challenges.tex 84 KB

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  1. \documentclass{llncs}
  2. % XXXX NM: Fold ``bandwidth and usability'' into ``Tor and filesharing'' --
  3. % ``bandwidth and file-sharing''.
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  19. \begin{document}
  20. \title{Challenges in deploying low-latency anonymity}
  21. \author{Roger Dingledine\inst{1} \and Nick Mathewson\inst{1} \and Paul Syverson\inst{2}}
  22. \institute{The Free Haven Project \email{<\{arma,nickm\}@freehaven.net>} \and
  23. Naval Research Lab \email{<syverson@itd.nrl.navy.mil>}}
  24. \maketitle
  25. \pagestyle{empty}
  26. \begin{abstract}
  27. There are many unexpected or unexpectedly difficult obstacles to
  28. deploying anonymous communications. Drawing on our experiences deploying
  29. Tor (the second-generation onion routing network), we describe social
  30. challenges and technical issues that must be faced
  31. in building, deploying, and sustaining a scalable, distributed, low-latency
  32. anonymity network.
  33. \end{abstract}
  34. \section{Introduction}
  35. % Your network is not practical unless it is sustainable and distributed.
  36. Anonymous communication is full of surprises. This paper discusses some
  37. unexpected challenges arising from our experiences deploying Tor, a
  38. low-latency general-purpose anonymous communication system. We will discuss
  39. some of the difficulties we have experienced and how we have met them (or how
  40. we plan to meet them, if we know). We will also discuss some less
  41. troublesome open problems that we must nevertheless eventually address.
  42. %We will describe both those future challenges that we intend to explore and
  43. %those that we have decided not to explore and why.
  44. Tor is an overlay network for anonymizing TCP streams over the
  45. Internet~\cite{tor-design}. It addresses limitations in earlier Onion
  46. Routing designs~\cite{or-ih96,or-jsac98,or-discex00,or-pet00} by adding
  47. perfect forward secrecy, congestion control, directory servers, integrity
  48. checking, configurable exit policies, and location-hidden services using
  49. rendezvous points. Tor works on the real-world Internet, requires no special
  50. privileges or kernel modifications, requires little synchronization or
  51. coordination between nodes, and provides a reasonable tradeoff between
  52. anonymity, usability, and efficiency.
  53. We first publicly deployed a Tor network in October 2003; since then it has
  54. grown to over a hundred volunteer Tor nodes
  55. and as much as 80 megabits of
  56. average traffic per second. Tor's research strategy has focused on deploying
  57. a network to as many users as possible; thus, we have resisted designs that
  58. would compromise deployability by imposing high resource demands on node
  59. operators, and designs that would compromise usability by imposing
  60. unacceptable restrictions on which applications we support. Although this
  61. strategy has
  62. its drawbacks (including a weakened threat model, as discussed below), it has
  63. made it possible for Tor to serve many thousands of users and attract
  64. funding from diverse sources whose goals range from security on a
  65. national scale down to the liberties of each individual.
  66. While the Tor design paper~\cite{tor-design} gives an overall view of Tor's
  67. design and goals, this paper describes some policy, social, and technical
  68. issues that we face as we continue deployment.
  69. Rather than trying to provide complete solutions to every problem here, we
  70. lay out the assumptions and constraints that we have observed while
  71. deploying Tor in the wild. In doing so, we aim to create a research agenda
  72. for others to help in addressing these issues. We believe that the issues
  73. described here will be of general interest to projects attempting to build
  74. and deploy practical, useable anonymity networks in the wild.
  75. %While the Tor design paper~\cite{tor-design} gives an overall view its
  76. %design and goals,
  77. %this paper describes the policy and technical issues that Tor faces as
  78. %we continue deployment. Rather than trying to provide complete solutions
  79. %to every problem here, we lay out the assumptions and constraints
  80. %that we have observed through deploying Tor in the wild. In doing so, we
  81. %aim to create a research agenda for others to
  82. %help in addressing these issues.
  83. % Section~\ref{sec:what-is-tor} gives an
  84. %overview of the Tor
  85. %design and ours goals. Sections~\ref{sec:crossroads-policy}
  86. %and~\ref{sec:crossroads-design} go on to describe the practical challenges,
  87. %both policy and technical respectively,
  88. %that stand in the way of moving
  89. %from a practical useful network to a practical useful anonymous network.
  90. %\section{What Is Tor}
  91. \section{Background}
  92. Here we give a basic overview of the Tor design and its properties, and
  93. compare Tor to other low-latency anonymity designs.
  94. \subsection{Tor, threat models, and distributed trust}
  95. \label{sec:what-is-tor}
  96. %Here we give a basic overview of the Tor design and its properties. For
  97. %details on the design, assumptions, and security arguments, we refer
  98. %the reader to the Tor design paper~\cite{tor-design}.
  99. %\medskip
  100. \noindent
  101. {\bf How Tor works.}
  102. Tor provides \emph{forward privacy}, so that users can connect to
  103. Internet sites without revealing their logical or physical locations
  104. to those sites or to observers. It also provides \emph{location-hidden
  105. services}, so that critical servers can support authorized users without
  106. giving adversaries an effective vector for physical or online attacks.
  107. The design provides these protections even when a portion of its own
  108. infrastructure is controlled by an adversary.
  109. To create a private network pathway with Tor, the client software
  110. incrementally builds a \emph{circuit} of encrypted connections through
  111. Tor nodes on the network. The circuit is extended one hop at a time, and
  112. each node along the way knows only which node gave it data and which
  113. node it is giving data to. No individual Tor node ever knows the complete
  114. path that a data packet has taken. The client negotiates a separate set
  115. of encryption keys for each hop along the circuit.% to ensure that each
  116. %hop can't trace these connections as they pass through.
  117. Because each node sees no more than one hop in the
  118. circuit, neither an eavesdropper nor a compromised node can use traffic
  119. analysis to link the connection's source and destination.
  120. For efficiency, the Tor software uses the same circuit for all the TCP
  121. connections that happen within the same short period.
  122. Later requests use a new
  123. circuit, to prevent long-term linkability between different actions by
  124. a single user.
  125. Tor also makes it possible for users to hide their locations while
  126. offering various kinds of services, such as web publishing or an instant
  127. messaging server. Using ``rendezvous points'', other Tor users can
  128. connect to these hidden services, each without knowing the other's network
  129. identity.
  130. Tor attempts to anonymize the transport layer, not the application layer, so
  131. application protocols that include personally identifying information need
  132. additional application-level scrubbing proxies, such as
  133. Privoxy~\cite{privoxy} for HTTP. Furthermore, Tor does not permit arbitrary
  134. IP packets; it only anonymizes TCP streams and DNS request, and only supports
  135. connections via SOCKS (see Section~\ref{subsec:tcp-vs-ip}).
  136. Most node operators do not want to allow arbitary TCP connections to leave
  137. their server. To address this, Tor provides \emph{exit policies} so that
  138. each exit node can block the IP addresses and ports it is unwilling to allow.
  139. TRs advertise their exit policies to the directory servers, so that
  140. client can tell which nodes will support their connections.
  141. As of January 2005, the Tor network has grown to around a hundred nodes
  142. on four continents, with a total capacity exceeding 1Gbit/s. Appendix A
  143. shows a graph of the number of working nodes over time, as well as a
  144. vgraph of the number of bytes being handled by the network over time. At
  145. this point the network is sufficiently diverse for further development
  146. and testing; but of course we always encourage and welcome new nodes
  147. to join the network.
  148. Tor research and development has been funded by the U.S.~Navy and DARPA
  149. for use in securing government
  150. communications, and by the Electronic Frontier Foundation, for use
  151. in maintaining civil liberties for ordinary citizens online. The Tor
  152. protocol is one of the leading choices
  153. to be the anonymizing layer in the European Union's PRIME directive to
  154. help maintain privacy in Europe. The University of Dresden in Germany
  155. has integrated an independent implementation of the Tor protocol into
  156. their popular Java Anon Proxy anonymizing client.
  157. % This wide variety of
  158. %interests helps maintain both the stability and the security of the
  159. %network.
  160. \medskip
  161. \noindent
  162. {\bf Threat models and design philosophy.}
  163. The ideal Tor network would be practical, useful and and anonymous. When
  164. trade-offs arise between these properties, Tor's research strategy has been
  165. to insist on remaining useful enough to attract many users,
  166. and practical enough to support them. Only subject to these
  167. constraints do we aim to maximize
  168. anonymity.\footnote{This is not the only possible
  169. direction in anonymity research: designs exist that provide more anonymity
  170. than Tor at the expense of significantly increased resource requirements, or
  171. decreased flexibility in application support (typically because of increased
  172. latency). Such research does not typically abandon aspirations towards
  173. deployability or utility, but instead tries to maximize deployability and
  174. utility subject to a certain degree of inherent anonymity (inherent because
  175. usability and practicality affect usage which affects the actual anonymity
  176. provided by the network \cite{back01,econymics}).}
  177. %{We believe that these
  178. %approaches can be promising and useful, but that by focusing on deploying a
  179. %usable system in the wild, Tor helps us experiment with the actual parameters
  180. %of what makes a system ``practical'' for volunteer operators and ``useful''
  181. %for home users, and helps illuminate undernoticed issues which any deployed
  182. %volunteer anonymity network will need to address.}
  183. Because of this strategy, Tor has a weaker threat model than many anonymity
  184. designs in the literature. In particular, because we
  185. support interactive communications without impractically expensive padding,
  186. we fall prey to a variety
  187. of intra-network~\cite{back01,attack-tor-oak05,flow-correlation04} and
  188. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  189. Tor does not attempt to defend against a global observer. In general, an
  190. attacker who can observe both ends of a connection through the Tor network
  191. can correlate the timing and volume of data on that connection as it enters
  192. and leaves the network, and so link a user to her chosen communication
  193. parties. Known solutions to this attack would seem to require introducing a
  194. prohibitive degree of traffic padding between the user and the network, or
  195. introducing an unacceptable degree of latency (but see Section
  196. \ref{subsec:mid-latency}). Also, it is not clear that these methods would
  197. work at all against even a minimally active adversary that can introduce timing
  198. patterns or additional traffic. Thus, Tor only attempts to defend against
  199. external observers who cannot observe both sides of a user's connection.
  200. The distinction between traffic correlation and traffic analysis is
  201. not as cut and dried as we might wish. In \cite{hintz-pet02} it was
  202. shown that if data volumes of various popular
  203. responder destinations are catalogued, it may not be necessary to
  204. observe both ends of a stream to learn a source-destination link.
  205. This should be fairly effective without simultaneously observing both
  206. ends of the connection. However, it is still essentially confirming
  207. suspected communicants where the responder suspects are ``stored'' rather
  208. than observed at the same time as the client.
  209. Similarly latencies of going through various routes can be
  210. catalogued~\cite{back01} to connect endpoints.
  211. This is likely to entail high variability and massive storage since
  212. % XXX hintz-pet02 just looked at data volumes of the sites. this
  213. % doesn't require much variability or storage. I think it works
  214. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  215. % attack another level further, to narrow down where you could be
  216. % based on an intersection attack on subpages in a website. -RD
  217. %
  218. % I was trying to be terse and simultaneously referring to both the
  219. % Hintz stuff and the Back et al. stuff from Info Hiding 01. I've
  220. % separated the two and added the references. -PFS
  221. routes through the network to each site will be random even if they
  222. have relatively unique latency characteristics. So this does not seem
  223. an immediate practical threat. Further along similar lines, the same
  224. paper suggested a ``clogging attack''. In \cite{attack-tor-oak05}, a
  225. version of this was demonstrated to be practical against portions of
  226. the fifty node Tor network as deployed in mid 2004. There it was shown
  227. that an outside attacker can trace a stream through the Tor network
  228. while a stream is still active simply by observing the latency of his
  229. own traffic sent through various Tor nodes. These attacks do not show
  230. the client address, only the first node within the Tor network, making
  231. helper nodes all the more worthy of exploration (cf.,
  232. Section~{subsec:helper-nodes}).
  233. Against internal attackers who sign up Tor nodes, the situation is more
  234. complicated. In the simplest case, if an adversary has compromised $c$ of
  235. $n$ nodes on the Tor network, then the adversary will be able to compromise
  236. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  237. initiator chooses hops randomly). But there are
  238. complicating factors:
  239. (1)~If the user continues to build random circuits over time, an adversary
  240. is pretty certain to see a statistical sample of the user's traffic, and
  241. thereby can build an increasingly accurate profile of her behavior. (See
  242. \ref{subsec:helper-nodes} for possible solutions.)
  243. (2)~An adversary who controls a popular service outside of the Tor network
  244. can be certain of observing all connections to that service; he
  245. therefore will trace connections to that service with probability
  246. $\frac{c}{n}$.
  247. (3)~Users do not in fact choose nodes with uniform probability; they
  248. favor nodes with high bandwidth or uptime, and exit nodes that
  249. permit connections to their favorite services.
  250. See Section~\ref{subsec:routing-zones} for discussion of larger
  251. adversaries and our dispersal goals.
  252. %\begin{tightlist}
  253. %\item If the user continues to build random circuits over time, an adversary
  254. % is pretty certain to see a statistical sample of the user's traffic, and
  255. % thereby can build an increasingly accurate profile of her behavior. (See
  256. % \ref{subsec:helper-nodes} for possible solutions.)
  257. %\item An adversary who controls a popular service outside of the Tor network
  258. % can be certain of observing all connections to that service; he
  259. % therefore will trace connections to that service with probability
  260. % $\frac{c}{n}$.
  261. %\item Users do not in fact choose nodes with uniform probability; they
  262. % favor nodes with high bandwidth or uptime, and exit nodes that
  263. % permit connections to their favorite services.
  264. %\end{tightlist}
  265. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  266. %the last hop is not $c/n$ since that doesn't take the destination (website)
  267. %into account. so in cases where the adversary does not also control the
  268. %final destination we're in good shape, but if he *does* then we'd be better
  269. %off with a system that lets each hop choose a path.
  270. %
  271. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  272. % dest, we would be just as well off with such as system.'' ? If not, why
  273. % not? -nm
  274. % Sure. In fact, better off, since they seem to scale more easily. -rd
  275. % XXXX the below paragraph should probably move later, and merge with
  276. % other discussions of attack-tor-oak5.
  277. %Murdoch and Danezis describe an attack
  278. %\cite{attack-tor-oak05} that lets an attacker determine the nodes used
  279. %in a circuit; yet s/he cannot identify the initiator or responder,
  280. %e.g., client or web server, through this attack. So the endpoints
  281. %remain secure, which is the goal. It is conceivable that an
  282. %adversary could attack or set up observation of all connections
  283. %to an arbitrary Tor node in only a few minutes. If such an adversary
  284. %were to exist, s/he could use this probing to remotely identify a node
  285. %for further attack. Of more likely immediate practical concern
  286. %an adversary with active access to the responder traffic
  287. %wants to keep a circuit alive long enough to attack an identified
  288. %node. Thus it is important to prevent the responding end of the circuit
  289. %from keeping it open indefinitely.
  290. %Also, someone could identify nodes in this way and if in their
  291. %jurisdiction, immediately get a subpoena (if they even need one)
  292. %telling the node operator(s) that she must retain all the active
  293. %circuit data she now has.
  294. %Further, the enclave model, which had previously looked to be the most
  295. %generally secure, seems particularly threatened by this attack, since
  296. %it identifies endpoints when they're also nodes in the Tor network:
  297. %see Section~\ref{subsec:helper-nodes} for discussion of some ways to
  298. %address this issue.
  299. \medskip
  300. \noindent
  301. {\bf Distributed trust.}
  302. In practice Tor's threat model is based entirely on the goal of
  303. dispersal and diversity.
  304. Tor's defense lies in having a diverse enough set of nodes
  305. to prevent most real-world
  306. adversaries from being in the right places to attack users.
  307. Tor aims to resist observers and insiders by distributing each transaction
  308. over several nodes in the network. This ``distributed trust'' approach
  309. means the Tor network can be safely operated and used by a wide variety
  310. of mutually distrustful users, providing more sustainability and security
  311. than some previous attempts at anonymizing networks.
  312. The Tor network has a broad range of users, including ordinary citizens
  313. concerned about their privacy, corporations
  314. who don't want to reveal information to their competitors, and law
  315. enforcement and government intelligence agencies who need
  316. to do operations on the Internet without being noticed.
  317. No organization can achieve this security on its own. If a single
  318. corporation or government agency were to build a private network to
  319. protect its operations, any connections entering or leaving that network
  320. would be obviously linkable to the controlling organization. The members
  321. and operations of that agency would be easier, not harder, to distinguish.
  322. Instead, to protect our networks from traffic analysis, we must
  323. collaboratively blend the traffic from many organizations and private
  324. citizens, so that an eavesdropper can't tell which users are which,
  325. and who is looking for what information. By bringing more users onto
  326. the network, all users become more secure~\cite{econymics}.
  327. [XXX I feel uncomfortable saying this last sentence now. -RD]
  328. Naturally, organizations will not want to depend on others for their
  329. security. If most participating providers are reliable, Tor tolerates
  330. some hostile infiltration of the network. For maximum protection,
  331. the Tor design includes an enclave approach that lets data be encrypted
  332. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  333. hasn't been read or modified. This even works for Internet services that
  334. don't have built-in encryption and authentication, such as unencrypted
  335. HTTP or chat, and it requires no modification of those services.
  336. \subsection{Related work}
  337. Tor is not the only anonymity system that aims to be practical and useful.
  338. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  339. open proxies around the Internet, can provide good
  340. performance and some security against a weaker attacker. The Java
  341. Anon Proxy~\cite{web-mix} provides similar functionality to Tor but only
  342. handles web browsing rather than arbitrary TCP\@.
  343. %Some peer-to-peer file-sharing overlay networks such as
  344. %Freenet~\cite{freenet} and Mute~\cite{mute}
  345. Zero-Knowledge Systems' commercial Freedom
  346. network~\cite{freedom21-security} was even more flexible than Tor in
  347. that it could transport arbitrary IP packets, and it also supported
  348. pseudonymous access rather than just anonymous access; but it had
  349. a different approach to sustainability (collecting money from users
  350. and paying ISPs to run Tor nodes), and was shut down due to financial
  351. load. Finally, potentially
  352. more scalable designs like Tarzan~\cite{tarzan:ccs02} and
  353. MorphMix~\cite{morphmix:fc04} have been proposed in the literature, but
  354. have not yet been fielded. All of these systems differ somewhat
  355. in threat model and presumably practical resistance to threats.
  356. Morphmix is very close to Tor in circuit setup. And, by separating
  357. node discovery from route selection from circuit setup, Tor is
  358. flexible enough to potentially contain a Morphmix experiment within
  359. it. We direct the interested reader to Section
  360. 2 of~\cite{tor-design} for a more in-depth review of related work.
  361. Tor differs from other deployed systems for traffic analysis resistance
  362. in its security and flexibility. Mix networks such as
  363. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  364. gain the highest degrees of anonymity at the expense of introducing highly
  365. variable delays, thus making them unsuitable for applications such as web
  366. browsing. Commercial single-hop
  367. proxies~\cite{anonymizer} present a single point of failure, where
  368. a single compromise can expose all users' traffic, and a single-point
  369. eavesdropper can perform traffic analysis on the entire network.
  370. Also, their proprietary implementations place any infrastucture that
  371. depends on these single-hop solutions at the mercy of their providers'
  372. financial health as well as network security.
  373. %XXXX six-four. crowds. i2p.
  374. %XXXX
  375. %have a serious discussion of morphmix's assumptions, since they would
  376. %seem to be the direct competition. in fact tor is a flexible architecture
  377. %that would encompass morphmix, and they're nearly identical except for
  378. %path selection and node discovery. and the trust system morphmix has
  379. %seems overkill (and/or insecure) based on the threat model we've picked.
  380. % this para should probably move to the scalability / directory system. -RD
  381. % Nope. Cut for space, except for small comment added above -PFS
  382. \section{Crossroads: Policy issues}
  383. \label{sec:crossroads-policy}
  384. Many of the issues the Tor project needs to address extend beyond
  385. system design and technology development. In particular, the
  386. Tor project's \emph{image} with respect to its users and the rest of
  387. the Internet impacts the security it can provide.
  388. % No image, no sustainability -NM
  389. With this image issue in mind, this section discusses the Tor user base and
  390. Tor's interaction with other services on the Internet.
  391. \subsection{Communicating security}
  392. A growing field of papers argue that usability for anonymity systems
  393. contributes directly to their security, because how usable the system
  394. is impacts the possible anonymity set~\cite{back01,econymics}. Or
  395. conversely, an unusable system attracts few users and thus can't provide
  396. much anonymity.
  397. This phenomenon has a second-order effect: knowing this, users should
  398. choose which anonymity system to use based in part on how usable
  399. \emph{others} will find it, in order to get the protection of a larger
  400. anonymity set. Thus we might replace the adage ``usability is a security
  401. parameter''~\cite{back01} with a new one: ``perceived usability is a
  402. security parameter.'' From here we can better understand the effects
  403. of publicity and advertising on security: the more convincing your
  404. advertising, the more likely people will believe you have users, and thus
  405. the more users you will attract. Perversely, over-hyped systems (if they
  406. are not too broken) may be a better choice than modestly promoted ones,
  407. if the hype attracts more users~\cite{usability-network-effect}.
  408. So it follows that we should come up with ways to accurately communicate
  409. the available security levels to the user, so she can make informed
  410. decisions. JAP aims to do this by including a
  411. comforting `anonymity meter' dial in the software's graphical interface,
  412. giving the user an impression of the level of protection for her current
  413. traffic.
  414. However, there's a catch. For users to share the same anonymity set,
  415. they need to act like each other. An attacker who can distinguish
  416. a given user's traffic from the rest of the traffic will not be
  417. distracted by anonymity set size. For high-latency systems like
  418. Mixminion, where the threat model is based on mixing messages with each
  419. other, there's an arms race between end-to-end statistical attacks and
  420. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  421. But for low-latency systems like Tor, end-to-end \emph{traffic
  422. correlation} attacks~\cite{danezis-pet2004,SS03,defensive-dropping}
  423. allow an attacker who can measure both ends of a communication
  424. to match packet timing and volume, quickly linking
  425. the initiator to her destination. This is why Tor's threat model is
  426. based on preventing the adversary from observing both the initiator and
  427. the responder.
  428. Like Tor, the current JAP implementation does not pad connections
  429. (apart from using small fixed-size cells for transport). In fact,
  430. JAP's cascade-based network topology may be even more vulnerable to these
  431. attacks, because the network has fewer edges. JAP was born out of
  432. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  433. every user had a fixed bandwidth allocation, but in its current context
  434. as a general Internet web anonymizer, adding sufficient padding to JAP
  435. would be prohibitively expensive.\footnote{Even if they could fund
  436. (indefinitely) higher-capacity nodes, our experience
  437. suggests that many users would not accept the increased per-user
  438. bandwidth requirements, leading to an overall much smaller user base. But
  439. cf.\ Section \ref{subsec:mid-latency}.} Therefore, since under this threat
  440. model the number of concurrent users does not seem to have much impact
  441. on the anonymity provided, we suggest that JAP's anonymity meter is not
  442. correctly communicating security levels to its users.
  443. % because more users don't help anonymity much, we need to rely more
  444. % on other incentive schemes, both policy-based (see sec x) and
  445. % technically enforced (see sec y)
  446. On the other hand, while the number of active concurrent users may not
  447. matter as much as we'd like, it still helps to have some other users
  448. who use the network. We investigate this issue in the next section.
  449. \subsection{Reputability and perceived social value}
  450. Another factor impacting the network's security is its reputability:
  451. the perception of its social value based on its current user base. If Alice is
  452. the only user who has ever downloaded the software, it might be socially
  453. accepted, but she's not getting much anonymity. Add a thousand animal rights
  454. activists, and she's anonymous, but everyone thinks she's a Bambi lover (or
  455. NRA member if you prefer a contrasting example). Add a thousand
  456. diverse citizens (cancer survivors, privacy enthusiasts, and so on)
  457. and now she's harder to profile.
  458. Furthermore, the network's reputability affects its node base: more people
  459. are willing to run a service if they believe it will be used by human rights
  460. workers than if they believe it will be used exclusively for disreputable
  461. ends. This effect becomes stronger if node operators themselves think they
  462. will be associated with these disreputable ends.
  463. So the more cancer survivors on Tor, the better for the human rights
  464. activists. The more malicious hackers, the worse for the normal users. Thus,
  465. reputability is an anonymity issue for two reasons. First, it impacts
  466. the sustainability of the network: a network that's always about to be
  467. shut down has difficulty attracting and keeping adquate nodes.
  468. Second, a disreputable network is more vulnerable to legal and
  469. political attacks, since it will attract fewer supporters.
  470. While people therefore have an incentive for the network to be used for
  471. ``more reputable'' activities than their own, there are still tradeoffs
  472. involved when it comes to anonymity. To follow the above example, a
  473. network used entirely by cancer survivors might welcome some NRA members
  474. onto the network, though of course they'd prefer a wider
  475. variety of users.
  476. Reputability becomes even more tricky in the case of privacy networks,
  477. since the good uses of the network (such as publishing by journalists in
  478. dangerous countries) are typically kept private, whereas network abuses
  479. or other problems tend to be more widely publicized.
  480. The impact of public perception on security is especially important
  481. during the bootstrapping phase of the network, where the first few
  482. widely publicized uses of the network can dictate the types of users it
  483. attracts next.
  484. As an example, some some U.S.~Department of Energy
  485. penetration testing engineers are tasked with compromising DoE computers
  486. from the outside. They only have a limited number of ISPs from which to
  487. launch their attacks, and they found that the defenders were recognizing
  488. attacks because they came from the same IP space. These engineers wanted
  489. to use Tor to hide their tracks. First, from a technical standpoint,
  490. Tor does not support the variety of IP packets one would like to use in
  491. such attacks (see Section~\ref{subsec:tcp-vs-ip}). But aside from this,
  492. we also decided that it would probably be poor precedent to encourage
  493. such use---even legal use that improves national security---and managed
  494. to dissuade them.
  495. %% "outside of academia, jap has just lost, permanently". (That is,
  496. %% even though the crime detection issues are resolved and are unlikely
  497. %% to go down the same way again, public perception has not been kind.)
  498. \subsection{Sustainability and incentives}
  499. One of the unsolved problems in low-latency anonymity designs is
  500. how to keep the nodes running. Zero-Knowledge Systems's Freedom network
  501. depended on paying third parties to run its servers; the JAP project's
  502. bandwidth depends on grants to pay for its bandwidth and
  503. administrative expenses. In Tor, bandwidth and administrative costs are
  504. distributed across the volunteers who run Tor nodes, so we at least have
  505. reason to think that the Tor network could survive without continued research
  506. funding.\footnote{It also helps that Tor is implemented with free and open
  507. source software that can be maintained by anybody with the ability and
  508. inclination.} But why are these volunteers running nodes, and what can we
  509. do to encourage more volunteers to do so?
  510. We have not formally surveyed Tor node operators to learn why they are
  511. running nodes, but
  512. from the information they have provided, it seems that many of them run Tor
  513. nodes for reasons of personal interest in privacy issues. It is possible
  514. that others are running Tor for their own
  515. anonymity reasons, but of course they are
  516. hardly likely to tell us specifics if they are.
  517. %Significantly, Tor's threat model changes the anonymity incentives for running
  518. %a node. In a high-latency mix network, users can receive additional
  519. %anonymity by running their own node, since doing so obscures when they are
  520. %injecting messages into the network. But, anybody observing all I/O to a Tor
  521. %node can tell when the node is generating traffic that corresponds to
  522. %none of its incoming traffic.
  523. %
  524. %I didn't buy the above for reason's subtle enough that I just cut it -PFS
  525. Tor exit node operators do attain a degree of
  526. ``deniability'' for traffic that originates at that exit node. For
  527. example, it is likely in practice that HTTP requests from a Tor node's IP
  528. will be assumed to be from the Tor network.
  529. More significantly, people and organizations who use Tor for
  530. anonymity depend on the
  531. continued existence of the Tor network to do so; running a node helps to
  532. keep the network operational.
  533. %\item Local Tor entry and exit nodes allow users on a network to run in an
  534. % `enclave' configuration. [XXXX need to resolve this. They would do this
  535. % for E2E encryption + auth?]
  536. %We must try to make the costs of running a Tor node easily minimized.
  537. Since Tor is run by volunteers, the most crucial software usability issue is
  538. usability by operators: when an operator leaves, the network becomes less
  539. usable by everybody. To keep operators pleased, we must try to keep Tor's
  540. resource and administrative demands as low as possible.
  541. Because of ISP billing structures, many Tor operators have underused capacity
  542. that they are willing to donate to the network, at no additional monetary
  543. cost to them. Features to limit bandwidth have been essential to adoption.
  544. Also useful has been a ``hibernation'' feature that allows a Tor node that
  545. wants to provide high bandwidth, but no more than a certain amount in a
  546. giving billing cycle, to become dormant once its bandwidth is exhausted, and
  547. to reawaken at a random offset into the next billing cycle. This feature has
  548. interesting policy implications, however; see
  549. Section~\ref{subsec:bandwidth-and-filesharing} below.
  550. Exit policies help to limit administrative costs by limiting the frequency of
  551. abuse complaints.
  552. %[XXXX say more. Why else would you run a node? What else can we do/do we
  553. % already do to make running a node more attractive?]
  554. %[We can enforce incentives; see Section 6.1. We can rate-limit clients.
  555. % We can put "top bandwidth nodes lists" up a la seti@home.]
  556. \subsection{Bandwidth and filesharing}
  557. \label{subsec:bandwidth-and-filesharing}
  558. %One potentially problematical area with deploying Tor has been our response
  559. %to file-sharing applications.
  560. Once users have configured their applications to work with Tor, the largest
  561. remaining usability issue is performance. Users begin to suffer
  562. when websites ``feel slow''.
  563. Clients currently try to build their connections through nodes that they
  564. guess will have enough bandwidth. But even if capacity is allocated
  565. optimally, it seems unlikely that the current network architecture will have
  566. enough capacity to provide every user with as much bandwidth as she would
  567. receive if she weren't using Tor, unless far more nodes join the network
  568. (see above).
  569. %Limited capacity does not destroy the network, however. Instead, usage tends
  570. %towards an equilibrium: when performance suffers, users who value performance
  571. %over anonymity tend to leave the system, thus freeing capacity until the
  572. %remaining users on the network are exactly those willing to use that capacity
  573. %there is.
  574. Much of Tor's recent bandwidth difficulties have come from file-sharing
  575. applications. These applications provide two challenges to
  576. any anonymizing network: their intensive bandwidth requirement, and the
  577. degree to which they are associated (correctly or not) with copyright
  578. violation.
  579. As noted above, high-bandwidth protocols can make the network unresponsive,
  580. but tend to be somewhat self-correcting. Issues of copyright violation,
  581. however, are more interesting. Typical exit node operators want to help
  582. people achieve private and anonymous speech, not to help people (say) host
  583. Vin Diesel movies for download; and typical ISPs would rather not
  584. deal with customers who incur them the overhead of getting menacing letters
  585. from the MPAA\@. While it is quite likely that the operators are doing nothing
  586. illegal, many ISPs have policies of dropping users who get repeated legal
  587. threats regardless of the merits of those threats, and many operators would
  588. prefer to avoid receiving legal threats even if those threats have little
  589. merit. So when the letters arrive, operators are likely to face
  590. pressure to block filesharing applications entirely, in order to avoid the
  591. hassle.
  592. But blocking filesharing would not necessarily be easy; most popular
  593. protocols have evolved to run on a variety of non-standard ports in order to
  594. get around other port-based bans. Thus, exit node operators who wanted to
  595. block filesharing would have to find some way to integrate Tor with a
  596. protocol-aware exit filter. This could be a technically expensive
  597. undertaking, and one with poor prospects: it is unlikely that Tor exit nodes
  598. would succeed where so many institutional firewalls have failed. Another
  599. possibility for sensitive operators is to run a restrictive node that
  600. only permits exit connections to a restricted range of ports which are
  601. not frequently associated with file sharing. There are increasingly few such
  602. ports.
  603. Other possible approaches might include rate-limiting connections, especially
  604. long-lived connections or connections to file-sharing ports, so that
  605. high-bandwidth connections do not flood the network. We might also want to
  606. give priority to cells on low-bandwidth connections to keep them interactive,
  607. but this could have negative anonymity implications.
  608. For the moment, it seems that Tor's bandwidth issues have rendered it
  609. unattractive for bulk file-sharing traffic; this may continue to be so in the
  610. future. Nevertheless, Tor will likely remain attractive for limited use in
  611. filesharing protocols that have separate control and data channels.
  612. %[We should say more -- but what? That we'll see a similar
  613. % equilibriating effect as with bandwidth, where sensitive ops switch to
  614. % middleman, and we become less useful for filesharing, so the filesharing
  615. % people back off, so we get more ops since there's less filesharing, so the
  616. % filesharers come back, etc.]
  617. %XXXX
  618. %in practice, plausible deniability is hypothetical and doesn't seem very
  619. %convincing. if ISPs find the activity antisocial, they don't care *why*
  620. %your computer is doing that behavior.
  621. \subsection{Tor and blacklists}
  622. It was long expected that, alongside Tor's legitimate users, it would also
  623. attract troublemakers who exploited Tor in order to abuse services on the
  624. Internet with vandalism, rude mail, and so on.
  625. %[XXX we're not talking bandwidth abuse here, we're talking vandalism,
  626. %hate mails via hotmail, attacks, etc.]
  627. Our initial answer to this situation was to use ``exit policies''
  628. to allow individual Tor nodes to block access to specific IP/port ranges.
  629. This approach was meant to make operators more willing to run Tor by allowing
  630. them to prevent their nodes from being used for abusing particular
  631. services. For example, all Tor nodes currently block SMTP (port 25), in
  632. order to avoid being used to send spam.
  633. This approach is useful, but is insufficient for two reasons. First, since
  634. it is not possible to force all nodes to block access to any given service,
  635. many of those services try to block Tor instead. More broadly, while being
  636. blockable is important to being good netizens, we would like to encourage
  637. services to allow anonymous access; services should not need to decide
  638. between blocking legitimate anonymous use and allowing unlimited abuse.
  639. This is potentially a bigger problem than it may appear.
  640. On the one hand, if people want to refuse connections from your address to
  641. their servers it would seem that they should be allowed. But, it's not just
  642. for himself that the individual node administrator is deciding when he decides
  643. if he wants to post to Wikipedia from his Tor node address or allow
  644. people to read Wikipedia anonymously through his Tor node. (Wikipedia
  645. has blocked all posting from all Tor nodes based on IP address.) If e.g.,
  646. s/he comes through a campus or corporate NAT, then the decision must
  647. be to have the entire population behind it able to have a Tor exit
  648. node or to have write access to Wikipedia. This is a loss for both Tor
  649. and Wikipedia. We don't want to compete for (or divvy up) the NAT
  650. protected entities of the world.
  651. Worse, many IP blacklists are not terribly fine-grained.
  652. No current IP blacklist, for example, allow a service provider to blacklist
  653. only those Tor nodes that allow access to a specific IP or port, even
  654. though this information is readily available. One IP blacklist even bans
  655. every class C network that contains a Tor node, and recommends banning SMTP
  656. from these networks even though Tor does not allow SMTP at all. This
  657. coarse-grained approach is typically a strategic decision to discourage the
  658. operation of anything resembling an open proxy by encouraging its neighbors
  659. to shut it down in order to get unblocked themselves.
  660. %[****Since this is stupid and we oppose it, shouldn't we name names here -pfs]
  661. %[XXX also, they're making \emph{middleman nodes leave} because they're caught
  662. % up in the standoff!]
  663. %[XXX Mention: it's not dumb, it's strategic!]
  664. %[XXX Mention: for some servops, any blacklist is a blacklist too many,
  665. % because it is risky. (Guy lives in apt _building_ with one IP.)]
  666. Problems of abuse occur mainly with services such as IRC networks and
  667. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  668. blush this practice might seem to depend on the anachronistic assumption that
  669. each IP is an identifier for a single user, it is actually more reasonable in
  670. practice: it assumes that non-proxy IPs are a costly resource, and that an
  671. abuser can not change IPs at will. By blocking IPs which are used by Tor
  672. nodes, open proxies, and service abusers, these systems hope to make
  673. ongoing abuse difficult. Although the system is imperfect, it works
  674. tolerably well for them in practice.
  675. But of course, we would prefer that legitimate anonymous users be able to
  676. access abuse-prone services. One conceivable approach would be to require
  677. would-be IRC users, for instance, to register accounts if they wanted to
  678. access the IRC network from Tor. But in practise, this would not
  679. significantly impede abuse if creating new accounts were easily automatable;
  680. this is why services use IP blocking. In order to deter abuse, pseudonymous
  681. identities need to require a significant switching cost in resources or human
  682. time.
  683. % XXX Mention captchas?
  684. %One approach, similar to that taken by Freedom, would be to bootstrap some
  685. %non-anonymous costly identification mechanism to allow access to a
  686. %blind-signature pseudonym protocol. This would effectively create costly
  687. %pseudonyms, which services could require in order to allow anonymous access.
  688. %This approach has difficulties in practise, however:
  689. %\begin{tightlist}
  690. %\item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  691. % be a shame to require payment in order to make Tor useful, or to make
  692. % non-paying users second-class citizens.
  693. %\item It is hard to think of an underlying resource that would actually work.
  694. % We could use IP addresses, but that's the problem, isn't it?
  695. %\item Managing single sign-on services is not considered a well-solved
  696. % problem in practice. If Microsoft can't get universal acceptance for
  697. % Passport, why do we think that a Tor-specific solution would do any good?
  698. %\item Even if we came up with a perfect authentication system for our needs,
  699. % there's no guarantee that any service would actually start using it. It
  700. % would require a nonzero effort for them to support it, and it might just
  701. % be less hassle for them to block tor anyway.
  702. %\end{tightlist}
  703. %The use of squishy IP-based ``authentication'' and ``authorization''
  704. %has not broken down even to the level that SSNs used for these
  705. %purposes have in commercial and public record contexts. Externalities
  706. %and misplaced incentives cause a continued focus on fighting identity
  707. %theft by protecting SSNs rather than developing better authentication
  708. %and incentive schemes \cite{price-privacy}. Similarly we can expect a
  709. %continued use of identification by IP number as long as there is no
  710. %workable alternative.
  711. %Fortunately, our modular design separates
  712. %routing from node discovery; so we could implement Morphmix in Tor just
  713. %by implementing the Morphmix-specific node discovery and path selection
  714. %pieces.
  715. %[XXX Mention correct DNS-RBL implementation. -NM]
  716. \section{Crossroads: Design choices}
  717. \label{sec:crossroads-design}
  718. In addition to social issues, Tor also faces some design challenges that must
  719. be addressed as the network develops.
  720. \subsection{Transporting the stream vs transporting the packets}
  721. \label{subsec:stream-vs-packet}
  722. \label{subsec:tcp-vs-ip}
  723. Tor transports streams; it does not tunnel packets.
  724. Developers of the old Freedom network~\cite{freedom21-security}
  725. keep telling us that IP addresses should ``obviously'' be anonymized
  726. at the IP layer. These issues need to be resolved before
  727. Tor will be ready to carry arbitrary IP traffic:
  728. \begin{enumerate}
  729. \setlength{\itemsep}{0mm}
  730. \setlength{\parsep}{0mm}
  731. \item \emph{IP packets reveal OS characteristics.} We still need to do
  732. IP-level packet normalization, to stop things like IP fingerprinting
  733. attacks. There likely exist libraries that can help with this.
  734. \item \emph{Application-level streams still need scrubbing.} We still need
  735. Tor to be easy to integrate with user-level application-specific proxies
  736. such as Privoxy. So it's not just a matter of capturing packets and
  737. anonymizing them at the IP layer.
  738. \item \emph{Certain protocols will still leak information.} For example,
  739. we must rewrite DNS requests destined for local DNS servers to
  740. be delivered to some unlinkable DNS server. This requires
  741. understanding the protocols we are transporting.
  742. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  743. approach that can provide security despite
  744. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  745. never publicly specified.
  746. Also, TLS over UDP is not implemented or even
  747. specified, though some early work has begun on that~\cite{dtls}.
  748. \item \emph{We'll still need to tune network parameters}. Since the above
  749. encryption system will likely need sequence numbers (and maybe more) to do
  750. replay detection, handle duplicate frames, etc., we will be reimplementing
  751. a subset of TCP anyway.
  752. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  753. IDS\@.} Our node operators tell us that exit policies are one of
  754. the main reasons they're willing to run Tor.
  755. Adding an Intrusion Detection System to handle exit policies would
  756. increase the security complexity of Tor, and would likely not work anyway,
  757. as evidenced by the entire field of IDS and counter-IDS papers. Many
  758. potential abuse issues are resolved by the fact that Tor only transports
  759. valid TCP streams (as opposed to arbitrary IP including malformed packets
  760. and IP floods), so exit policies become even \emph{more} important as
  761. we become able to transport IP packets. We also need to compactly
  762. describe exit policies so clients can predict
  763. which nodes will allow which packets to exit.
  764. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  765. support hidden service {\tt{.onion}} addresses, and other special addresses
  766. like {\tt{.exit}} for the user to request a particular exit node,
  767. by intercepting the addresses when they are passed to the Tor client.
  768. \end{enumerate}
  769. This list is discouragingly long, but being able to transport more
  770. protocols obviously has some advantages. It would be good to learn which
  771. items are actual roadblocks and which are easier to resolve than we think.
  772. To be fair, Tor's stream-based approach has run into
  773. stumbling blocks as well. While Tor supports the SOCKS protocol,
  774. which provides a standardized interface for generic TCP proxies, many
  775. applications do not support SOCKS\@. For them we must
  776. replace the networking system calls with SOCKS-aware
  777. versions, or run a SOCKS tunnel locally, neither of which is
  778. easy for the average user. %---even with good instructions.
  779. Even when applications do use SOCKS, they often make DNS requests
  780. themselves before handing the address to Tor, which advertises
  781. where the user is about to connect.
  782. We are still working on usable solutions.
  783. %So in order to actually provide good anonymity, we need to make sure that
  784. %users have a practical way to use Tor anonymously. Possibilities include
  785. %writing wrappers for applications to anonymize them automatically; improving
  786. %the applications' support for SOCKS; writing libraries to help application
  787. %writers use Tor properly; and implementing a local DNS proxy to reroute DNS
  788. %requests to Tor so that applications can simply point their DNS resolvers at
  789. %localhost and continue to use SOCKS for data only.
  790. \subsection{Mid-latency}
  791. \label{subsec:mid-latency}
  792. Some users need to resist traffic correlation attacks. Higher-latency
  793. mix-networks resist these attacks by introducing variability into message
  794. arrival times: as timing variance increases, timing correlation attacks
  795. require increasingly more data~\cite{e2e-traffic}. Can we improve Tor's
  796. resistance to these attacks without losing too much usability?
  797. %by introducing batching
  798. %and delaying strategies to the Tor messages?
  799. First, we need to learn whether we can trade a small increase in latency
  800. for a large anonymity increase, or if we'll end up trading a lot of
  801. latency for a small security gain. It would be worthwhile even if we
  802. can only protect certain use cases, such as infrequent short-duration
  803. transactions. In order to answer this question, we might
  804. try to adapt the techniques of~\cite{e2e-traffic} to a lower-latency mix
  805. network, where instead of sending messages, users send batches
  806. of cells in temporally clustered connections.
  807. Once the anonymity questions are answered, we need to consider usability. If
  808. the latency could be kept to two or three times its current overhead, this
  809. might be acceptable to most Tor users. However, it might also destroy much of
  810. the user base, and it is difficult to know in advance. Note also that in
  811. practice, as the network grows to incorporate more DSL and cable-modem nodes,
  812. and more nodes in various continents, there are \emph{already}
  813. many-second increases for some transactions. It could be possible to
  814. run a mid-latency option over the Tor network for those
  815. users either willing to experiment or in need of more
  816. anonymity. This would allow us to experiment with both
  817. the anonymity provided and the interest on the part of users.
  818. Adding a mid-latency option should not require significant fundamental
  819. change to the Tor client or server design; circuits could be labeled as
  820. low- or mid- latency as they are constructed. Low-latency traffic
  821. would be processed as now, while cells on circuits that are mid-latency
  822. would be sent in uniform-size chunks at synchronized intervals. (Traffic
  823. already moves through the Tor network in fixed-sized cells; this would
  824. increase the granularity.) If nodes forward these chunks in roughly
  825. synchronous fashion, it will increase the similarity of data stream timing
  826. signatures. By experimenting with the granularity of data chunks and
  827. of synchronization we can attempt once again to optimize for both
  828. usability and anonymity. Unlike in \cite{sync-batching}, it may be
  829. impractical to synchronize on end-to-end network batches.
  830. But, batch timing could be obscured by
  831. synchronizing batches at the link level.
  832. %Alternatively, if end-to-end traffic correlation is the
  833. %concern, there is little point in mixing.
  834. % Why not?? -NM
  835. It might also be feasible to
  836. pad chunks to uniform size as is done now for cells; if this is link
  837. padding rather than end-to-end, then it will take less overhead,
  838. especially in bursty environments.
  839. % This is another way in which it
  840. %would be fairly practical to set up a mid-latency option within the
  841. %existing Tor network.
  842. Other padding regimens might supplement the
  843. mid-latency option; however, we should continue the caution with which
  844. we have always approached padding lest the overhead cost us too much
  845. performance or too many volunteers.
  846. \subsection{Measuring performance and capacity}
  847. \label{subsec:performance}
  848. One of the paradoxes with engineering an anonymity network is that we'd like
  849. to learn as much as we can about how traffic flows so we can improve the
  850. network, but we want to prevent others from learning how traffic flows in
  851. order to trace users' connections through the network. Furthermore, many
  852. mechanisms that help Tor run efficiently (such as having clients choose nodes
  853. based on their capacities) require measurements about the network.
  854. Currently, nodes record their bandwidth use in 15-minute intervals and
  855. include this information in the descriptors they upload to the directory.
  856. They also try to deduce their own available bandwidth (based on how
  857. much traffic they have been able to transfer recently) and upload this
  858. information as well.
  859. This is, of course, eminently cheatable. A malicious node can get a
  860. disproportionate amount of traffic simply by claiming to have more bandwidth
  861. than it does. But better mechanisms have their problems. If bandwidth data
  862. is to be measured rather than self-reported, it is usually possible for
  863. nodes to selectively provide better service for the measuring party, or
  864. sabotage the measured value of other nodes. Complex solutions for
  865. mix networks have been proposed, but do not address the issues
  866. completely~\cite{mix-acc,casc-rep}.
  867. Even with no cheating, network measurement is complex. It is common
  868. for views of a node's latency and/or bandwidth to vary wildly between
  869. observers. Further, it is unclear whether total bandwidth is really
  870. the right measure; perhaps clients should instead be considering nodes
  871. based on unused bandwidth or observed throughput.
  872. % XXXX say more here?
  873. %How to measure performance without letting people selectively deny service
  874. %by distinguishing pings. Heck, just how to measure performance at all. In
  875. %practice people have funny firewalls that don't match up to their exit
  876. %policies and Tor doesn't deal.
  877. %Network investigation: Is all this bandwidth publishing thing a good idea?
  878. %How can we collect stats better? Note weasel's smokeping, at
  879. %http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  880. %which probably gives george and steven enough info to break tor?
  881. Even if we can collect and use this network information effectively, we need
  882. to make sure that it is not more useful to attackers than to us. While it
  883. seems plausible that bandwidth data alone is not enough to reveal
  884. sender-recipient connections under most circumstances, it could certainly
  885. reveal the path taken by large traffic flows under low-usage circumstances.
  886. \subsection{Running a Tor node, path length, and helper nodes}
  887. \label{subsec:helper-nodes}
  888. It has been thought for some time that the best anonymity protection
  889. comes from running your own node~\cite{or-pet00,tor-design}.
  890. (In fact, in Onion Routing's first design, this was the only option
  891. possible~\cite{or-ih96}.) While the first implementation
  892. had a fixed path length of five nodes, first generation
  893. Onion Routing design included random length routes chosen
  894. to simultaneously maximize efficiency and unpredictability in routes.
  895. If one followed Tor's three node default
  896. path length, an enclave-to-enclave communication (in which the entry and
  897. exit nodes were run by enclaves themselves)
  898. would be completely compromised by the
  899. middle node. Thus for enclave-to-enclave communication, four is the fewest
  900. number of nodes that preserves the $\frac{c^2}{n^2}$ degree of protection
  901. in any setting.
  902. The attack in~\cite{attack-tor-oak05}, however,
  903. shows that simply adding to the
  904. path length may not protect usage of an enclave protecting node. A
  905. hostile web server can observe interference with latency of its own
  906. communication to nodes to determine all of the nodes in a three node Tor
  907. path (although not their order).
  908. It is reasonable to think that this attack can be easily extended to
  909. longer paths should those be used; nonetheless there may be some
  910. advantage to random path length. If the number of nodes is unknown,
  911. then the adversary would need to send streams to all the nodes in the
  912. network and analyze the resulting latency from them to be reasonably
  913. certain that it has not missed the first node in the circuit. Also,
  914. the attack does not identify the order of nodes in a route, so the
  915. longer the route, the greater the uncertainty about which node might
  916. be first. It may be possible to extend the attack to learn the route
  917. node order, but this has not been explored.
  918. If so, the incompleteness uncertainty engendered by random lengths would
  919. remain, but once the complete set of nodes in the route were identified
  920. the initiating node would also be identified.
  921. Another way to reduce the threats to both enclaves and simple Tor
  922. clients is to have helper nodes. Helper nodes were introduced
  923. in~\cite{wright03} as a suggested means of protecting the identity
  924. of the initiator of a communication in various anonymity protocols.
  925. The idea is to use a single trusted node as the first one you go to,
  926. that way an attacker cannot ever attack the first nodes you connect
  927. to and do some form of intersection attack. This will not affect the
  928. interference attack at all if the attacker can time latencies to
  929. both the helper node and the enclave node.
  930. \medskip
  931. \noindent
  932. {\bf Helper nodes.}
  933. Tor can only provide anonymity against an attacker if that attacker can't
  934. monitor the user's entry and exit on the Tor network. But since Tor
  935. currently chooses entry and exit points randomly and changes them frequently,
  936. a patient attacker who controls a single entry and a single exit is sure to
  937. eventually break some circuits of frequent users who consider those nodes.
  938. (We assume that users are as concerned about statistical profiling as about
  939. the anonymity any particular connection. That is, it is almost as bad to
  940. leak the fact that Alice {\it sometimes} talks to Bob as it is to leak the times
  941. when Alice is {\it actually} talking to Bob.)
  942. One solution to this problem is to use ``helper nodes''~\cite{wright02,wright03}---to
  943. have each client choose a few fixed nodes for critical positions in her
  944. circuits. That is, Alice might choose some node H1 as her preferred
  945. entry, so that unless the attacker happens to control or observe her
  946. connection to H1, her circuits will remain anonymous. If H1 is compromised,
  947. Alice is vunerable as before. But now, at least, she has a chance of
  948. not being profiled.
  949. (Choosing fixed exit nodes is less useful, since the connection from the exit
  950. node to Alice's destination will be seen not only by the exit but by the
  951. destination. Even if Alice chooses a good fixed exit node, she may
  952. nevertheless connect to a hostile website.)
  953. There are still obstacles remaining before helper nodes can be implemented.
  954. For one, the litereature does not describe how to choose helpers from a list
  955. of nodes that changes over time. If Alice is forced to choose a new entry
  956. helper every $d$ days, she can expect to choose a compromised node around
  957. every $dc/n$ days. Statistically over time this approach only helps
  958. if she is better at choosing honest helper nodes than at choosing
  959. honest nodes. Worse, an attacker with the ability to DoS nodes could
  960. force their users to switch helper nodes more frequently and/or to remove
  961. other candidate helpers.
  962. %Do general DoS attacks have anonymity implications? See e.g. Adam
  963. %Back's IH paper, but I think there's more to be pointed out here. -RD
  964. % Not sure what you want to say here. -NM
  965. %Game theory for helper nodes: if Alice offers a hidden service on a
  966. %server (enclave model), and nobody ever uses helper nodes, then against
  967. %George+Steven's attack she's totally nailed. If only Alice uses a helper
  968. %node, then she's still identified as the source of the data. If everybody
  969. %uses a helper node (including Alice), then the attack identifies the
  970. %helper node and also Alice, and knows which one is which. If everybody
  971. %uses a helper node (but not Alice), then the attacker figures the real
  972. %source was a client that is using Alice as a helper node. [How's my
  973. %logic here?] -RD
  974. %
  975. % Not sure about the logic. For the attack to work with helper nodes, the
  976. %attacker needs to guess that Alice is running the hidden service, right?
  977. %Otherwise, how can he know to measure her traffic specifically? -NM
  978. %point to routing-zones section re: helper nodes to defend against
  979. %big stuff.
  980. \subsection{Location-hidden services}
  981. \label{subsec:hidden-services}
  982. While most of the discussions above have been about forward anonymity
  983. with Tor, it also provides support for \emph{rendezvous points}, which
  984. let users provide TCP services to other Tor users without revealing
  985. their location. Since this feature is relatively recent, we describe here
  986. a couple of our early observations from its deployment.
  987. First, our implementation of hidden services seems less hidden than we'd
  988. like, since they are configured on a single client and get used over
  989. and over---particularly because an external adversary can induce them to
  990. produce traffic. They seem the ideal use case for our above discussion
  991. of helper nodes. This insecurity means that they may not be suitable as
  992. a building block for Free Haven~\cite{freehaven-berk} or other anonymous
  993. publishing systems that aim to provide long-term security.
  994. %Also, they're brittle in terms of intersection and observation attacks.
  995. \emph{Hot-swap} hidden services, where more than one location can
  996. provide the service and loss of any one location does not imply a
  997. change in service, would help foil intersection and observation attacks
  998. where an adversary monitors availability of a hidden service and also
  999. monitors whether certain users or servers are online. The design
  1000. challenges in providing these services without otherwise compromising
  1001. the hidden service's anonymity remain an open problem;
  1002. however, see~\cite{move-ndss05}.
  1003. In practice, hidden services are used for more than just providing private
  1004. access to a web server or IRC server. People are using hidden services
  1005. as a poor man's VPN and firewall-buster. Many people want to be able
  1006. to connect to the computers in their private network via secure shell,
  1007. and rather than playing with dyndns and trying to pierce holes in their
  1008. firewall, they run a hidden service on the inside and then rendezvous
  1009. with that hidden service externally.
  1010. Also, sites like Bloggers Without Borders (www.b19s.org) are advertising
  1011. a hidden-service address on their front page. Doing this can provide
  1012. increased robustness if they use the dual-IP approach we describe
  1013. in~\cite{tor-design},
  1014. but in practice they do it firstly to increase visibility
  1015. of the Tor project and their support for privacy, and secondly to offer
  1016. a way for their users, using unmodified software, to get end-to-end
  1017. encryption and end-to-end authentication to their website.
  1018. \subsection{Trust and discovery}
  1019. \label{subsec:trust-and-discovery}
  1020. [arma will edit this and expand/retract it]
  1021. The published Tor design adopted a deliberately simplistic design for
  1022. authorizing new nodes and informing clients about Tor nodes and their status.
  1023. In the early Tor designs, all nodes periodically uploaded a signed description
  1024. of their locations, keys, and capabilities to each of several well-known {\it
  1025. directory servers}. These directory servers constructed a signed summary
  1026. of all known Tor nodes (a ``directory''), and a signed statement of which
  1027. nodes they
  1028. believed to be operational at any given time (a ``network status''). Clients
  1029. periodically downloaded a directory in order to learn the latest nodes and
  1030. keys, and more frequently downloaded a network status to learn which nodes are
  1031. likely to be running. Tor nodes also operate as directory caches, in order to
  1032. lighten the bandwidth on the authoritative directory servers.
  1033. In order to prevent Sybil attacks (wherein an adversary signs up many
  1034. purportedly independent nodes in order to increase her chances of observing
  1035. a stream as it enters and leaves the network), the early Tor directory design
  1036. required the operators of the authoritative directory servers to manually
  1037. approve new nodes. Unapproved nodes were included in the directory,
  1038. but clients
  1039. did not use them at the start or end of their circuits. In practice,
  1040. directory administrators performed little actual verification, and tended to
  1041. approve any Tor node whose operator could compose a coherent email.
  1042. This procedure
  1043. may have prevented trivial automated Sybil attacks, but would do little
  1044. against a clever attacker.
  1045. There are a number of flaws in this system that need to be addressed as we
  1046. move forward. They include:
  1047. \begin{tightlist}
  1048. \item Each directory server represents an independent point of failure; if
  1049. any one were compromised, it could immediately compromise all of its users
  1050. by recommending only compromised nodes.
  1051. \item The more nodes join the network, the more unreasonable it
  1052. becomes to expect clients to know about them all. Directories
  1053. become infeasibly large, and downloading the list of nodes becomes
  1054. burdensome.
  1055. \item The validation scheme may do as much harm as it does good. It is not
  1056. only incapable of preventing clever attackers from mounting Sybil attacks,
  1057. but may deter node operators from joining the network. (For instance, if
  1058. they expect the validation process to be difficult, or if they do not share
  1059. any languages in common with the directory server operators.)
  1060. \end{tightlist}
  1061. We could try to move the system in several directions, depending on our
  1062. choice of threat model and requirements. If we did not need to increase
  1063. network capacity in order to support more users, we could simply
  1064. adopt even stricter validation requirements, and reduce the number of
  1065. nodes in the network to a trusted minimum.
  1066. But, we can only do that if can simultaneously make node capacity
  1067. scale much more than we anticipate feasible soon, and if we can find
  1068. entities willing to run such nodes, an equally daunting prospect.
  1069. In order to address the first two issues, it seems wise to move to a system
  1070. including a number of semi-trusted directory servers, no one of which can
  1071. compromise a user on its own. Ultimately, of course, we cannot escape the
  1072. problem of a first introducer: since most users will run Tor in whatever
  1073. configuration the software ships with, the Tor distribution itself will
  1074. remain a potential single point of failure so long as it includes the seed
  1075. keys for directory servers, a list of directory servers, or any other means
  1076. to learn which nodes are on the network. But omitting this information
  1077. from the Tor distribution would only delegate the trust problem to the
  1078. individual users, most of whom are presumably less informed about how to make
  1079. trust decisions than the Tor developers.
  1080. %Network discovery, sybil, node admission, scaling. It seems that the code
  1081. %will ship with something and that's our trust root. We could try to get
  1082. %people to build a web of trust, but no. Where we go from here depends
  1083. %on what threats we have in mind. Really decentralized if your threat is
  1084. %RIAA; less so if threat is to application data or individuals or...
  1085. \section{Scaling}
  1086. %\label{sec:crossroads-scaling}
  1087. %P2P + anonymity issues:
  1088. Tor is running today with hundreds of nodes and tens of thousands of
  1089. users, but it will certainly not scale to millions.
  1090. Scaling Tor involves three main challenges. First is safe node
  1091. discovery, both bootstrapping -- how a Tor client can robustly find an
  1092. initial node list -- and ongoing -- how a Tor client can learn about
  1093. a fair sample of honest nodes and not let the adversary control his
  1094. circuits (see Section~\ref{subsec:trust-and-discovery}). Second is detecting and handling the speed
  1095. and reliability of the variety of nodes we must use if we want to
  1096. accept many nodes (see Section~\ref{subsec:performance}).
  1097. Since the speed and reliability of a circuit is limited by its worst link,
  1098. we must learn to track and predict performance. Finally, in order to get
  1099. a large set of nodes in the first place, we must address incentives
  1100. for users to carry traffic for others (see Section incentives).
  1101. \subsection{Incentives by Design}
  1102. There are three behaviors we need to encourage for each Tor node: relaying
  1103. traffic; providing good throughput and reliability while doing it;
  1104. and allowing traffic to exit the network from that node.
  1105. We encourage these behaviors through \emph{indirect} incentives, that
  1106. is, designing the system and educating users in such a way that users
  1107. with certain goals will choose to relay traffic. One
  1108. main incentive for running a Tor node is social benefit: volunteers
  1109. altruistically donate their bandwidth and time. We also keep public
  1110. rankings of the throughput and reliability of nodes, much like
  1111. seti@home. We further explain to users that they can get plausible
  1112. deniability for any traffic emerging from the same address as a Tor
  1113. exit node, and they can use their own Tor node
  1114. as entry or exit point and be confident it's not run by the adversary.
  1115. Further, users who need to be able to communicate anonymously
  1116. may run a node simply because their need to increase
  1117. expectation that such a network continues to be available to them
  1118. and usable exceeds any countervening costs.
  1119. Finally, we can improve the usability and feature set of the software:
  1120. rate limiting support and easy packaging decrease the hassle of
  1121. maintaining a node, and our configurable exit policies allow each
  1122. operator to advertise a policy describing the hosts and ports to which
  1123. he feels comfortable connecting.
  1124. To date these appear to have been adequate. As the system scales or as
  1125. new issues emerge, however, we may also need to provide
  1126. \emph{direct} incentives:
  1127. providing payment or other resources in return for high-quality service.
  1128. Paying actual money is problematic: decentralized e-cash systems are
  1129. not yet practical, and a centralized collection system not only reduces
  1130. robustness, but also has failed in the past (the history of commercial
  1131. anonymizing networks is littered with failed attempts). A more promising
  1132. option is to use a tit-for-tat incentive scheme: provide better service
  1133. to nodes that have provided good service to you.
  1134. Unfortunately, such an approach introduces new anonymity problems.
  1135. There are many surprising ways for nodes to game the incentive and
  1136. reputation system to undermine anonymity because such systems are
  1137. designed to encourage fairness in storage or bandwidth usage not
  1138. fairness of provided anonymity. An adversary can attract more traffic
  1139. by performing well or can provide targeted differential performance to
  1140. individual users to undermine their anonymity. Typically a user who
  1141. chooses evenly from all options is most resistant to an adversary
  1142. targeting him, but that approach prevents from handling heterogeneous
  1143. nodes.
  1144. %When a node (call him Steve) performs well for Alice, does Steve gain
  1145. %reputation with the entire system, or just with Alice? If the entire
  1146. %system, how does Alice tell everybody about her experience in a way that
  1147. %prevents her from lying about it yet still protects her identity? If
  1148. %Steve's behavior only affects Alice's behavior, does this allow Steve to
  1149. %selectively perform only for Alice, and then break her anonymity later
  1150. %when somebody (presumably Alice) routes through his node?
  1151. A possible solution is a simplified approach to the tit-for-tat
  1152. incentive scheme based on two rules: (1) each node should measure the
  1153. service it receives from adjacent nodes, and provide service relative
  1154. to the received service, but (2) when a node is making decisions that
  1155. affect its own security (e.g. when building a circuit for its own
  1156. application connections), it should choose evenly from a sufficiently
  1157. large set of nodes that meet some minimum service threshold
  1158. \cite{casc-rep}. This approach allows us to discourage bad service
  1159. without opening Alice up as much to attacks. All of this requires
  1160. further study.
  1161. %XXX rewrite the above so it sounds less like a grant proposal and
  1162. %more like a "if somebody were to try to solve this, maybe this is a
  1163. %good first step".
  1164. %We should implement the above incentive scheme in the
  1165. %deployed Tor network, in conjunction with our plans to add the necessary
  1166. %associated scalability mechanisms. We will do experiments (simulated
  1167. %and/or real) to determine how much the incentive system improves
  1168. %efficiency over baseline, and also to determine how far we are from
  1169. %optimal efficiency (what we could get if we ignored the anonymity goals).
  1170. \subsection{Location diversity and ISP-class adversaries}
  1171. \label{subsec:routing-zones}
  1172. Anonymity networks have long relied on diversity of node location for
  1173. protection against attacks---typically an adversary who can observe a
  1174. larger fraction of the network can launch a more effective attack. One
  1175. way to achieve dispersal involves growing the network so a given adversary
  1176. sees less. Alternately, we can arrange the topology so traffic can enter
  1177. or exit at many places (for example, by using a free-route network
  1178. like Tor rather than a cascade network like JAP). Lastly, we can use
  1179. distributed trust to spread each transaction over multiple jurisdictions.
  1180. But how do we decide whether two nodes are in related locations?
  1181. Feamster and Dingledine defined a \emph{location diversity} metric
  1182. in \cite{feamster:wpes2004}, and began investigating a variant of location
  1183. diversity based on the fact that the Internet is divided into thousands of
  1184. independently operated networks called {\em autonomous systems} (ASes).
  1185. The key insight from their paper is that while we typically think of a
  1186. connection as going directly from the Tor client to her first Tor node,
  1187. actually it traverses many different ASes on each hop. An adversary at
  1188. any of these ASes can monitor or influence traffic. Specifically, given
  1189. plausible initiators and recipients and path random path selection,
  1190. some ASes in the simulation were able to observe 10\% to 30\% of the
  1191. transactions (that is, learn both the origin and the destination) on
  1192. the deployed Tor network (33 nodes as of June 2004).
  1193. The paper concludes that for best protection against the AS-level
  1194. adversary, nodes should be in ASes that have the most links to other ASes:
  1195. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  1196. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  1197. initiator and responder are both in the U.S., it actually \emph{hurts}
  1198. our location diversity to add far-flung nodes in continents like Asia
  1199. or South America.
  1200. Many open questions remain. First, it will be an immense engineering
  1201. challenge to get an entire BGP routing table to each Tor client, or at
  1202. least summarize it sufficiently. Without a local copy, clients won't be
  1203. able to safely predict what ASes will be traversed on the various paths
  1204. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  1205. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  1206. determine location diversity; but the above paper showed that in practice
  1207. many of the Mixmaster nodes that share a single AS have entirely different
  1208. IP prefixes. When the network has scaled to thousands of nodes, does IP
  1209. prefix comparison become a more useful approximation?
  1210. %
  1211. Second, can take advantage of caching certain content at the exit nodes, to
  1212. limit the number of requests that need to leave the network at all.
  1213. what about taking advantage of caches like akamai's or googles? what
  1214. about treating them as adversaries?
  1215. %
  1216. Third, if we follow the paper's recommendations and tailor path selection
  1217. to avoid choosing endpoints in similar locations, how much are we hurting
  1218. anonymity against larger real-world adversaries who can take advantage
  1219. of knowing our algorithm?
  1220. %
  1221. Lastly, can we use this knowledge to figure out which gaps in our network
  1222. would most improve our robustness to this class of attack, and go recruit
  1223. new nodes with those ASes in mind?
  1224. Tor's security relies in large part on the dispersal properties of its
  1225. network. We need to be more aware of the anonymity properties of various
  1226. approaches we can make better design decisions in the future.
  1227. \subsection{The China problem}
  1228. \label{subsec:china}
  1229. Citizens in a variety of countries, such as most recently China and
  1230. Iran, are periodically blocked from accessing various sites outside
  1231. their country. These users try to find any tools available to allow
  1232. them to get-around these firewalls. Some anonymity networks, such as
  1233. Six-Four~\cite{six-four}, are designed specifically with this goal in
  1234. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  1235. such as Voice of America to set up a network to encourage Internet
  1236. freedom. Even though Tor wasn't
  1237. designed with ubiquitous access to the network in mind, thousands of
  1238. users across the world are trying to use it for exactly this purpose.
  1239. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  1240. Anti-censorship networks hoping to bridge country-level blocks face
  1241. a variety of challenges. One of these is that they need to find enough
  1242. exit nodes---servers on the `free' side that are willing to relay
  1243. arbitrary traffic from users to their final destinations. Anonymizing
  1244. networks including Tor are well-suited to this task, since we have
  1245. already gathered a set of exit nodes that are willing to tolerate some
  1246. political heat.
  1247. The other main challenge is to distribute a list of reachable relays
  1248. to the users inside the country, and give them software to use them,
  1249. without letting the authorities also enumerate this list and block each
  1250. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  1251. addresses (or having them donated), abandoning old addresses as they are
  1252. `used up', and telling a few users about the new ones. Distributed
  1253. anonymizing networks again have an advantage here, in that we already
  1254. have tens of thousands of separate IP addresses whose users might
  1255. volunteer to provide this service since they've already installed and use
  1256. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1257. the Tor protocol separates routing from network discovery \cite{tor-design},
  1258. volunteers could configure their Tor clients
  1259. to generate node descriptors and send them to a special directory
  1260. server that gives them out to dissidents who need to get around blocks.
  1261. Of course, this still doesn't prevent the adversary
  1262. from enumerating all the volunteer relays and blocking them preemptively.
  1263. Perhaps a tiered-trust system could be built where a few individuals are
  1264. given relays' locations, and they recommend other individuals by telling them
  1265. those addresses, thus providing a built-in incentive to avoid letting the
  1266. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1267. might help to bound the number of IP addresses leaked to the adversary. Groups
  1268. like the W3C are looking into using Tor as a component in an overall system to
  1269. help address censorship; we wish them luck.
  1270. %\cite{infranet}
  1271. \subsection{Non-clique topologies}
  1272. Tor's comparatively weak model makes it easier to scale than other mix net
  1273. designs. High-latency mix networks need to avoid partitioning attacks, where
  1274. network splits prevent users of the separate partitions from providing cover
  1275. for each other. In Tor, however, we assume that the adversary cannot
  1276. cheaply observe nodes at will, so even if the network becomes split, the
  1277. users do not necessarily receive much less protection.
  1278. Thus, a simple possibility when the scale of a Tor network
  1279. exceeds some size is to simply split it. Care could be taken in
  1280. allocating which nodes go to which network along the lines of
  1281. \cite{casc-rep} to insure that collaborating hostile nodes are not
  1282. able to gain any advantage in network splitting that they do not
  1283. already have in joining a network.
  1284. If the network is split,
  1285. a client does not need to use just one of the two resulting networks.
  1286. Alice could use either of them, and it would not be difficult to make
  1287. the Tor client able to access several such network on a per circuit
  1288. basis. More analysis is needed; we simply note here that splitting
  1289. a Tor network is an easy way to achieve moderate scalability and that
  1290. it does not necessarily have the same implications as splitting a mixnet.
  1291. Alternatively, we can try to scale a single Tor network. Some issues for
  1292. scaling include restricting the number of sockets and the amount of bandwidth
  1293. used by each node. The number of sockets is determined by the network's
  1294. connectivity and the number of users, while bandwidth capacity is determined
  1295. by the total bandwidth of nodes on the network. The simplest solution to
  1296. bandwidth capacity is to add more nodes, since adding a tor node of any
  1297. feasible bandwidth will increase the traffic capacity of the network. So as
  1298. a first step to scaling, we should focus on making the network tolerate more
  1299. nodes, by reducing the interconnectivity of the nodes; later we can reduce
  1300. overhead associated with directories, discovery, and so on.
  1301. By reducing the connectivity of the network we increase the total number of
  1302. nodes that the network can contain. Danezis~\cite{danezis-pets03} considers
  1303. the anonymity implications of restricting routes on mix networks, and
  1304. recommends an approach based on expander graphs (where any subgraph is likely
  1305. to have many neighbors). It is not immediately clear that this approach will
  1306. extend to Tor, which has a weaker threat model but higher performance
  1307. requirements than the network considered. Instead of analyzing the
  1308. probability of an attacker's viewing whole paths, we will need to examine the
  1309. attacker's likelihood of compromising the endpoints of a Tor circuit through
  1310. a sparse network.
  1311. % Nick edits these next 2 grafs.
  1312. To make matters simpler, Tor may not need an expander graph per se: it
  1313. may be enough to have a single subnet that is highly connected. As an
  1314. example, assume fifty nodes of relatively high traffic capacity. This
  1315. \emph{center} forms are a clique. Assume each center node can each
  1316. handle 200 connections to other nodes (including the other ones in the
  1317. center). Assume every noncenter node connects to three nodes in the
  1318. center and anyone out of the center that they want to. Then the
  1319. network easily scales to c. 2500 nodes with commensurate increase in
  1320. bandwidth. There are many open questions: how directory information
  1321. is distributed (presumably information about the center nodes could
  1322. be given to any new nodes with their codebase), whether center nodes
  1323. will need to function as a `backbone', etc. As above the point is
  1324. that this would create problems for the expected anonymity for a mixnet,
  1325. but for an onion routing network where anonymity derives largely from
  1326. the edges, it may be feasible.
  1327. Another point is that we already have a non-clique topology.
  1328. Individuals can set up and run Tor nodes without informing the
  1329. directory servers. This will allow, e.g., dissident groups to run a
  1330. local Tor network of such nodes that connects to the public Tor
  1331. network. This network is hidden behind the Tor network and its
  1332. only visible connection to Tor at those points where it connects.
  1333. As far as the public network is concerned or anyone observing it,
  1334. they are running clients.
  1335. \section{The Future}
  1336. \label{sec:conclusion}
  1337. we should put random thoughts here until there are enough for a
  1338. conclusion.
  1339. will our sustainability approach work? we'll see.
  1340. Applications that leak data: we can say they're not our problem, but
  1341. they're somebody's problem.
  1342. The more widely deployed Tor becomes, the more people who need a
  1343. deployed overlay network tell us they'd like to use us if only we added
  1344. the following more features.
  1345. "These are difficult and open questions, yet choosing not to solve them
  1346. means leaving most users to a less secure network or no anonymizing
  1347. network at all."
  1348. \bibliographystyle{plain} \bibliography{tor-design}
  1349. \clearpage
  1350. \appendix
  1351. \begin{figure}[t]
  1352. %\unitlength=1in
  1353. \centering
  1354. %\begin{picture}(6.0,2.0)
  1355. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1356. %\end{picture}
  1357. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1358. \caption{Number of Tor nodes over time. Lowest line is number of exit
  1359. nodes that allow connections to port 80. Middle line is total number of
  1360. verified (registered) Tor nodes. The line above that represents nodes
  1361. that are not yet registered.}
  1362. \label{fig:graphnodes}
  1363. \end{figure}
  1364. \begin{figure}[t]
  1365. \centering
  1366. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1367. \caption{The sum of traffic reported by each node over time. The bottom
  1368. pair show average throughput, and the top pair represent the largest 15
  1369. minute burst in each 4 hour period.}
  1370. \label{fig:graphtraffic}
  1371. \end{figure}
  1372. \section{Things to cut?}
  1373. \subsection{Peer-to-peer / practical issues}
  1374. [leave this section for now, and make sure things here are covered
  1375. elsewhere. then remove it.]
  1376. Making use of nodes with little bandwidth. How to handle hammering by
  1377. certain applications.
  1378. Handling nodes that are far away from the rest of the network, e.g. on
  1379. the continents that aren't North America and Europe. High latency,
  1380. often high packet loss.
  1381. Running Tor nodes behind NATs, behind great-firewalls-of-China, etc.
  1382. Restricted routes. How to propagate to everybody the topology? BGP
  1383. style doesn't work because we don't want just *one* path. Point to
  1384. Geoff's stuff.
  1385. \subsection{Caching stuff: If a topic's gotta go for space, I think this
  1386. is the best candidate}
  1387. The attacks in \cite{attack-tor-oak05} are also dependent on
  1388. cooperation of the responding application or the ability to modify or
  1389. monitor the responder stream, in order of decreasing attack
  1390. effectiveness. So, another way to slow some of these attacks
  1391. would be to cache responses at exit nodes where possible, as it is with
  1392. DNS lookups and cacheable HTTP responses. Caching would, however,
  1393. create threats of its own. First, a Tor network is expected to contain
  1394. hostile nodes. If one of these is the repository of a cache, the
  1395. attack is still possible. Though more work to set up a Tor node and
  1396. cache repository, the payoff of such an attack is potentially
  1397. higher.
  1398. %To be
  1399. %useful, such caches would need to be distributed to any likely exit
  1400. %nodes of recurred requests for the same data.
  1401. % Even local caches could be useful, I think. -NM
  1402. %
  1403. %Added some clarification -PFS
  1404. Besides allowing any other insider attacks, caching nodes would hold a
  1405. record of destinations and data visited by Tor users reducing forward
  1406. anonymity. Worse, for the cache to be widely useful much beyond the
  1407. client that caused it there would have to either be a new mechanism to
  1408. distribute cache information around the network and a way for clients
  1409. to make use of it or the caches themselves would need to be
  1410. distributed widely. Either way the record of visited sites and
  1411. downloaded information is made automatically available to an attacker
  1412. without having to actively gather it himself. Besides its inherent
  1413. value, this could serve as useful data to an attacker deciding which
  1414. locations to target for confirmation. A way to counter this
  1415. distribution threat might be to only cache at certain semitrusted
  1416. helper nodes. This might help specific clients, but it would limit
  1417. the general value of caching.
  1418. \end{document}