrappers for applications to anonymize them automatically; improving
  728. the applications' support for SOCKS; writing libraries to help application
  729. writers use Tor properly; and implementing a local DNS proxy to reroute DNS
  730. requests to Tor so that applications can simply point their DNS resolvers at
  731. localhost and continue to use SOCKS for data only.
  732. \subsection{Mid-latency}
  733. \label{subsec:mid-latency}
  734. Some users need to resist traffic correlation attacks. Higher-latency
  735. mix-networks resist these attacks by introducing variability into message
  736. arrival times: as timing variance increases, timing correlation attacks
  737. require increasingly more data~\cite{e2e-traffic}. Can we improve Tor's
  738. resistance to these attacks without losing too much usability?
  739. %by introducing batching
  740. %and delaying strategies to the Tor messages?
  741. First, we need to learn whether we can trade a small increase in latency
  742. for a large anonymity increase, or if we'll end up trading a lot of
  743. latency for a small security gain. It would be worthwhile even if we
  744. can only protect certain use cases, such as infrequent short-duration
  745. transactions.
  746. In order to answer this question, we might
  747. try to adapt the techniques of~\cite{e2e-traffic} to a lower-latency mix
  748. network, where instead of sending messages, users send batches
  749. of cells in temporally clustered connections.
  750. Once the anonymity questions are answered, we need to consider usability. If
  751. the latency could be kept to two or three times its current overhead, this
  752. might be acceptable to most Tor users. However, it might also destroy much of
  753. the user base, and it is difficult to know in advance. Note also that in
  754. practice, as the network grows to incorporate more DSL and cable-modem nodes,
  755. and more nodes in various continents, this alone will \emph{already} cause
  756. many-second delays for some transactions. Reducing this latency will be
  757. hard, so perhaps it's worth considering whether accepting this higher latency
  758. can improve the anonymity we provide. Also, it could be possible to
  759. run a mid-latency option over the Tor network for those
  760. users either willing to experiment or in need of more
  761. anonymity. This would allow us to experiment with both
  762. the anonymity provided and the interest on the part of users.
  763. Adding a mid-latency option should not require significant fundamental
  764. change to the Tor client or server design; circuits could be labeled as
  765. low- or mid- latency as they are constructed. Low-latency traffic
  766. would be processed as now, while cells on circuits that are mid-latency
  767. would be sent in uniform-size chunks at synchronized intervals. (Traffic
  768. already moves through the Tor network in fixed-sized cells; this would
  769. increase the granularity.) If servers forward these chunks in roughly
  770. synchronous fashion, it will increase the similarity of data stream timing
  771. signatures. By experimenting with the granularity of data chunks and
  772. of synchronization we can attempt once again to optimize for both
  773. usability and anonymity. Unlike in \cite{sync-batching}, it may be
  774. impractical to synchronize on network batches by dropping chunks from
  775. a batch that arrive late at a given node---unless Tor moves away from
  776. stream processing to a more loss-tolerant paradigm (cf.\
  777. Section~\ref{subsec:tcp-vs-ip}). Instead, batch timing would be obscured by
  778. synchronizing batches at the link level, and there would
  779. be no direct attempt to synchronize all batches
  780. entering the Tor network at the same time.
  781. %Alternatively, if end-to-end traffic correlation is the
  782. %concern, there is little point in mixing.
  783. % Why not?? -NM
  784. It might also be feasible to
  785. pad chunks to uniform size as is done now for cells; if this is link
  786. padding rather than end-to-end, then it will take less overhead,
  787. especially in bursty environments.
  788. % This is another way in which it
  789. %would be fairly practical to set up a mid-latency option within the
  790. %existing Tor network.
  791. Other padding regimens might supplement the
  792. mid-latency option; however, we should continue the caution with which
  793. we have always approached padding lest the overhead cost us too much
  794. performance or too many volunteers.
  795. The distinction between traffic correlation and traffic analysis is
  796. not as cut and dried as we might wish. In \cite{hintz-pet02} it was
  797. shown that if data volumes of various popular
  798. responder destinations are catalogued, it may not be necessary to
  799. observe both ends of a stream to learn a source-destination link.
  800. This should be fairly effective without simultaneously observing both
  801. ends of the connection. However, it is still essentially confirming
  802. suspected communicants where the responder suspects are ``stored'' rather
  803. than observed at the same time as the client.
  804. Similarly latencies of going through various routes can be
  805. catalogued~\cite{back01} to connect endpoints.
  806. This is likely to entail high variability and massive storage since
  807. % XXX hintz-pet02 just looked at data volumes of the sites. this
  808. % doesn't require much variability or storage. I think it works
  809. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  810. % attack another level further, to narrow down where you could be
  811. % based on an intersection attack on subpages in a website. -RD
  812. %
  813. % I was trying to be terse and simultaneously referring to both the
  814. % Hintz stuff and the Back et al. stuff from Info Hiding 01. I've
  815. % separated the two and added the references. -PFS
  816. routes through the network to each site will be random even if they
  817. have relatively unique latency characteristics. So this does
  818. not seem an immediate practical threat. Further along similar lines,
  819. the same paper suggested a ``clogging attack''. A version of this
  820. was demonstrated to be practical in
  821. \cite{attack-tor-oak05}. There it was shown that an outside attacker can
  822. trace a stream through the Tor network while a stream is still active
  823. simply by observing the latency of his own traffic sent through
  824. various Tor nodes. These attacks are especially significant since they
  825. counter previous results that running one's own onion router protects
  826. better than using the network from the outside. The attacks do not
  827. show the client address, only the first server within the Tor network,
  828. making helper nodes all the more worthy of exploration for enclave
  829. protection. Setting up a mid-latency subnet as described above would
  830. be another significant step to evaluating resistance to such attacks.
  831. The attacks in \cite{attack-tor-oak05} are also dependent on
  832. cooperation of the responding application or the ability to modify or
  833. monitor the responder stream, in order of decreasing attack
  834. effectiveness. So, another way to slow some of these attacks
  835. would be to cache responses at exit servers where possible, as it is with
  836. DNS lookups and cacheable HTTP responses. Caching would, however,
  837. create threats of its own. First, a Tor network is expected to contain
  838. hostile nodes. If one of these is the repository of a cache, the
  839. attack is still possible. Though more work to set up a Tor node and
  840. cache repository, the payoff of such an attack is potentially
  841. higher.
  842. %To be
  843. %useful, such caches would need to be distributed to any likely exit
  844. %nodes of recurred requests for the same data.
  845. % Even local caches could be useful, I think. -NM
  846. %
  847. %Added some clarification -PFS
  848. Besides allowing any other insider attacks, caching nodes would hold a
  849. record of destinations and data visited by Tor users reducing forward
  850. anonymity. Worse, for the cache to be widely useful much beyond the
  851. client that caused it there would have to either be a new mechanism to
  852. distribute cache information around the network and a way for clients
  853. to make use of it or the caches themselves would need to be
  854. distributed widely. Either way the record of visited sites and
  855. downloaded information is made automatically available to an attacker
  856. without having to actively gather it himself. Besides its inherent
  857. value, this could serve as useful data to an attacker deciding which
  858. locations to target for confirmation. A way to counter this
  859. distribution threat might be to only cache at certain semitrusted
  860. helper nodes. This might help specific clients, but it would limit
  861. the general value of caching.
  862. \subsection{Measuring performance and capacity}
  863. \label{subsec:performance}
  864. One of the paradoxes with engineering an anonymity network is that we'd like
  865. to learn as much as we can about how traffic flows so we can improve the
  866. network, but we want to prevent others from learning how traffic flows in
  867. order to trace users' connections through the network. Furthermore, many
  868. mechanisms that help Tor run efficiently (such as having clients choose servers
  869. based on their capacities) require measurements about the network.
  870. Currently, servers record their bandwidth use in 15-minute intervals and
  871. include this information in the descriptors they upload to the directory.
  872. They also try to deduce their own available bandwidth, on the basis of how
  873. much traffic they have been able to transfer recently, and upload this
  874. information as well.
  875. This is, of course, eminently cheatable. A malicious server can get a
  876. disproportionate amount of traffic simply by claiming to have more bandiwdth
  877. than it does. But better mechanisms have their problems. If bandwidth data
  878. is to be measured rather than self-reported, it is usually possible for
  879. servers to selectively provide better service for the measuring party, or
  880. sabotage the measured value of other servers. Complex solutions for
  881. mix networks have been proposed, but do not address the issues
  882. completely~\cite{mix-acc,casc-rep}.
  883. Even without the possibility of cheating, network measurement is
  884. non-trivial. It is far from unusual for one observer's view of a server's
  885. latency or bandwidth to disagree wildly with another's. Furthermore, it is
  886. unclear whether total bandwidth is really the right measure; perhaps clients
  887. should be considering servers on the basis of unused bandwidth instead, or
  888. perhaps observed throughput.
  889. % XXXX say more here?
  890. %How to measure performance without letting people selectively deny service
  891. %by distinguishing pings. Heck, just how to measure performance at all. In
  892. %practice people have funny firewalls that don't match up to their exit
  893. %policies and Tor doesn't deal.
  894. %Network investigation: Is all this bandwidth publishing thing a good idea?
  895. %How can we collect stats better? Note weasel's smokeping, at
  896. %http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  897. %which probably gives george and steven enough info to break tor?
  898. Even if we can collect and use this network information effectively, we need
  899. to make sure that it is not more useful to attackers than to us. While it
  900. seems plausible that bandwidth data alone is not enough to reveal
  901. sender-recipient connections under most circumstances, it could certainly
  902. reveal the path taken by large traffic flows under low-usage circumstances.
  903. \subsection{Running a Tor server, path length, and helper nodes}
  904. It has been thought for some time that the best anonymity protection
  905. comes from running your own onion router~\cite{or-pet00,tor-design}.
  906. (In fact, in Onion Routing's first design, this was the only option
  907. possible~\cite{or-ih96}.) The first design also had a fixed path
  908. length of five nodes. Middle Onion Routing involved much analysis
  909. (mostly unpublished) of route selection algorithms and path length
  910. algorithms to combine efficiency with unpredictability in routes.
  911. Since, unlike Crowds, nodes in a route cannot all know the ultimate
  912. destination of an application connection, it was generally not
  913. considered significant if a node could determine via latency that it
  914. was second in the route. But if one followed Tor's three node default
  915. path length, an enclave-to-enclave communication (in which two of the
  916. ORs were at each enclave) would be completely compromised by the
  917. middle node. Thus for enclave-to-enclave communication, four is the fewest
  918. number of nodes that preserves the $\frac{c^2}{n^2}$ degree of protection
  919. in any setting.
  920. The Murdoch-Danezis attack, however, shows that simply adding to the
  921. path length may not protect usage of an enclave protecting OR\@. A
  922. hostile web server can determine all of the nodes in a three node Tor
  923. path. The attack only identifies that a node is on the route, not
  924. where. For example, if all of the nodes on the route were enclave
  925. nodes, the attack would not identify which of the two not directly
  926. visible to the attacker was the source. Thus, there remains an
  927. element of plausible deniability that is preserved for enclave nodes.
  928. However, Tor has always sought to be stronger than plausible
  929. deniability. Our assumption is that users of the network are concerned
  930. about being identified by an adversary, not with being proven guilty
  931. beyond any reasonable doubt. Still it is something, and may be desired
  932. in some settings.
  933. It is reasonable to think that this attack can be easily extended to
  934. longer paths should those be used; nonetheless there may be some
  935. advantage to random path length. If the number of nodes is unknown,
  936. then the adversary would need to send streams to all the nodes in the
  937. network and analyze the resulting latency from them to be reasonably
  938. certain that it has not missed the first node in the circuit. Also,
  939. the attack does not identify the order of nodes in a route, so the
  940. longer the route, the greater the uncertainty about which node might
  941. be first. It may be possible to extend the attack to learn the route
  942. node order, but has not been shown whether this is practically feasible.
  943. If so, the incompleteness uncertainty engendered by random lengths would
  944. remain, but once the complete set of nodes in the route were identified
  945. the initiating node would also be identified.
  946. Another way to reduce the threats to both enclaves and simple Tor
  947. clients is to have helper nodes. Helper nodes were introduced
  948. in~\cite{wright03} as a suggested means of protecting the identity
  949. of the initiator of a communication in various anonymity protocols.
  950. The idea is to use a single trusted node as the first one you go to,
  951. that way an attacker cannot ever attack the first nodes you connect
  952. to and do some form of intersection attack. This will not affect the
  953. Danezis-Murdoch attack at all if the attacker can time latencies to
  954. both the helper node and the enclave node.
  955. We have to pick the path length so adversary can't distinguish client from
  956. server (how many hops is good?).
  957. \subsection{Helper nodes}
  958. \label{subsec:helper-nodes}
  959. Tor can only provide anonymity against an attacker if that attacker can't
  960. monitor the user's entry and exit on the Tor network. But since Tor
  961. currently chooses entry and exit points randomly and changes them frequently,
  962. a patient attacker who controls a single entry and a single exit is sure to
  963. eventually break some circuits of frequent users who consider those servers.
  964. (We assume that users are as concerned about statistical profiling as about
  965. the anonymity any particular connection. That is, it is almost as bad to
  966. leak the fact that Alice {\it sometimes} talks to Bob as it is to leak the times
  967. when Alice is {\it actually} talking to Bob.)
  968. One solution to this problem is to use ``helper nodes''~\cite{wright02,wright03}---to
  969. have each client choose a few fixed servers for critical positions in her
  970. circuits. That is, Alice might choose some server H1 as her preferred
  971. entry, so that unless the attacker happens to control or observe her
  972. connection to H1, her circuits will remain anonymous. If H1 is compromised,
  973. Alice is vunerable as before. But now, at least, she has a chance of
  974. not being profiled.
  975. (Choosing fixed exit nodes is less useful, since the connection from the exit
  976. node to Alice's destination will be seen not only by the exit but by the
  977. destination. Even if Alice chooses a good fixed exit node, she may
  978. nevertheless connect to a hostile website.)
  979. There are still obstacles remaining before helper nodes can be implemented.
  980. For one, the litereature does not describe how to choose helpers from a list
  981. of servers that changes over time. If Alice is forced to choose a new entry
  982. helper every $d$ days, she can expect to choose a compromised server around
  983. every $dc/n$ days. Worse, an attacker with the ability to DoS servers could
  984. force their users to switch helper nodes more frequently.
  985. %Do general DoS attacks have anonymity implications? See e.g. Adam
  986. %Back's IH paper, but I think there's more to be pointed out here. -RD
  987. % Not sure what you want to say here. -NM
  988. %Game theory for helper nodes: if Alice offers a hidden service on a
  989. %server (enclave model), and nobody ever uses helper nodes, then against
  990. %George+Steven's attack she's totally nailed. If only Alice uses a helper
  991. %node, then she's still identified as the source of the data. If everybody
  992. %uses a helper node (including Alice), then the attack identifies the
  993. %helper node and also Alice, and knows which one is which. If everybody
  994. %uses a helper node (but not Alice), then the attacker figures the real
  995. %source was a client that is using Alice as a helper node. [How's my
  996. %logic here?] -RD
  997. %
  998. % Not sure about the logic. For the attack to work with helper nodes, the
  999. %attacker needs to guess that Alice is running the hidden service, right?
  1000. %Otherwise, how can he know to measure her traffic specifically? -NM
  1001. %point to routing-zones section re: helper nodes to defend against
  1002. %big stuff.
  1003. \subsection{Location-hidden services}
  1004. \label{subsec:hidden-services}
  1005. While most of the discussions about have been about forward anonymity
  1006. with Tor, it also provides support for \emph{rendezvous points}, which
  1007. let users provide TCP services to other Tor users without revealing
  1008. their location. Since this feature is relatively recent, we describe here
  1009. a couple of our early observations from its deployment.
  1010. First, our implementation of hidden services seems less hidden than we'd
  1011. like, since they are configured on a single client and get used over
  1012. and over---particularly because an external adversary can induce them to
  1013. produce traffic. They seem the ideal use case for our above discussion
  1014. of helper nodes. This insecurity means that they may not be suitable as
  1015. a building block for Free Haven~\cite{freehaven-berk} or other anonymous
  1016. publishing systems that aim to provide long-term security.
  1017. %Also, they're brittle in terms of intersection and observation attacks.
  1018. \emph{Hot-swap} hidden services, where more than one location can
  1019. provide the service and loss of any one location does not imply a
  1020. change in service, would help foil intersection and observation attacks
  1021. where an adversary monitors availability of a hidden service and also
  1022. monitors whether certain users or servers are online. However, the design
  1023. challenges in providing these services without otherwise compromising
  1024. the hidden service's anonymity remain an open problem.
  1025. In practice, hidden services are used for more than just providing private
  1026. access to a web server or IRC server. People are using hidden services
  1027. as a poor man's VPN and firewall-buster. Many people want to be able
  1028. to connect to the computers in their private network via secure shell,
  1029. and rather than playing with dyndns and trying to pierce holes in their
  1030. firewall, they run a hidden service on the inside and then rendezvous
  1031. with that hidden service externally.
  1032. Also, sites like Bloggers Without Borders (www.b19s.org) are advertising
  1033. a hidden-service address on their front page. Doing this can provide
  1034. increased robustness if they use the dual-IP approach we describe in
  1035. tor-design, but in practice they do it firstly to increase visibility
  1036. of the tor project and their support for privacy, and secondly to offer
  1037. a way for their users, using unmodified software, to get end-to-end
  1038. encryption and end-to-end authentication to their website.
  1039. \subsection{Trust and discovery}
  1040. \label{subsec:trust-and-discovery}
  1041. [arma will edit this and expand/retract it]
  1042. The published Tor design adopted a deliberately simplistic design for
  1043. authorizing new nodes and informing clients about servers and their status.
  1044. In the early Tor designs, all ORs periodically uploaded a signed description
  1045. of their locations, keys, and capabilities to each of several well-known {\it
  1046. directory servers}. These directory servers constructed a signed summary
  1047. of all known ORs (a ``directory''), and a signed statement of which ORs they
  1048. believed to be operational at any given time (a ``network status''). Clients
  1049. periodically downloaded a directory in order to learn the latest ORs and
  1050. keys, and more frequently downloaded a network status to learn which ORs are
  1051. likely to be running. ORs also operate as directory caches, in order to
  1052. lighten the bandwidth on the authoritative directory servers.
  1053. In order to prevent Sybil attacks (wherein an adversary signs up many
  1054. purportedly independent servers in order to increase her chances of observing
  1055. a stream as it enters and leaves the network), the early Tor directory design
  1056. required the operators of the authoritative directory servers to manually
  1057. approve new ORs. Unapproved ORs were included in the directory, but clients
  1058. did not use them at the start or end of their circuits. In practice,
  1059. directory administrators performed little actual verification, and tended to
  1060. approve any OR whose operator could compose a coherent email. This procedure
  1061. may have prevented trivial automated Sybil attacks, but would do little
  1062. against a clever attacker.
  1063. There are a number of flaws in this system that need to be addressed as we
  1064. move forward. They include:
  1065. \begin{tightlist}
  1066. \item Each directory server represents an independent point of failure; if
  1067. any one were compromised, it could immediately compromise all of its users
  1068. by recommending only compromised ORs.
  1069. \item The more servers appear join the network, the more unreasonable it
  1070. becomes to expect clients to know about them all. Directories
  1071. become unfeasibly large, and downloading the list of servers becomes
  1072. burdonsome.
  1073. \item The validation scheme may do as much harm as it does good. It is not
  1074. only incapable of preventing clever attackers from mounting Sybil attacks,
  1075. but may deter server operators from joining the network. (For instance, if
  1076. they expect the validation process to be difficult, or if they do not share
  1077. any languages in common with the directory server operators.)
  1078. \end{tightlist}
  1079. We could try to move the system in several directions, depending on our
  1080. choice of threat model and requirements. If we did not need to increase
  1081. network capacity in order to support more users, there would be no reason not
  1082. to adopt even stricter validation requirements, and reduce the number of
  1083. servers in the network to a trusted minimum. But since we want Tor to work
  1084. for as many users as it can, we need XXXXX
  1085. In order to address the first two issues, it seems wise to move to a system
  1086. including a number of semi-trusted directory servers, no one of which can
  1087. compromise a user on its own. Ultimately, of course, we cannot escape the
  1088. problem of a first introducer: since most users will run Tor in whatever
  1089. configuration the software ships with, the Tor distribution itself will
  1090. remain a potential single point of failure so long as it includes the seed
  1091. keys for directory servers, a list of directory servers, or any other means
  1092. to learn which servers are on the network. But omitting this information
  1093. from the Tor distribution would only delegate the trust problem to the
  1094. individual users, most of whom are presumably less informed about how to make
  1095. trust decisions than the Tor developers.
  1096. %Network discovery, sybil, node admission, scaling. It seems that the code
  1097. %will ship with something and that's our trust root. We could try to get
  1098. %people to build a web of trust, but no. Where we go from here depends
  1099. %on what threats we have in mind. Really decentralized if your threat is
  1100. %RIAA; less so if threat is to application data or individuals or...
  1101. \section{Scaling}
  1102. %\label{sec:crossroads-scaling}
  1103. %P2P + anonymity issues:
  1104. Tor is running today with hundreds of servers and tens of thousands of
  1105. users, but it will certainly not scale to millions.
  1106. Scaling Tor involves three main challenges. First is safe server
  1107. discovery, both bootstrapping -- how a Tor client can robustly find an
  1108. initial server list -- and ongoing -- how a Tor client can learn about
  1109. a fair sample of honest servers and not let the adversary control his
  1110. circuits (see Section~\ref{subsec:trust-and-discovery}). Second is detecting and handling the speed
  1111. and reliability of the variety of servers we must use if we want to
  1112. accept many servers (see Section~\ref{subsec:performance}).
  1113. Since the speed and reliability of a circuit is limited by its worst link,
  1114. we must learn to track and predict performance. Finally, in order to get
  1115. a large set of servers in the first place, we must address incentives
  1116. for users to carry traffic for others (see Section incentives).
  1117. \subsection{Incentives by Design}
  1118. There are three behaviors we need to encourage for each server: relaying
  1119. traffic; providing good throughput and reliability while doing it;
  1120. and allowing traffic to exit the network from that server.
  1121. We encourage these behaviors through \emph{indirect} incentives, that
  1122. is, designing the system and educating users in such a way that users
  1123. with certain goals will choose to relay traffic. One
  1124. main incentive for running a Tor server is social benefit: volunteers
  1125. altruistically donate their bandwidth and time. We also keep public
  1126. rankings of the throughput and reliability of servers, much like
  1127. seti@home. We further explain to users that they can get plausible
  1128. deniability for any traffic emerging from the same address as a Tor
  1129. exit node, and they can use their own Tor server
  1130. as entry or exit point and be confident it's not run by the adversary.
  1131. Further, users who need to be able to communicate anonymously
  1132. may run a server simply because their need to increase
  1133. expectation that such a network continues to be available to them
  1134. and usable exceeds any countervening costs.
  1135. Finally, we can improve the usability and feature set of the software:
  1136. rate limiting support and easy packaging decrease the hassle of
  1137. maintaining a server, and our configurable exit policies allow each
  1138. operator to advertise a policy describing the hosts and ports to which
  1139. he feels comfortable connecting.
  1140. To date these appear to have been adequate. As the system scales or as
  1141. new issues emerge, however, we may also need to provide
  1142. \emph{direct} incentives:
  1143. providing payment or other resources in return for high-quality service.
  1144. Paying actual money is problematic: decentralized e-cash systems are
  1145. not yet practical, and a centralized collection system not only reduces
  1146. robustness, but also has failed in the past (the history of commercial
  1147. anonymizing networks is littered with failed attempts). A more promising
  1148. option is to use a tit-for-tat incentive scheme: provide better service
  1149. to nodes that have provided good service to you.
  1150. Unfortunately, such an approach introduces new anonymity problems.
  1151. There are many surprising ways for servers to game the incentive and
  1152. reputation system to undermine anonymity because such systems are
  1153. designed to encourage fairness in storage or bandwidth usage not
  1154. fairness of provided anonymity. An adversary can attract more traffic
  1155. by performing well or can provide targeted differential performance to
  1156. individual users to undermine their anonymity. Typically a user who
  1157. chooses evenly from all options is most resistant to an adversary
  1158. targeting him, but that approach prevents from handling heterogeneous
  1159. servers.
  1160. %When a server (call him Steve) performs well for Alice, does Steve gain
  1161. %reputation with the entire system, or just with Alice? If the entire
  1162. %system, how does Alice tell everybody about her experience in a way that
  1163. %prevents her from lying about it yet still protects her identity? If
  1164. %Steve's behavior only affects Alice's behavior, does this allow Steve to
  1165. %selectively perform only for Alice, and then break her anonymity later
  1166. %when somebody (presumably Alice) routes through his node?
  1167. A possible solution is a simplified approach to the tit-for-tat
  1168. incentive scheme based on two rules: (1) each node should measure the
  1169. service it receives from adjacent nodes, and provide service relative
  1170. to the received service, but (2) when a node is making decisions that
  1171. affect its own security (e.g. when building a circuit for its own
  1172. application connections), it should choose evenly from a sufficiently
  1173. large set of nodes that meet some minimum service threshold
  1174. \cite{casc-rep}. This approach allows us to discourage bad service
  1175. without opening Alice up as much to attacks. All of this requires
  1176. further study.
  1177. %XXX rewrite the above so it sounds less like a grant proposal and
  1178. %more like a "if somebody were to try to solve this, maybe this is a
  1179. %good first step".
  1180. %We should implement the above incentive scheme in the
  1181. %deployed Tor network, in conjunction with our plans to add the necessary
  1182. %associated scalability mechanisms. We will do experiments (simulated
  1183. %and/or real) to determine how much the incentive system improves
  1184. %efficiency over baseline, and also to determine how far we are from
  1185. %optimal efficiency (what we could get if we ignored the anonymity goals).
  1186. \subsection{Peer-to-peer / practical issues}
  1187. [leave this section for now, and make sure things here are covered
  1188. elsewhere. then remove it.]
  1189. Making use of servers with little bandwidth. How to handle hammering by
  1190. certain applications.
  1191. Handling servers that are far away from the rest of the network, e.g. on
  1192. the continents that aren't North America and Europe. High latency,
  1193. often high packet loss.
  1194. Running Tor servers behind NATs, behind great-firewalls-of-China, etc.
  1195. Restricted routes. How to propagate to everybody the topology? BGP
  1196. style doesn't work because we don't want just *one* path. Point to
  1197. Geoff's stuff.
  1198. \subsection{Location diversity and ISP-class adversaries}
  1199. \label{subsec:routing-zones}
  1200. Anonymity networks have long relied on diversity of node location for
  1201. protection against attacks---typically an adversary who can observe a
  1202. larger fraction of the network can launch a more effective attack. One
  1203. way to achieve dispersal involves growing the network so a given adversary
  1204. sees less. Alternately, we can arrange the topology so traffic can enter
  1205. or exit at many places (for example, by using a free-route network
  1206. like Tor rather than a cascade network like JAP). Lastly, we can use
  1207. distributed trust to spread each transaction over multiple jurisdictions.
  1208. But how do we decide whether two nodes are in related locations?
  1209. Feamster and Dingledine defined a \emph{location diversity} metric
  1210. in \cite{feamster:wpes2004}, and began investigating a variant of location
  1211. diversity based on the fact that the Internet is divided into thousands of
  1212. independently operated networks called {\em autonomous systems} (ASes).
  1213. The key insight from their paper is that while we typically think of a
  1214. connection as going directly from the Tor client to her first Tor node,
  1215. actually it traverses many different ASes on each hop. An adversary at
  1216. any of these ASes can monitor or influence traffic. Specifically, given
  1217. plausible initiators and recipients and path random path selection,
  1218. some ASes in the simulation were able to observe 10\% to 30\% of the
  1219. transactions (that is, learn both the origin and the destination) on
  1220. the deployed Tor network (33 nodes as of June 2004).
  1221. The paper concludes that for best protection against the AS-level
  1222. adversary, nodes should be in ASes that have the most links to other ASes:
  1223. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  1224. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  1225. initiator and responder are both in the U.S., it actually \emph{hurts}
  1226. our location diversity to add far-flung nodes in continents like Asia
  1227. or South America.
  1228. Many open questions remain. First, it will be an immense engineering
  1229. challenge to get an entire BGP routing table to each Tor client, or at
  1230. least summarize it sufficiently. Without a local copy, clients won't be
  1231. able to safely predict what ASes will be traversed on the various paths
  1232. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  1233. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  1234. determine location diversity; but the above paper showed that in practice
  1235. many of the Mixmaster nodes that share a single AS have entirely different
  1236. IP prefixes. When the network has scaled to thousands of nodes, does IP
  1237. prefix comparison become a more useful approximation?
  1238. %
  1239. Second, can take advantage of caching certain content at the exit nodes, to
  1240. limit the number of requests that need to leave the network at all.
  1241. what about taking advantage of caches like akamai's or googles? what
  1242. about treating them as adversaries?
  1243. %
  1244. Third, if we follow the paper's recommendations and tailor path selection
  1245. to avoid choosing endpoints in similar locations, how much are we hurting
  1246. anonymity against larger real-world adversaries who can take advantage
  1247. of knowing our algorithm?
  1248. %
  1249. Lastly, can we use this knowledge to figure out which gaps in our network
  1250. would most improve our robustness to this class of attack, and go recruit
  1251. new servers with those ASes in mind?
  1252. Tor's security relies in large part on the dispersal properties of its
  1253. network. We need to be more aware of the anonymity properties of various
  1254. approaches we can make better design decisions in the future.
  1255. \subsection{The China problem}
  1256. \label{subsec:china}
  1257. Citizens in a variety of countries, such as most recently China and
  1258. Iran, are periodically blocked from accessing various sites outside
  1259. their country. These users try to find any tools available to allow
  1260. them to get-around these firewalls. Some anonymity networks, such as
  1261. Six-Four~\cite{six-four}, are designed specifically with this goal in
  1262. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  1263. such as Voice of America to set up a network to encourage Internet
  1264. freedom. Even though Tor wasn't
  1265. designed with ubiquitous access to the network in mind, thousands of
  1266. users across the world are trying to use it for exactly this purpose.
  1267. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  1268. Anti-censorship networks hoping to bridge country-level blocks face
  1269. a variety of challenges. One of these is that they need to find enough
  1270. exit nodes---servers on the `free' side that are willing to relay
  1271. arbitrary traffic from users to their final destinations. Anonymizing
  1272. networks including Tor are well-suited to this task, since we have
  1273. already gathered a set of exit nodes that are willing to tolerate some
  1274. political heat.
  1275. The other main challenge is to distribute a list of reachable relays
  1276. to the users inside the country, and give them software to use them,
  1277. without letting the authorities also enumerate this list and block each
  1278. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  1279. addresses (or having them donated), abandoning old addresses as they are
  1280. `used up', and telling a few users about the new ones. Distributed
  1281. anonymizing networks again have an advantage here, in that we already
  1282. have tens of thousands of separate IP addresses whose users might
  1283. volunteer to provide this service since they've already installed and use
  1284. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1285. the Tor protocol separates routing from network discovery (see Section
  1286. \ref{do-we-discuss-this?}), volunteers could configure their Tor clients
  1287. to generate server descriptors and send them to a special directory
  1288. server that gives them out to dissidents who need to get around blocks.
  1289. Of course, this still doesn't prevent the adversary
  1290. from enumerating all the volunteer relays and blocking them preemptively.
  1291. Perhaps a tiered-trust system could be built where a few individuals are
  1292. given relays' locations, and they recommend other individuals by telling them
  1293. those addresses, thus providing a built-in incentive to avoid letting the
  1294. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1295. might help to bound the number of IP addresses leaked to the adversary. Groups
  1296. like the W3C are looking into using Tor as a component in an overall system to
  1297. help address censorship; we wish them luck.
  1298. %\cite{infranet}
  1299. \subsection{Non-clique topologies}
  1300. Tor's comparatively weak model makes it easier to scale than other mix net
  1301. designs. High-latency mix networks need to avoid partitioning attacks, where
  1302. network splits prevent users of the separate partitions from providing cover
  1303. for each other. In Tor, however, we assume that the adversary cannot
  1304. cheaply observe nodes at will, so even if the network becomes split, the
  1305. users do not necessarily receive much less protection.
  1306. Thus, a simple possibility when the scale of a Tor network
  1307. exceeds some size is to simply split it. Care could be taken in
  1308. allocating which nodes go to which network along the lines of
  1309. \cite{casc-rep} to insure that collaborating hostile nodes are not
  1310. able to gain any advantage in network splitting that they do not
  1311. already have in joining a network.
  1312. % Describe these attacks; many people will not have read the paper!
  1313. The attacks in \cite{attack-tor-oak05} show that certain types of
  1314. brute force attacks are in fact feasible; however they make the
  1315. above point stronger not weaker. The attacks do not appear to be
  1316. significantly more difficult to mount against a network that is
  1317. twice the size. Also, they only identify the Tor nodes used in a
  1318. circuit, not the client. Finally note that even if the network is split,
  1319. a client does not need to use just one of the two resulting networks.
  1320. Alice could use either of them, and it would not be difficult to make
  1321. the Tor client able to access several such network on a per circuit
  1322. basis. More analysis is needed; we simply note here that splitting
  1323. a Tor network is an easy way to achieve moderate scalability and that
  1324. it does not necessarily have the same implications as splitting a mixnet.
  1325. Alternatively, we can try to scale a single Tor network. Some issues for
  1326. scaling include restricting the number of sockets and the amount of bandwidth
  1327. used by each server. The number of sockets is determined by the network's
  1328. connectivity and the number of users, while bandwidth capacity is determined
  1329. by the total bandwidth of servers on the network. The simplest solution to
  1330. bandwidth capacity is to add more servers, since adding a tor node of any
  1331. feasible bandwidth will increase the traffic capacity of the network. So as
  1332. a first step to scaling, we should focus on making the network tolerate more
  1333. servers, by reducing the interconnectivity of the nodes; later we can reduce
  1334. overhead associated withy directories, discovery, and so on.
  1335. By reducing the connectivity of the network we increase the total number of
  1336. nodes that the network can contain. Danezis~\cite{danezis-pets03} considers
  1337. the anonymity implications of restricting routes on mix networks, and
  1338. recommends an approach based on expander graphs (where any subgraph is likely
  1339. to have many neighbors). It is not immediately clear that this approach will
  1340. extend to Tor, which has a weaker threat model but higher performance
  1341. requirements than the network considered. Instead of analyzing the
  1342. probability of an attacker's viewing whole paths, we will need to examine the
  1343. attacker's likelihood of compromising the endpoints of a Tor circuit through
  1344. a sparse network.
  1345. % Nick edits these next 2 grafs.
  1346. To make matters simpler, Tor may not need an expander graph per se: it
  1347. may be enough to have a single subnet that is highly connected. As an
  1348. example, assume fifty nodes of relatively high traffic capacity. This
  1349. \emph{center} forms are a clique. Assume each center node can each
  1350. handle 200 connections to other nodes (including the other ones in the
  1351. center). Assume every noncenter node connects to three nodes in the
  1352. center and anyone out of the center that they want to. Then the
  1353. network easily scales to c. 2500 nodes with commensurate increase in
  1354. bandwidth. There are many open questions: how directory information
  1355. is distributed (presumably information about the center nodes could
  1356. be given to any new nodes with their codebase), whether center nodes
  1357. will need to function as a `backbone', etc. As above the point is
  1358. that this would create problems for the expected anonymity for a mixnet,
  1359. but for an onion routing network where anonymity derives largely from
  1360. the edges, it may be feasible.
  1361. Another point is that we already have a non-clique topology.
  1362. Individuals can set up and run Tor nodes without informing the
  1363. directory servers. This will allow, e.g., dissident groups to run a
  1364. local Tor network of such nodes that connects to the public Tor
  1365. network. This network is hidden behind the Tor network and its
  1366. only visible connection to Tor at those points where it connects.
  1367. As far as the public network is concerned or anyone observing it,
  1368. they are running clients.
  1369. \section{The Future}
  1370. \label{sec:conclusion}
  1371. we should put random thoughts here until there are enough for a
  1372. conclusion.
  1373. will our sustainability approach work? we'll see.
  1374. Applications that leak data: we can say they're not our problem, but
  1375. they're somebody's problem.
  1376. The more widely deployed Tor becomes, the more people who need a
  1377. deployed overlay network tell us they'd like to use us if only we added
  1378. the following more features.
  1379. "These are difficult and open questions, yet choosing not to solve them
  1380. means leaving most users to a less secure network or no anonymizing
  1381. network at all."
  1382. \bibliographystyle{plain} \bibliography{tor-design}
  1383. \clearpage
  1384. \appendix
  1385. \begin{figure}[t]
  1386. %\unitlength=1in
  1387. \centering
  1388. %\begin{picture}(6.0,2.0)
  1389. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1390. %\end{picture}
  1391. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1392. \caption{Number of servers over time. Lowest line is number of exit
  1393. nodes that allow connections to port 80. Middle line is total number of
  1394. verified (registered) servers. The line above that represents servers
  1395. that are not yet registered.}
  1396. \label{fig:graphnodes}
  1397. \end{figure}
  1398. \begin{figure}[t]
  1399. \centering
  1400. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1401. \caption{The sum of traffic reported by each server over time. The bottom
  1402. pair show average throughput, and the top pair represent the largest 15
  1403. minute burst in each 4 hour period.}
  1404. \label{fig:graphtraffic}
  1405. \end{figure}
  1406. \end{document}