challenges.tex 79 KB

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  1. \documentclass{llncs}
  2. % XXXX NM: Fold ``bandwidth and usability'' into ``Tor and file-sharing'' --
  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
  22. Nick Mathewson\inst{1} \and
  23. Paul Syverson\inst{2}}
  24. \institute{The Free Haven Project \email{<\{arma,nickm\}@freehaven.net>} \and
  25. Naval Research Lab \email{<syverson@itd.nrl.navy.mil>}}
  26. \maketitle
  27. \pagestyle{plain}
  28. \begin{abstract}
  29. There are many unexpected or unexpectedly difficult obstacles to
  30. deploying anonymous communications. Drawing on our experiences deploying
  31. Tor (the second-generation onion routing network), we describe social
  32. challenges and technical issues that must be faced
  33. in building, deploying, and sustaining a scalable, distributed, low-latency
  34. anonymity network.
  35. \end{abstract}
  36. \section{Introduction}
  37. % Your network is not practical unless it is sustainable and distributed.
  38. Anonymous communication is full of surprises. This paper discusses some
  39. unexpected challenges arising from our experiences deploying Tor, a
  40. low-latency general-purpose anonymous communication system. We will discuss
  41. some of the difficulties we have experienced and how we have met them (or how
  42. we plan to meet them, if we know). We will also discuss some less
  43. troublesome open problems that we must nevertheless eventually address.
  44. %We will describe both those future challenges that we intend to explore and
  45. %those that we have decided not to explore and why.
  46. Tor is an overlay network for anonymizing TCP streams over the
  47. Internet~\cite{tor-design}. It addresses limitations in earlier Onion
  48. Routing designs~\cite{or-ih96,or-jsac98,or-discex00,or-pet00} by adding
  49. perfect forward secrecy, congestion control, directory servers, integrity
  50. checking, configurable exit policies, and location-hidden services using
  51. rendezvous points. Tor works on the real-world Internet, requires no special
  52. privileges or kernel modifications, requires little synchronization or
  53. coordination between nodes, and provides a reasonable tradeoff between
  54. anonymity, usability, and efficiency.
  55. We first publicly deployed a Tor network in October 2003; since then it has
  56. grown to over a hundred volunteer Tor nodes
  57. and as much as 80 megabits of
  58. average traffic per second. Tor's research strategy has focused on deploying
  59. a network to as many users as possible; thus, we have resisted designs that
  60. would compromise deployability by imposing high resource demands on node
  61. operators, and designs that would compromise usability by imposing
  62. unacceptable restrictions on which applications we support. Although this
  63. strategy has
  64. its drawbacks (including a weakened threat model, as discussed below), it has
  65. made it possible for Tor to serve many thousands of users and attract
  66. funding from diverse sources whose goals range from security on a
  67. national scale down to the liberties of each individual.
  68. While the Tor design paper~\cite{tor-design} gives an overall view of Tor's
  69. design and goals, this paper describes some policy, social, and technical
  70. issues that we face as we continue deployment.
  71. Rather than trying to provide complete solutions to every problem here, we
  72. lay out the assumptions and constraints that we have observed while
  73. deploying Tor in the wild. In doing so, we aim to create a research agenda
  74. for others to help in addressing these issues. We believe that the issues
  75. described here will be of general interest to projects attempting to build
  76. and deploy practical, useable anonymity networks in the wild.
  77. %While the Tor design paper~\cite{tor-design} gives an overall view its
  78. %design and goals,
  79. %this paper describes the policy and technical issues that Tor faces as
  80. %we continue deployment. Rather than trying to provide complete solutions
  81. %to every problem here, we lay out the assumptions and constraints
  82. %that we have observed through deploying Tor in the wild. In doing so, we
  83. %aim to create a research agenda for others to
  84. %help in addressing these issues.
  85. % Section~\ref{sec:what-is-tor} gives an
  86. %overview of the Tor
  87. %design and ours goals. Sections~\ref{sec:crossroads-policy}
  88. %and~\ref{sec:crossroads-design} go on to describe the practical challenges,
  89. %both policy and technical respectively,
  90. %that stand in the way of moving
  91. %from a practical useful network to a practical useful anonymous network.
  92. %\section{What Is Tor}
  93. \section{Background}
  94. Here we give a basic overview of the Tor design and its properties, and
  95. compare Tor to other low-latency anonymity designs.
  96. \subsection{Tor, threat models, and distributed trust}
  97. \label{sec:what-is-tor}
  98. %Here we give a basic overview of the Tor design and its properties. For
  99. %details on the design, assumptions, and security arguments, we refer
  100. %the reader to the Tor design paper~\cite{tor-design}.
  101. %\medskip
  102. \noindent
  103. {\bf How Tor works.}
  104. Tor provides \emph{forward privacy}, so that users can connect to
  105. Internet sites without revealing their logical or physical locations
  106. to those sites or to observers. It also provides \emph{location-hidden
  107. services}, so that critical servers can support authorized users without
  108. giving adversaries an effective vector for physical or online attacks.
  109. The design provides these protections even when a portion of its own
  110. infrastructure is controlled by an adversary.
  111. To create a private network pathway with Tor, the client software
  112. incrementally builds a \emph{circuit} of encrypted connections through
  113. Tor nodes on the network. The circuit is extended one hop at a time, and
  114. each node along the way knows only which node gave it data and which
  115. node it is giving data to. No individual Tor node ever knows the complete
  116. path that a data packet has taken. The client negotiates a separate set
  117. of encryption keys for each hop along the circuit.% to ensure that each
  118. %hop can't trace these connections as they pass through.
  119. Because each node sees no more than one hop in the
  120. circuit, neither an eavesdropper nor a compromised node can use traffic
  121. analysis to link the connection's source and destination.
  122. For efficiency, the Tor software uses the same circuit for all the TCP
  123. connections that happen within the same short period.
  124. Later requests use a new
  125. circuit, to prevent long-term linkability between different actions by
  126. a single user.
  127. Tor also makes it possible for users to hide their locations while
  128. offering various kinds of services, such as web publishing or an instant
  129. messaging server. Using ``rendezvous points'', other Tor users can
  130. connect to these hidden services, each without knowing the other's network
  131. identity.
  132. Tor attempts to anonymize the transport layer, not the application layer, so
  133. application protocols that include personally identifying information need
  134. additional application-level scrubbing proxies, such as
  135. Privoxy~\cite{privoxy} for HTTP. Furthermore, Tor does not permit arbitrary
  136. IP packets; it only anonymizes TCP streams and DNS request, and only supports
  137. connections via SOCKS (see Section~\ref{subsec:tcp-vs-ip}).
  138. Most node operators do not want to allow arbitary TCP connections to leave
  139. their server. To address this, Tor provides \emph{exit policies} so that
  140. each exit node can block the IP addresses and ports it is unwilling to allow.
  141. TRs advertise their exit policies to the directory servers, so that
  142. client can tell which nodes will support their connections.
  143. As of January 2005, the Tor network has grown to around a hundred nodes
  144. on four continents, with a total capacity exceeding 1Gbit/s. Appendix A
  145. shows a graph of the number of working nodes over time, as well as a
  146. vgraph of the number of bytes being handled by the network over time. At
  147. this point the network is sufficiently diverse for further development
  148. and testing; but of course we always encourage and welcome new nodes
  149. to join the network.
  150. Tor research and development has been funded by the U.S.~Navy and DARPA
  151. for use in securing government
  152. communications, and by the Electronic Frontier Foundation, for use
  153. in maintaining civil liberties for ordinary citizens online. The Tor
  154. protocol is one of the leading choices
  155. to be the anonymizing layer in the European Union's PRIME directive to
  156. help maintain privacy in Europe. The University of Dresden in Germany
  157. has integrated an independent implementation of the Tor protocol into
  158. their popular Java Anon Proxy anonymizing client.
  159. % This wide variety of
  160. %interests helps maintain both the stability and the security of the
  161. %network.
  162. \medskip
  163. \noindent
  164. {\bf Threat models and design philosophy.}
  165. The ideal Tor network would be practical, useful and and anonymous. When
  166. trade-offs arise between these properties, Tor's research strategy has been
  167. to insist on remaining useful enough to attract many users,
  168. and practical enough to support them. Only subject to these
  169. constraints do we aim to maximize
  170. anonymity.\footnote{This is not the only possible
  171. direction in anonymity research: designs exist that provide more anonymity
  172. than Tor at the expense of significantly increased resource requirements, or
  173. decreased flexibility in application support (typically because of increased
  174. latency). Such research does not typically abandon aspirations towards
  175. deployability or utility, but instead tries to maximize deployability and
  176. utility subject to a certain degree of inherent anonymity (inherent because
  177. usability and practicality affect usage which affects the actual anonymity
  178. provided by the network \cite{econymics,back01}).}
  179. %{We believe that these
  180. %approaches can be promising and useful, but that by focusing on deploying a
  181. %usable system in the wild, Tor helps us experiment with the actual parameters
  182. %of what makes a system ``practical'' for volunteer operators and ``useful''
  183. %for home users, and helps illuminate undernoticed issues which any deployed
  184. %volunteer anonymity network will need to address.}
  185. Because of this strategy, Tor has a weaker threat model than many anonymity
  186. designs in the literature. In particular, because we
  187. support interactive communications without impractically expensive padding,
  188. we fall prey to a variety
  189. of intra-network~\cite{back01,attack-tor-oak05,flow-correlation04} and
  190. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  191. Tor does not attempt to defend against a global observer. In general, an
  192. attacker who can observe both ends of a connection through the Tor network
  193. can correlate the timing and volume of data on that connection as it enters
  194. and leaves the network, and so link a user to her chosen communication
  195. parties. Known solutions to this attack would seem to require introducing a
  196. prohibitive degree of traffic padding between the user and the network, or
  197. introducing an unacceptable degree of latency (but see Section
  198. \ref{subsec:mid-latency}). Also, it is not clear that these methods would
  199. work at all against even a minimally active adversary that can introduce timing
  200. patterns or additional traffic. Thus, Tor only attempts to defend against
  201. external observers who cannot observe both sides of a user's connection.
  202. The distinction between traffic correlation and traffic analysis is
  203. not as cut and dried as we might wish. In \cite{hintz-pet02} it was
  204. shown that if data volumes of various popular
  205. responder destinations are catalogued, it may not be necessary to
  206. observe both ends of a stream to learn a source-destination link.
  207. This should be fairly effective without simultaneously observing both
  208. ends of the connection. However, it is still essentially confirming
  209. suspected communicants where the responder suspects are ``stored'' rather
  210. than observed at the same time as the client.
  211. Similarly latencies of going through various routes can be
  212. catalogued~\cite{back01} to connect endpoints.
  213. This is likely to entail high variability and massive storage since
  214. % XXX hintz-pet02 just looked at data volumes of the sites. this
  215. % doesn't require much variability or storage. I think it works
  216. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  217. % attack another level further, to narrow down where you could be
  218. % based on an intersection attack on subpages in a website. -RD
  219. %
  220. % I was trying to be terse and simultaneously referring to both the
  221. % Hintz stuff and the Back et al. stuff from Info Hiding 01. I've
  222. % separated the two and added the references. -PFS
  223. routes through the network to each site will be random even if they
  224. have relatively unique latency characteristics. So this does not seem
  225. an immediate practical threat. Further along similar lines, the same
  226. paper suggested a ``clogging attack''. In \cite{attack-tor-oak05}, a
  227. version of this was demonstrated to be practical against portions of
  228. the fifty node Tor network as deployed in mid 2004. There it was shown
  229. that an outside attacker can trace a stream through the Tor network
  230. while a stream is still active simply by observing the latency of his
  231. own traffic sent through various Tor nodes. These attacks do not show
  232. the client address, only the first node within the Tor network, making
  233. helper nodes all the more worthy of exploration (cf.,
  234. Section~\ref{subsec:helper-nodes}).
  235. Against internal attackers who sign up Tor nodes, the situation is more
  236. complicated. In the simplest case, if an adversary has compromised $c$ of
  237. $n$ nodes on the Tor network, then the adversary will be able to compromise
  238. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  239. initiator chooses hops randomly). But there are
  240. complicating factors:
  241. (1)~If the user continues to build random circuits over time, an adversary
  242. is pretty certain to see a statistical sample of the user's traffic, and
  243. thereby can build an increasingly accurate profile of her behavior. (See
  244. Section~\ref{subsec:helper-nodes} for possible solutions.)
  245. (2)~An adversary who controls a popular service outside of the Tor network
  246. can be certain of observing all connections to that service; he
  247. therefore will trace connections to that service with probability
  248. $\frac{c}{n}$.
  249. (3)~Users do not in fact choose nodes with uniform probability; they
  250. favor nodes with high bandwidth or uptime, and exit nodes that
  251. permit connections to their favorite services.
  252. See Section~\ref{subsec:routing-zones} for discussion of larger
  253. adversaries and our dispersal goals.
  254. %\begin{tightlist}
  255. %\item If the user continues to build random circuits over time, an adversary
  256. % is pretty certain to see a statistical sample of the user's traffic, and
  257. % thereby can build an increasingly accurate profile of her behavior. (See
  258. % \ref{subsec:helper-nodes} for possible solutions.)
  259. %\item An adversary who controls a popular service outside of the Tor network
  260. % can be certain of observing all connections to that service; he
  261. % therefore will trace connections to that service with probability
  262. % $\frac{c}{n}$.
  263. %\item Users do not in fact choose nodes with uniform probability; they
  264. % favor nodes with high bandwidth or uptime, and exit nodes that
  265. % permit connections to their favorite services.
  266. %\end{tightlist}
  267. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  268. %the last hop is not $c/n$ since that doesn't take the destination (website)
  269. %into account. so in cases where the adversary does not also control the
  270. %final destination we're in good shape, but if he *does* then we'd be better
  271. %off with a system that lets each hop choose a path.
  272. %
  273. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  274. % dest, we would be just as well off with such as system.'' ? If not, why
  275. % not? -nm
  276. % Sure. In fact, better off, since they seem to scale more easily. -rd
  277. % XXXX the below paragraph should probably move later, and merge with
  278. % other discussions of attack-tor-oak5.
  279. %Murdoch and Danezis describe an attack
  280. %\cite{attack-tor-oak05} that lets an attacker determine the nodes used
  281. %in a circuit; yet s/he cannot identify the initiator or responder,
  282. %e.g., client or web server, through this attack. So the endpoints
  283. %remain secure, which is the goal. It is conceivable that an
  284. %adversary could attack or set up observation of all connections
  285. %to an arbitrary Tor node in only a few minutes. If such an adversary
  286. %were to exist, s/he could use this probing to remotely identify a node
  287. %for further attack. Of more likely immediate practical concern
  288. %an adversary with active access to the responder traffic
  289. %wants to keep a circuit alive long enough to attack an identified
  290. %node. Thus it is important to prevent the responding end of the circuit
  291. %from keeping it open indefinitely.
  292. %Also, someone could identify nodes in this way and if in their
  293. %jurisdiction, immediately get a subpoena (if they even need one)
  294. %telling the node operator(s) that she must retain all the active
  295. %circuit data she now has.
  296. %Further, the enclave model, which had previously looked to be the most
  297. %generally secure, seems particularly threatened by this attack, since
  298. %it identifies endpoints when they're also nodes in the Tor network:
  299. %see Section~\ref{subsec:helper-nodes} for discussion of some ways to
  300. %address this issue.
  301. \medskip
  302. \noindent
  303. {\bf Distributed trust.}
  304. In practice Tor's threat model is based entirely on the goal of
  305. dispersal and diversity.
  306. Tor's defense lies in having a diverse enough set of nodes
  307. to prevent most real-world
  308. adversaries from being in the right places to attack users.
  309. Tor aims to resist observers and insiders by distributing each transaction
  310. over several nodes in the network. This ``distributed trust'' approach
  311. means the Tor network can be safely operated and used by a wide variety
  312. of mutually distrustful users, providing more sustainability and security
  313. than some previous attempts at anonymizing networks.
  314. The Tor network has a broad range of users, including ordinary citizens
  315. concerned about their privacy, corporations
  316. who don't want to reveal information to their competitors, and law
  317. enforcement and government intelligence agencies who need
  318. to do operations on the Internet without being noticed.
  319. No organization can achieve this security on its own. If a single
  320. corporation or government agency were to build a private network to
  321. protect its operations, any connections entering or leaving that network
  322. would be obviously linkable to the controlling organization. The members
  323. and operations of that agency would be easier, not harder, to distinguish.
  324. Instead, to protect our networks from traffic analysis, we must
  325. collaboratively blend the traffic from many organizations and private
  326. citizens, so that an eavesdropper can't tell which users are which,
  327. and who is looking for what information. By bringing more users onto
  328. the network, all users become more secure~\cite{econymics}.
  329. [XXX I feel uncomfortable saying this last sentence now. -RD]
  330. Naturally, organizations will not want to depend on others for their
  331. security. If most participating providers are reliable, Tor tolerates
  332. some hostile infiltration of the network. For maximum protection,
  333. the Tor design includes an enclave approach that lets data be encrypted
  334. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  335. hasn't been read or modified. This even works for Internet services that
  336. don't have built-in encryption and authentication, such as unencrypted
  337. HTTP or chat, and it requires no modification of those services.
  338. \subsection{Related work}
  339. Tor is not the only anonymity system that aims to be practical and useful.
  340. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  341. open proxies around the Internet, can provide good
  342. performance and some security against a weaker attacker. The Java
  343. Anon Proxy~\cite{web-mix} provides similar functionality to Tor but only
  344. handles web browsing rather than arbitrary TCP\@.
  345. %Some peer-to-peer file-sharing overlay networks such as
  346. %Freenet~\cite{freenet} and Mute~\cite{mute}
  347. Zero-Knowledge Systems' commercial Freedom
  348. network~\cite{freedom21-security} was even more flexible than Tor in
  349. that it could transport arbitrary IP packets, and it also supported
  350. pseudonymous access rather than just anonymous access; but it had
  351. a different approach to sustainability (collecting money from users
  352. and paying ISPs to run Tor nodes), and was shut down due to financial
  353. load. Finally, potentially
  354. more scalable designs like Tarzan~\cite{tarzan:ccs02} and
  355. MorphMix~\cite{morphmix:fc04} have been proposed in the literature, but
  356. have not yet been fielded. All of these systems differ somewhat
  357. in threat model and presumably practical resistance to threats.
  358. Morphmix is very close to Tor in circuit setup. And, by separating
  359. node discovery from route selection from circuit setup, Tor is
  360. flexible enough to potentially contain a Morphmix experiment within
  361. it. We direct the interested reader to Section
  362. 2 of~\cite{tor-design} for a more in-depth review of related work.
  363. Tor differs from other deployed systems for traffic analysis resistance
  364. in its security and flexibility. Mix networks such as
  365. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  366. gain the highest degrees of anonymity at the expense of introducing highly
  367. variable delays, thus making them unsuitable for applications such as web
  368. browsing. Commercial single-hop
  369. proxies~\cite{anonymizer} present a single point of failure, where
  370. a single compromise can expose all users' traffic, and a single-point
  371. eavesdropper can perform traffic analysis on the entire network.
  372. Also, their proprietary implementations place any infrastucture that
  373. depends on these single-hop solutions at the mercy of their providers'
  374. financial health as well as network security.
  375. %XXXX six-four. crowds. i2p.
  376. %XXXX
  377. %have a serious discussion of morphmix's assumptions, since they would
  378. %seem to be the direct competition. in fact tor is a flexible architecture
  379. %that would encompass morphmix, and they're nearly identical except for
  380. %path selection and node discovery. and the trust system morphmix has
  381. %seems overkill (and/or insecure) based on the threat model we've picked.
  382. % this para should probably move to the scalability / directory system. -RD
  383. % Nope. Cut for space, except for small comment added above -PFS
  384. \section{Social challenges}
  385. Many of the issues the Tor project needs to address extend beyond
  386. system design and technology development. In particular, the
  387. Tor project's \emph{image} with respect to its users and the rest of
  388. the Internet impacts the security it can provide.
  389. % No image, no sustainability -NM
  390. With this image issue in mind, this section discusses the Tor user base and
  391. Tor's interaction with other services on the Internet.
  392. \subsection{Communicating security}
  393. A growing field of papers argue that usability for anonymity systems
  394. contributes directly to their security, because how usable the system
  395. is impacts the possible anonymity set~\cite{econymics,back01}. Or
  396. conversely, an unusable system attracts few users and thus can't provide
  397. much anonymity.
  398. This phenomenon has a second-order effect: knowing this, users should
  399. choose which anonymity system to use based in part on how usable
  400. \emph{others} will find it, in order to get the protection of a larger
  401. anonymity set. Thus we might replace the adage ``usability is a security
  402. parameter''~\cite{back01} with a new one: ``perceived usability is a
  403. security parameter.'' From here we can better understand the effects
  404. of publicity and advertising on security: the more convincing your
  405. advertising, the more likely people will believe you have users, and thus
  406. the more users you will attract. Perversely, over-hyped systems (if they
  407. are not too broken) may be a better choice than modestly promoted ones,
  408. if the hype attracts more users~\cite{usability-network-effect}.
  409. So it follows that we should come up with ways to accurately communicate
  410. the available security levels to the user, so she can make informed
  411. decisions. JAP aims to do this by including a
  412. comforting `anonymity meter' dial in the software's graphical interface,
  413. giving the user an impression of the level of protection for her current
  414. traffic.
  415. However, there's a catch. For users to share the same anonymity set,
  416. they need to act like each other. An attacker who can distinguish
  417. a given user's traffic from the rest of the traffic will not be
  418. distracted by anonymity set size. For high-latency systems like
  419. Mixminion, where the threat model is based on mixing messages with each
  420. other, there's an arms race between end-to-end statistical attacks and
  421. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  422. But for low-latency systems like Tor, end-to-end \emph{traffic
  423. correlation} attacks~\cite{danezis-pet2004,defensive-dropping,SS03}
  424. allow an attacker who can measure both ends of a communication
  425. to match packet timing and volume, quickly linking
  426. the initiator to her destination. This is why Tor's threat model is
  427. based on preventing the adversary from observing both the initiator and
  428. the responder.
  429. Like Tor, the current JAP implementation does not pad connections
  430. (apart from using small fixed-size cells for transport). In fact,
  431. JAP's cascade-based network topology may be even more vulnerable to these
  432. attacks, because the network has fewer edges. JAP was born out of
  433. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  434. every user had a fixed bandwidth allocation, but in its current context
  435. as a general Internet web anonymizer, adding sufficient padding to JAP
  436. would be prohibitively expensive.\footnote{Even if JAP could
  437. fund higher-capacity nodes indefinitely, our experience
  438. suggests that many users would not accept the increased per-user
  439. bandwidth requirements, leading to an overall much smaller user base. But
  440. cf.\ Section \ref{subsec:mid-latency}.} Therefore, since under this threat
  441. model the number of concurrent users does not seem to have much impact
  442. on the anonymity provided, we suggest that JAP's anonymity meter is not
  443. accurately communicating security levels to its users.
  444. % because more users don't help anonymity much, we need to rely more
  445. % on other incentive schemes, both policy-based (see sec x) and
  446. % technically enforced (see sec y)
  447. On the other hand, while the number of active concurrent users may not
  448. matter as much as we'd like, it still helps to have some other users
  449. on the network. We investigate this issue next.
  450. \subsection{Reputability and perceived social value}
  451. Another factor impacting the network's security is its reputability:
  452. the perception of its social value based on its current user base. If Alice is
  453. the only user who has ever downloaded the software, it might be socially
  454. accepted, but she's not getting much anonymity. Add a thousand animal rights
  455. activists, and she's anonymous, but everyone thinks she's a Bambi lover (or
  456. NRA member if you prefer a contrasting example). Add a thousand
  457. diverse citizens (cancer survivors, privacy enthusiasts, and so on)
  458. and now she's harder to profile.
  459. Furthermore, the network's reputability affects its node base: more people
  460. are willing to run a service if they believe it will be used by human rights
  461. workers than if they believe it will be used exclusively for disreputable
  462. ends. This effect becomes stronger if node operators themselves think they
  463. will be associated with these disreputable ends.
  464. So the more cancer survivors on Tor, the better for the human rights
  465. activists. The more malicious hackers, the worse for the normal users. Thus,
  466. reputability is an anonymity issue for two reasons. First, it impacts
  467. the sustainability of the network: a network that's always about to be
  468. shut down has difficulty attracting and keeping adquate nodes.
  469. Second, a disreputable network is more vulnerable to legal and
  470. political attacks, since it will attract fewer supporters.
  471. While people therefore have an incentive for the network to be used for
  472. ``more reputable'' activities than their own, there are still tradeoffs
  473. involved when it comes to anonymity. To follow the above example, a
  474. network used entirely by cancer survivors might welcome some NRA members
  475. onto the network, though of course they'd prefer a wider
  476. variety of users.
  477. Reputability becomes even more tricky in the case of privacy networks,
  478. since the good uses of the network (such as publishing by journalists in
  479. dangerous countries) are typically kept private, whereas network abuses
  480. or other problems tend to be more widely publicized.
  481. The impact of public perception on security is especially important
  482. during the bootstrapping phase of the network, where the first few
  483. widely publicized uses of the network can dictate the types of users it
  484. attracts next.
  485. As an example, some U.S.~Department of Energy
  486. penetration testing engineers are tasked with compromising DoE computers
  487. from the outside. They only have a limited number of ISPs from which to
  488. launch their attacks, and they found that the defenders were recognizing
  489. attacks because they came from the same IP space. These engineers wanted
  490. to use Tor to hide their tracks. First, from a technical standpoint,
  491. Tor does not support the variety of IP packets one would like to use in
  492. such attacks (see Section~\ref{subsec:tcp-vs-ip}). But aside from this,
  493. we also decided that it would probably be poor precedent to encourage
  494. such use---even legal use that improves national security---and managed
  495. to dissuade them.
  496. %% "outside of academia, jap has just lost, permanently". (That is,
  497. %% even though the crime detection issues are resolved and are unlikely
  498. %% to go down the same way again, public perception has not been kind.)
  499. \subsection{Sustainability and incentives}
  500. One of the unsolved problems in low-latency anonymity designs is
  501. how to keep the nodes running. Zero-Knowledge Systems's Freedom network
  502. depended on paying third parties to run its servers; the JAP project's
  503. bandwidth depends on grants to pay for its bandwidth and
  504. administrative expenses. In Tor, bandwidth and administrative costs are
  505. distributed across the volunteers who run Tor nodes, so we at least have
  506. reason to think that the Tor network could survive without continued research
  507. funding.\footnote{It also helps that Tor is implemented with free and open
  508. source software that can be maintained by anybody with the ability and
  509. inclination.} But why are these volunteers running nodes, and what can we
  510. do to encourage more volunteers to do so?
  511. We have not formally surveyed Tor node operators to learn why they are
  512. running nodes, but
  513. from the information they have provided, it seems that many of them run Tor
  514. nodes for reasons of personal interest in privacy issues. It is possible
  515. that others are running Tor for their own
  516. anonymity reasons, but of course they are
  517. hardly likely to tell us specifics if they are.
  518. %Significantly, Tor's threat model changes the anonymity incentives for running
  519. %a node. In a high-latency mix network, users can receive additional
  520. %anonymity by running their own node, since doing so obscures when they are
  521. %injecting messages into the network. But, anybody observing all I/O to a Tor
  522. %node can tell when the node is generating traffic that corresponds to
  523. %none of its incoming traffic.
  524. %
  525. %I didn't buy the above for reason's subtle enough that I just cut it -PFS
  526. Tor exit node operators do attain a degree of
  527. ``deniability'' for traffic that originates at that exit node. For
  528. example, it is likely in practice that HTTP requests from a Tor node's IP
  529. will be assumed to be from the Tor network.
  530. More significantly, people and organizations who use Tor for
  531. anonymity depend on the
  532. continued existence of the Tor network to do so; running a node helps to
  533. keep the network operational.
  534. %\item Local Tor entry and exit nodes allow users on a network to run in an
  535. % `enclave' configuration. [XXXX need to resolve this. They would do this
  536. % for E2E encryption + auth?]
  537. %We must try to make the costs of running a Tor node easily minimized.
  538. Since Tor is run by volunteers, the most crucial software usability issue is
  539. usability by operators: when an operator leaves, the network becomes less
  540. usable by everybody. To keep operators pleased, we must try to keep Tor's
  541. resource and administrative demands as low as possible.
  542. Because of ISP billing structures, many Tor operators have underused capacity
  543. that they are willing to donate to the network, at no additional monetary
  544. cost to them. Features to limit bandwidth have been essential to adoption.
  545. Also useful has been a ``hibernation'' feature that allows a Tor node that
  546. wants to provide high bandwidth, but no more than a certain amount in a
  547. giving billing cycle, to become dormant once its bandwidth is exhausted, and
  548. to reawaken at a random offset into the next billing cycle. This feature has
  549. interesting policy implications, however; see
  550. Section~\ref{subsec:bandwidth-and-file-sharing} below.
  551. Exit policies help to limit administrative costs by limiting the frequency of
  552. abuse complaints.
  553. %[XXXX say more. Why else would you run a node? What else can we do/do we
  554. % already do to make running a node more attractive?]
  555. %[We can enforce incentives; see Section 6.1. We can rate-limit clients.
  556. % We can put "top bandwidth nodes lists" up a la seti@home.]
  557. \subsection{Bandwidth and file-sharing}
  558. \label{subsec:bandwidth-and-file-sharing}
  559. %One potentially problematical area with deploying Tor has been our response
  560. %to file-sharing applications.
  561. Once users have configured their applications to work with Tor, the largest
  562. remaining usability issue is performance. Users begin to suffer
  563. when websites ``feel slow''.
  564. Clients currently try to build their connections through nodes that they
  565. guess will have enough bandwidth. But even if capacity is allocated
  566. optimally, it seems unlikely that the current network architecture will have
  567. enough capacity to provide every user with as much bandwidth as she would
  568. receive if she weren't using Tor, unless far more nodes join the network
  569. (see above).
  570. %Limited capacity does not destroy the network, however. Instead, usage tends
  571. %towards an equilibrium: when performance suffers, users who value performance
  572. %over anonymity tend to leave the system, thus freeing capacity until the
  573. %remaining users on the network are exactly those willing to use that capacity
  574. %there is.
  575. Much of Tor's recent bandwidth difficulties have come from file-sharing
  576. applications. These applications provide two challenges to
  577. any anonymizing network: their intensive bandwidth requirement, and the
  578. degree to which they are associated (correctly or not) with copyright
  579. violation.
  580. As noted above, high-bandwidth protocols can make the network unresponsive,
  581. but tend to be somewhat self-correcting. Issues of copyright violation,
  582. however, are more interesting. Typical exit node operators want to help
  583. people achieve private and anonymous speech, not to help people (say) host
  584. Vin Diesel movies for download; and typical ISPs would rather not
  585. deal with customers who incur them the overhead of getting menacing letters
  586. from the MPAA\@. While it is quite likely that the operators are doing nothing
  587. illegal, many ISPs have policies of dropping users who get repeated legal
  588. threats regardless of the merits of those threats, and many operators would
  589. prefer to avoid receiving legal threats even if those threats have little
  590. merit. So when the letters arrive, operators are likely to face
  591. pressure to block file-sharing applications entirely, in order to avoid the
  592. hassle.
  593. But blocking file-sharing would not necessarily be easy; most popular
  594. protocols have evolved to run on a variety of non-standard ports in order to
  595. get around other port-based bans. Thus, exit node operators who wanted to
  596. block file-sharing would have to find some way to integrate Tor with a
  597. protocol-aware exit filter. This could be a technically expensive
  598. undertaking, and one with poor prospects: it is unlikely that Tor exit nodes
  599. would succeed where so many institutional firewalls have failed. Another
  600. possibility for sensitive operators is to run a restrictive node that
  601. only permits exit connections to a restricted range of ports which are
  602. not frequently associated with file sharing. There are increasingly few such
  603. ports.
  604. Other possible approaches might include rate-limiting connections, especially
  605. long-lived connections or connections to file-sharing ports, so that
  606. high-bandwidth connections do not flood the network. We might also want to
  607. give priority to cells on low-bandwidth connections to keep them interactive,
  608. but this could have negative anonymity implications.
  609. For the moment, it seems that Tor's bandwidth issues have rendered it
  610. unattractive for bulk file-sharing traffic; this may continue to be so in the
  611. future. Nevertheless, Tor will likely remain attractive for limited use in
  612. file-sharing protocols that have separate control and data channels.
  613. %[We should say more -- but what? That we'll see a similar
  614. % equilibriating effect as with bandwidth, where sensitive ops switch to
  615. % middleman, and we become less useful for file-sharing, so the file-sharing
  616. % people back off, so we get more ops since there's less file-sharing, so the
  617. % file-sharers come back, etc.]
  618. %XXXX
  619. %in practice, plausible deniability is hypothetical and doesn't seem very
  620. %convincing. if ISPs find the activity antisocial, they don't care *why*
  621. %your computer is doing that behavior.
  622. \subsection{Tor and blacklists}
  623. It was long expected that, alongside Tor's legitimate users, it would also
  624. attract troublemakers who exploited Tor in order to abuse services on the
  625. Internet with vandalism, rude mail, and so on.
  626. %[XXX we're not talking bandwidth abuse here, we're talking vandalism,
  627. %hate mails via hotmail, attacks, etc.]
  628. Our initial answer to this situation was to use ``exit policies''
  629. to allow individual Tor nodes to block access to specific IP/port ranges.
  630. This approach aims to make operators more willing to run Tor by allowing
  631. them to prevent their nodes from being used for abusing particular
  632. services. For example, all Tor nodes currently block SMTP (port 25), in
  633. order to avoid being used to send spam.
  634. This approach is useful, but is insufficient for two reasons. First, since
  635. it is not possible to force all nodes to block access to any given service,
  636. many of those services try to block Tor instead. More broadly, while being
  637. blockable is important to being good netizens, we would like to encourage
  638. services to allow anonymous access; services should not need to decide
  639. between blocking legitimate anonymous use and allowing unlimited abuse.
  640. This is potentially a bigger problem than it may appear.
  641. On the one hand, if people want to refuse connections from your address to
  642. their servers it would seem that they should be allowed. But, it's not just
  643. for himself that the individual node administrator is deciding when he decides
  644. if he wants to post to Wikipedia from his Tor node address or allow
  645. people to read Wikipedia anonymously through his Tor node. (Wikipedia
  646. has blocked all posting from all Tor nodes based on IP address.) If e.g.,
  647. s/he comes through a campus or corporate NAT, then the decision must
  648. be to have the entire population behind it able to have a Tor exit
  649. node or to have write access to Wikipedia. This is a loss for both Tor
  650. and Wikipedia. We don't want to compete for (or divvy up) the NAT
  651. protected entities of the world.
  652. Worse, many IP blacklists are not terribly fine-grained.
  653. No current IP blacklist, for example, allow a service provider to blacklist
  654. only those Tor nodes that allow access to a specific IP or port, even
  655. though this information is readily available. One IP blacklist even bans
  656. every class C network that contains a Tor node, and recommends banning SMTP
  657. from these networks even though Tor does not allow SMTP at all. This
  658. coarse-grained approach is typically a strategic decision to discourage the
  659. operation of anything resembling an open proxy by encouraging its neighbors
  660. to shut it down in order to get unblocked themselves.
  661. %[****Since this is stupid and we oppose it, shouldn't we name names here -pfs]
  662. %[XXX also, they're making \emph{middleman nodes leave} because they're caught
  663. % up in the standoff!]
  664. %[XXX Mention: it's not dumb, it's strategic!]
  665. %[XXX Mention: for some servops, any blacklist is a blacklist too many,
  666. % because it is risky. (Guy lives in apt _building_ with one IP.)]
  667. Problems of abuse occur mainly with services such as IRC networks and
  668. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  669. blush this practice might seem to depend on the anachronistic assumption that
  670. each IP is an identifier for a single user, it is actually more reasonable in
  671. practice: it assumes that non-proxy IPs are a costly resource, and that an
  672. abuser can not change IPs at will. By blocking IPs which are used by Tor
  673. nodes, open proxies, and service abusers, these systems hope to make
  674. ongoing abuse difficult. Although the system is imperfect, it works
  675. tolerably well for them in practice.
  676. But of course, we would prefer that legitimate anonymous users be able to
  677. access abuse-prone services. One conceivable approach would be to require
  678. would-be IRC users, for instance, to register accounts if they wanted to
  679. access the IRC network from Tor. But in practise, this would not
  680. significantly impede abuse if creating new accounts were easily automatable;
  681. this is why services use IP blocking. In order to deter abuse, pseudonymous
  682. identities need to require a significant switching cost in resources or human
  683. time.
  684. % XXX Mention captchas?
  685. %One approach, similar to that taken by Freedom, would be to bootstrap some
  686. %non-anonymous costly identification mechanism to allow access to a
  687. %blind-signature pseudonym protocol. This would effectively create costly
  688. %pseudonyms, which services could require in order to allow anonymous access.
  689. %This approach has difficulties in practise, however:
  690. %\begin{tightlist}
  691. %\item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  692. % be a shame to require payment in order to make Tor useful, or to make
  693. % non-paying users second-class citizens.
  694. %\item It is hard to think of an underlying resource that would actually work.
  695. % We could use IP addresses, but that's the problem, isn't it?
  696. %\item Managing single sign-on services is not considered a well-solved
  697. % problem in practice. If Microsoft can't get universal acceptance for
  698. % Passport, why do we think that a Tor-specific solution would do any good?
  699. %\item Even if we came up with a perfect authentication system for our needs,
  700. % there's no guarantee that any service would actually start using it. It
  701. % would require a nonzero effort for them to support it, and it might just
  702. % be less hassle for them to block tor anyway.
  703. %\end{tightlist}
  704. %The use of squishy IP-based ``authentication'' and ``authorization''
  705. %has not broken down even to the level that SSNs used for these
  706. %purposes have in commercial and public record contexts. Externalities
  707. %and misplaced incentives cause a continued focus on fighting identity
  708. %theft by protecting SSNs rather than developing better authentication
  709. %and incentive schemes \cite{price-privacy}. Similarly we can expect a
  710. %continued use of identification by IP number as long as there is no
  711. %workable alternative.
  712. %[XXX Mention correct DNS-RBL implementation. -NM]
  713. \section{Design choices}
  714. In addition to social issues, Tor also faces some design tradeoffs that must
  715. be investigated as the network develops.
  716. \subsection{Transporting the stream vs transporting the packets}
  717. \label{subsec:stream-vs-packet}
  718. \label{subsec:tcp-vs-ip}
  719. Tor transports streams; it does not tunnel packets.
  720. Developers of the old Freedom network~\cite{freedom21-security}
  721. keep telling us that IP addresses should ``obviously'' be anonymized
  722. at the IP layer. These issues need to be resolved before
  723. Tor will be ready to carry arbitrary IP traffic:
  724. \begin{enumerate}
  725. \setlength{\itemsep}{0mm}
  726. \setlength{\parsep}{0mm}
  727. \item \emph{IP packets reveal OS characteristics.} We still need to do
  728. IP-level packet normalization, to stop things like IP fingerprinting
  729. attacks. There likely exist libraries that can help with this.
  730. \item \emph{Application-level streams still need scrubbing.} We still need
  731. Tor to be easy to integrate with user-level application-specific proxies
  732. such as Privoxy. So it's not just a matter of capturing packets and
  733. anonymizing them at the IP layer.
  734. \item \emph{Certain protocols will still leak information.} For example,
  735. we must rewrite DNS requests so they are
  736. delivered to an unlinkable DNS server; so we must
  737. understand the protocols we are transporting.
  738. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  739. approach that can provide security despite
  740. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  741. never publicly specified.
  742. Also, TLS over UDP is not implemented or even
  743. specified, though some early work has begun on that~\cite{dtls}.
  744. \item \emph{We'll still need to tune network parameters}. Since the above
  745. encryption system will likely need sequence numbers (and maybe more) to do
  746. replay detection, handle duplicate frames, etc., we will be reimplementing
  747. a subset of TCP anyway.
  748. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  749. IDS\@.} Our node operators tell us that exit policies are one of
  750. the main reasons they're willing to run Tor.
  751. Adding an Intrusion Detection System to handle exit policies would
  752. increase the security complexity of Tor, and would likely not work anyway,
  753. as evidenced by the entire field of IDS and counter-IDS papers. Many
  754. potential abuse issues are resolved by the fact that Tor only transports
  755. valid TCP streams (as opposed to arbitrary IP including malformed packets
  756. and IP floods), so exit policies become even \emph{more} important as
  757. we become able to transport IP packets. We also need to compactly
  758. describe exit policies so clients can predict
  759. which nodes will allow which packets to exit.
  760. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  761. support hidden service {\tt{.onion}} addresses, and other special addresses
  762. like {\tt{.exit}} for the user to request a particular exit node,
  763. by intercepting the addresses when they are passed to the Tor client.
  764. \end{enumerate}
  765. This list is discouragingly long, but being able to transport more
  766. protocols obviously has some advantages. It would be good to learn which
  767. items are actual roadblocks and which are easier to resolve than we think.
  768. To be fair, Tor's stream-based approach has run into
  769. stumbling blocks as well. While Tor supports the SOCKS protocol,
  770. which provides a standardized interface for generic TCP proxies, many
  771. applications do not support SOCKS\@. For them we must
  772. replace the networking system calls with SOCKS-aware
  773. versions, or run a SOCKS tunnel locally, neither of which is
  774. easy for the average user. %---even with good instructions.
  775. Even when applications do use SOCKS, they often make DNS requests
  776. themselves before handing the address to Tor, which advertises
  777. where the user is about to connect.
  778. We are still working on usable solutions.
  779. %So in order to actually provide good anonymity, we need to make sure that
  780. %users have a practical way to use Tor anonymously. Possibilities include
  781. %writing wrappers for applications to anonymize them automatically; improving
  782. %the applications' support for SOCKS; writing libraries to help application
  783. %writers use Tor properly; and implementing a local DNS proxy to reroute DNS
  784. %requests to Tor so that applications can simply point their DNS resolvers at
  785. %localhost and continue to use SOCKS for data only.
  786. \subsection{Mid-latency}
  787. \label{subsec:mid-latency}
  788. Some users need to resist traffic correlation attacks. Higher-latency
  789. mix-networks introduce variability into message
  790. arrival times: as timing variance increases, timing correlation attacks
  791. require increasingly more data~\cite{e2e-traffic}. Can we improve Tor's
  792. resistance without losing too much usability?
  793. We need to learn whether we can trade a small increase in latency
  794. for a large anonymity increase, or if we'll end up trading a lot of
  795. latency for a small security gain. A trade could be worthwhile even if we
  796. can only protect certain use cases, such as infrequent short-duration
  797. transactions. % To answer this question
  798. We might adapt the techniques of~\cite{e2e-traffic} to a lower-latency mix
  799. network, where the messages are batches of cells in temporally clustered
  800. connections. These large fixed-size batches can also help resist volume
  801. signature attacks~\cite{hintz-pet02}. We can also experiment with traffic
  802. shaping to get a good balance of throughput and security.
  803. %Other padding regimens might supplement the
  804. %mid-latency option; however, we should continue the caution with which
  805. %we have always approached padding lest the overhead cost us too much
  806. %performance or too many volunteers.
  807. We must keep usability in mind too. How much can latency increase
  808. before we drive away our users? We're already being forced to increase
  809. latency slightly, as our growing network incorporates more DSL and
  810. cable-modem nodes and more nodes in distant continents. Perhaps we can
  811. harness this increased latency to improve anonymity rather than just
  812. reduce usability. Further, if we let clients label certain circuits as
  813. mid-latency as they are constructed, we could handle both types of traffic
  814. on the same network, giving users a choice between speed and security.
  815. \subsection{Enclaves and helper nodes}
  816. \label{subsec:helper-nodes}
  817. It has long been thought that the best anonymity comes from running your
  818. own node~\cite{tor-design,or-pet00}. This is called using Tor in an
  819. \emph{enclave} configuration. Of course, Tor's default path length of
  820. three is insufficient for these enclaves, since the entry and/or exit
  821. themselves are sensitive. Tor thus increments the path length by one
  822. for each sensitive endpoint in the circuit.
  823. Enclaves also help to protect against end-to-end attacks, since it's
  824. possible that traffic coming from the node has simply been relayed from
  825. elsewhere. However, if the node has recognizable behavior patterns,
  826. an attacker who runs nodes in the network can triangulate over time to
  827. gain confidence that it is in fact originating the traffic. Wright et
  828. al.~\cite{wright03} introduce the notion of a \emph{helper node}---a
  829. single fixed entry node for each user---to combat this \emph{predecessor
  830. attack}.
  831. However, the attack in~\cite{attack-tor-oak05} shows that simply adding
  832. to the path length, or using a helper node, may not protect an enclave
  833. node. A hostile web server can send constant interference traffic to
  834. all nodes in the network, and learn which nodes are involved in the
  835. circuit (though at least in the current attack, he can't learn their
  836. order). Using randomized path lengths may help some, since the attacker
  837. will never be certain he has identified all nodes in the path, but as
  838. long as the network remains small this attack will still be feasible.
  839. Helper nodes also aim to help Tor clients, because choosing entry and exit points
  840. randomly and changing them frequently allows an attacker who controls
  841. even a few nodes to eventually link some of their destinations. The goal
  842. is to take the risk once and for all about choosing a bad entry node,
  843. rather than taking a new risk for each new circuit. (Choosing fixed
  844. exit nodes is less useful, since even an honest exit node still doesn't
  845. protect against a hostile website.) But obstacles still remain before
  846. we can implement them.
  847. For one, the literature does not describe how to choose helpers from a list
  848. of nodes that changes over time. If Alice is forced to choose a new entry
  849. helper every $d$ days and $c$ of the $n$ nodes are bad, she can expect
  850. to choose a compromised node around
  851. every $dc/n$ days. Statistically over time this approach only helps
  852. if she is better at choosing honest helper nodes than at choosing
  853. honest nodes. Worse, an attacker with the ability to DoS nodes could
  854. force users to switch helper nodes more frequently and/or remove
  855. other candidate helpers.
  856. %Do general DoS attacks have anonymity implications? See e.g. Adam
  857. %Back's IH paper, but I think there's more to be pointed out here. -RD
  858. % Not sure what you want to say here. -NM
  859. %Game theory for helper nodes: if Alice offers a hidden service on a
  860. %server (enclave model), and nobody ever uses helper nodes, then against
  861. %George+Steven's attack she's totally nailed. If only Alice uses a helper
  862. %node, then she's still identified as the source of the data. If everybody
  863. %uses a helper node (including Alice), then the attack identifies the
  864. %helper node and also Alice, and knows which one is which. If everybody
  865. %uses a helper node (but not Alice), then the attacker figures the real
  866. %source was a client that is using Alice as a helper node. [How's my
  867. %logic here?] -RD
  868. %
  869. % Not sure about the logic. For the attack to work with helper nodes, the
  870. %attacker needs to guess that Alice is running the hidden service, right?
  871. %Otherwise, how can he know to measure her traffic specifically? -NM
  872. %
  873. % In the Murdoch-Danezis attack, the adversary measures all servers. -RD
  874. %point to routing-zones section re: helper nodes to defend against
  875. %big stuff.
  876. \subsection{Location-hidden services}
  877. \label{subsec:hidden-services}
  878. Tor's \emph{rendezvous points}
  879. let users provide TCP services to other Tor users without revealing
  880. the service's location. Since this feature is relatively recent, we describe here
  881. a couple of our early observations from its deployment.
  882. First, our implementation of hidden services seems less hidden than we'd
  883. like, since they are configured on a single client and get used over
  884. and over---particularly because an external adversary can induce them to
  885. produce traffic. They seem the ideal use case for our above discussion
  886. of helper nodes. This insecurity means that they may not be suitable as
  887. a building block for Free Haven~\cite{freehaven-berk} or other anonymous
  888. publishing systems that aim to provide long-term security.
  889. \emph{Hot-swap} hidden services, where more than one location can
  890. provide the service and loss of any one location does not imply a
  891. change in service, would help foil intersection and observation attacks
  892. where an adversary monitors availability of a hidden service and also
  893. monitors whether certain users or servers are online. The design
  894. challenges in providing such services without otherwise compromising
  895. the hidden service's anonymity remain an open problem;
  896. however, see~\cite{move-ndss05}.
  897. In practice, hidden services are used for more than just providing private
  898. access to a web server or IRC server. People are using hidden services
  899. as a poor man's VPN and firewall-buster. Many people want to be able
  900. to connect to the computers in their private network via secure shell,
  901. and rather than playing with dyndns and trying to pierce holes in their
  902. firewall, they run a hidden service on the inside and then rendezvous
  903. with that hidden service externally.
  904. News sites like Bloggers Without Borders (www.b19s.org) are advertising
  905. a hidden-service address on their front page. Doing this can provide
  906. increased robustness if they use the dual-IP approach we describe
  907. in~\cite{tor-design},
  908. but in practice they do it firstly to increase visibility
  909. of the Tor project and their support for privacy, and secondly to offer
  910. a way for their users, using unmodified software, to get end-to-end
  911. encryption and end-to-end authentication to their website.
  912. \subsection{Location diversity and ISP-class adversaries}
  913. \label{subsec:routing-zones}
  914. Anonymity networks have long relied on diversity of node location for
  915. protection against attacks---typically an adversary who can observe a
  916. larger fraction of the network can launch a more effective attack. One
  917. way to achieve dispersal involves growing the network so a given adversary
  918. sees less. Alternately, we can arrange the topology so traffic can enter
  919. or exit at many places (for example, by using a free-route network
  920. like Tor rather than a cascade network like JAP). Lastly, we can use
  921. distributed trust to spread each transaction over multiple jurisdictions.
  922. But how do we decide whether two nodes are in related locations?
  923. Feamster and Dingledine defined a \emph{location diversity} metric
  924. in \cite{feamster:wpes2004}, and began investigating a variant of location
  925. diversity based on the fact that the Internet is divided into thousands of
  926. independently operated networks called {\em autonomous systems} (ASes).
  927. The key insight from their paper is that while we typically think of a
  928. connection as going directly from the Tor client to her first Tor node,
  929. actually it traverses many different ASes on each hop. An adversary at
  930. any of these ASes can monitor or influence traffic. Specifically, given
  931. plausible initiators and recipients and path random path selection,
  932. some ASes in the simulation were able to observe 10\% to 30\% of the
  933. transactions (that is, learn both the origin and the destination) on
  934. the deployed Tor network (33 nodes as of June 2004).
  935. The paper concludes that for best protection against the AS-level
  936. adversary, nodes should be in ASes that have the most links to other ASes:
  937. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  938. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  939. initiator and responder are both in the U.S., it actually \emph{hurts}
  940. our location diversity to add far-flung nodes in continents like Asia
  941. or South America.
  942. Many open questions remain. First, it will be an immense engineering
  943. challenge to get an entire BGP routing table to each Tor client, or to
  944. summarize it sufficiently. Without a local copy, clients won't be
  945. able to safely predict what ASes will be traversed on the various paths
  946. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  947. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  948. determine location diversity; but the above paper showed that in practice
  949. many of the Mixmaster nodes that share a single AS have entirely different
  950. IP prefixes. When the network has scaled to thousands of nodes, does IP
  951. prefix comparison become a more useful approximation?
  952. %
  953. Second, we can take advantage of caching certain content at the
  954. exit nodes, to limit the number of requests that need to leave the
  955. network at all. What about taking advantage of caches like Akamai or
  956. Google~\cite{shsm03}? (Note that they're also well-positioned as global
  957. adversaries.)
  958. %
  959. Third, if we follow the paper's recommendations and tailor path selection
  960. to avoid choosing endpoints in similar locations, how much are we hurting
  961. anonymity against larger real-world adversaries who can take advantage
  962. of knowing our algorithm?
  963. %
  964. Lastly, can we use this knowledge to figure out which gaps in our network
  965. would most improve our robustness to this class of attack, and go recruit
  966. new nodes with those ASes in mind?
  967. %Tor's security relies in large part on the dispersal properties of its
  968. %network. We need to be more aware of the anonymity properties of various
  969. %approaches so we can make better design decisions in the future.
  970. \subsection{The China problem}
  971. \label{subsec:china}
  972. Citizens in a variety of countries, such as most recently China and
  973. Iran, are periodically blocked from accessing various sites outside
  974. their country. These users try to find any tools available to allow
  975. them to get-around these firewalls. Some anonymity networks, such as
  976. Six-Four~\cite{six-four}, are designed specifically with this goal in
  977. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  978. such as Voice of America to set up a network to encourage Internet
  979. freedom. Even though Tor wasn't
  980. designed with ubiquitous access to the network in mind, thousands of
  981. users across the world are trying to use it for exactly this purpose.
  982. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  983. Anti-censorship networks hoping to bridge country-level blocks face
  984. a variety of challenges. One of these is that they need to find enough
  985. exit nodes---servers on the `free' side that are willing to relay
  986. arbitrary traffic from users to their final destinations. Anonymizing
  987. networks including Tor are well-suited to this task, since we have
  988. already gathered a set of exit nodes that are willing to tolerate some
  989. political heat.
  990. The other main challenge is to distribute a list of reachable relays
  991. to the users inside the country, and give them software to use them,
  992. without letting the authorities also enumerate this list and block each
  993. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  994. addresses (or having them donated), abandoning old addresses as they are
  995. `used up', and telling a few users about the new ones. Distributed
  996. anonymizing networks again have an advantage here, in that we already
  997. have tens of thousands of separate IP addresses whose users might
  998. volunteer to provide this service since they've already installed and use
  999. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1000. the Tor protocol separates routing from network discovery \cite{tor-design},
  1001. volunteers could configure their Tor clients
  1002. to generate node descriptors and send them to a special directory
  1003. server that gives them out to dissidents who need to get around blocks.
  1004. Of course, this still doesn't prevent the adversary
  1005. from enumerating all the volunteer relays and blocking them preemptively.
  1006. Perhaps a tiered-trust system could be built where a few individuals are
  1007. given relays' locations, and they recommend other individuals by telling them
  1008. those addresses, thus providing a built-in incentive to avoid letting the
  1009. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1010. might help to bound the number of IP addresses leaked to the adversary. Groups
  1011. like the W3C are looking into using Tor as a component in an overall system to
  1012. help address censorship; we wish them luck.
  1013. %\cite{infranet}
  1014. \section{Scaling}
  1015. \label{sec:scaling}
  1016. Tor is running today with hundreds of nodes and tens of thousands of
  1017. users, but it will certainly not scale to millions.
  1018. Scaling Tor involves three main challenges. First is safe node
  1019. discovery, both bootstrapping -- how a Tor client can robustly find an
  1020. initial node list -- and ongoing -- how a Tor client can learn about
  1021. a fair sample of honest nodes and not let the adversary control his
  1022. circuits (see Section~\ref{subsec:trust-and-discovery}). Second is detecting and handling the speed
  1023. and reliability of the variety of nodes we must use if we want to
  1024. accept many nodes (see Section~\ref{subsec:performance}).
  1025. Since the speed and reliability of a circuit is limited by its worst link,
  1026. we must learn to track and predict performance. Finally, in order to get
  1027. a large set of nodes in the first place, we must address incentives
  1028. for users to carry traffic for others (see Section incentives).
  1029. \subsection{Incentives by Design}
  1030. There are three behaviors we need to encourage for each Tor node: relaying
  1031. traffic; providing good throughput and reliability while doing it;
  1032. and allowing traffic to exit the network from that node.
  1033. We encourage these behaviors through \emph{indirect} incentives, that
  1034. is, designing the system and educating users in such a way that users
  1035. with certain goals will choose to relay traffic. One
  1036. main incentive for running a Tor node is social benefit: volunteers
  1037. altruistically donate their bandwidth and time. We also keep public
  1038. rankings of the throughput and reliability of nodes, much like
  1039. seti@home. We further explain to users that they can get plausible
  1040. deniability for any traffic emerging from the same address as a Tor
  1041. exit node, and they can use their own Tor node
  1042. as entry or exit point and be confident it's not run by the adversary.
  1043. Further, users who need to be able to communicate anonymously
  1044. may run a node simply because their need to increase
  1045. expectation that such a network continues to be available to them
  1046. and usable exceeds any countervening costs.
  1047. Finally, we can improve the usability and feature set of the software:
  1048. rate limiting support and easy packaging decrease the hassle of
  1049. maintaining a node, and our configurable exit policies allow each
  1050. operator to advertise a policy describing the hosts and ports to which
  1051. he feels comfortable connecting.
  1052. To date these appear to have been adequate. As the system scales or as
  1053. new issues emerge, however, we may also need to provide
  1054. \emph{direct} incentives:
  1055. providing payment or other resources in return for high-quality service.
  1056. Paying actual money is problematic: decentralized e-cash systems are
  1057. not yet practical, and a centralized collection system not only reduces
  1058. robustness, but also has failed in the past (the history of commercial
  1059. anonymizing networks is littered with failed attempts). A more promising
  1060. option is to use a tit-for-tat incentive scheme: provide better service
  1061. to nodes that have provided good service to you.
  1062. Unfortunately, such an approach introduces new anonymity problems.
  1063. There are many surprising ways for nodes to game the incentive and
  1064. reputation system to undermine anonymity because such systems are
  1065. designed to encourage fairness in storage or bandwidth usage not
  1066. fairness of provided anonymity. An adversary can attract more traffic
  1067. by performing well or can provide targeted differential performance to
  1068. individual users to undermine their anonymity. Typically a user who
  1069. chooses evenly from all options is most resistant to an adversary
  1070. targeting him, but that approach prevents from handling heterogeneous
  1071. nodes.
  1072. %When a node (call him Steve) performs well for Alice, does Steve gain
  1073. %reputation with the entire system, or just with Alice? If the entire
  1074. %system, how does Alice tell everybody about her experience in a way that
  1075. %prevents her from lying about it yet still protects her identity? If
  1076. %Steve's behavior only affects Alice's behavior, does this allow Steve to
  1077. %selectively perform only for Alice, and then break her anonymity later
  1078. %when somebody (presumably Alice) routes through his node?
  1079. A possible solution is a simplified approach to the tit-for-tat
  1080. incentive scheme based on two rules: (1) each node should measure the
  1081. service it receives from adjacent nodes, and provide service relative
  1082. to the received service, but (2) when a node is making decisions that
  1083. affect its own security (e.g. when building a circuit for its own
  1084. application connections), it should choose evenly from a sufficiently
  1085. large set of nodes that meet some minimum service threshold
  1086. \cite{casc-rep}. This approach allows us to discourage bad service
  1087. without opening Alice up as much to attacks. All of this requires
  1088. further study.
  1089. %XXX rewrite the above so it sounds less like a grant proposal and
  1090. %more like a "if somebody were to try to solve this, maybe this is a
  1091. %good first step".
  1092. %We should implement the above incentive scheme in the
  1093. %deployed Tor network, in conjunction with our plans to add the necessary
  1094. %associated scalability mechanisms. We will do experiments (simulated
  1095. %and/or real) to determine how much the incentive system improves
  1096. %efficiency over baseline, and also to determine how far we are from
  1097. %optimal efficiency (what we could get if we ignored the anonymity goals).
  1098. \subsection{Trust and discovery}
  1099. \label{subsec:trust-and-discovery}
  1100. The published Tor design adopted a deliberately simplistic design for
  1101. authorizing new nodes and informing clients about Tor nodes and their status.
  1102. In the early Tor designs, all nodes periodically uploaded a signed description
  1103. of their locations, keys, and capabilities to each of several well-known {\it
  1104. directory servers}. These directory servers constructed a signed summary
  1105. of all known Tor nodes (a ``directory''), and a signed statement of which
  1106. nodes they
  1107. believed to be operational at any given time (a ``network status''). Clients
  1108. periodically downloaded a directory in order to learn the latest nodes and
  1109. keys, and more frequently downloaded a network status to learn which nodes are
  1110. likely to be running. Tor nodes also operate as directory caches, in order to
  1111. lighten the bandwidth on the authoritative directory servers.
  1112. In order to prevent Sybil attacks (wherein an adversary signs up many
  1113. purportedly independent nodes in order to increase her chances of observing
  1114. a stream as it enters and leaves the network), the early Tor directory design
  1115. required the operators of the authoritative directory servers to manually
  1116. approve new nodes. Unapproved nodes were included in the directory,
  1117. but clients
  1118. did not use them at the start or end of their circuits. In practice,
  1119. directory administrators performed little actual verification, and tended to
  1120. approve any Tor node whose operator could compose a coherent email.
  1121. This procedure
  1122. may have prevented trivial automated Sybil attacks, but would do little
  1123. against a clever attacker.
  1124. There are a number of flaws in this system that need to be addressed as we
  1125. move forward. They include:
  1126. \begin{tightlist}
  1127. \item Each directory server represents an independent point of failure; if
  1128. any one were compromised, it could immediately compromise all of its users
  1129. by recommending only compromised nodes.
  1130. \item The more nodes join the network, the more unreasonable it
  1131. becomes to expect clients to know about them all. Directories
  1132. become infeasibly large, and downloading the list of nodes becomes
  1133. burdensome.
  1134. \item The validation scheme may do as much harm as it does good. It is not
  1135. only incapable of preventing clever attackers from mounting Sybil attacks,
  1136. but may deter node operators from joining the network. (For instance, if
  1137. they expect the validation process to be difficult, or if they do not share
  1138. any languages in common with the directory server operators.)
  1139. \end{tightlist}
  1140. We could try to move the system in several directions, depending on our
  1141. choice of threat model and requirements. If we did not need to increase
  1142. network capacity in order to support more users, we could simply
  1143. adopt even stricter validation requirements, and reduce the number of
  1144. nodes in the network to a trusted minimum.
  1145. But, we can only do that if can simultaneously make node capacity
  1146. scale much more than we anticipate feasible soon, and if we can find
  1147. entities willing to run such nodes, an equally daunting prospect.
  1148. In order to address the first two issues, it seems wise to move to a system
  1149. including a number of semi-trusted directory servers, no one of which can
  1150. compromise a user on its own. Ultimately, of course, we cannot escape the
  1151. problem of a first introducer: since most users will run Tor in whatever
  1152. configuration the software ships with, the Tor distribution itself will
  1153. remain a potential single point of failure so long as it includes the seed
  1154. keys for directory servers, a list of directory servers, or any other means
  1155. to learn which nodes are on the network. But omitting this information
  1156. from the Tor distribution would only delegate the trust problem to the
  1157. individual users, most of whom are presumably less informed about how to make
  1158. trust decisions than the Tor developers.
  1159. %Network discovery, sybil, node admission, scaling. It seems that the code
  1160. %will ship with something and that's our trust root. We could try to get
  1161. %people to build a web of trust, but no. Where we go from here depends
  1162. %on what threats we have in mind. Really decentralized if your threat is
  1163. %RIAA; less so if threat is to application data or individuals or...
  1164. \subsection{Measuring performance and capacity}
  1165. \label{subsec:performance}
  1166. One of the paradoxes with engineering an anonymity network is that we'd like
  1167. to learn as much as we can about how traffic flows so we can improve the
  1168. network, but we want to prevent others from learning how traffic flows in
  1169. order to trace users' connections through the network. Furthermore, many
  1170. mechanisms that help Tor run efficiently
  1171. require measurements about the network.
  1172. Currently, nodes try to deduce their own available bandwidth (based on how
  1173. much traffic they have been able to transfer recently) and include this
  1174. information in the descriptors they upload to the directory. Clients
  1175. choose servers weighted by their bandwidth, neglecting really slow
  1176. servers and capping the influence of really fast ones.
  1177. %
  1178. This is, of course, eminently cheatable. A malicious node can get a
  1179. disproportionate amount of traffic simply by claiming to have more bandwidth
  1180. than it does. But better mechanisms have their problems. If bandwidth data
  1181. is to be measured rather than self-reported, it is usually possible for
  1182. nodes to selectively provide better service for the measuring party, or
  1183. sabotage the measured value of other nodes. Complex solutions for
  1184. mix networks have been proposed, but do not address the issues
  1185. completely~\cite{mix-acc,casc-rep}.
  1186. Even with no cheating, network measurement is complex. It is common
  1187. for views of a node's latency and/or bandwidth to vary wildly between
  1188. observers. Further, it is unclear whether total bandwidth is really
  1189. the right measure; perhaps clients should instead be considering nodes
  1190. based on unused bandwidth or observed throughput.
  1191. % XXXX say more here?
  1192. %How to measure performance without letting people selectively deny service
  1193. %by distinguishing pings. Heck, just how to measure performance at all. In
  1194. %practice people have funny firewalls that don't match up to their exit
  1195. %policies and Tor doesn't deal.
  1196. %Network investigation: Is all this bandwidth publishing thing a good idea?
  1197. %How can we collect stats better? Note weasel's smokeping, at
  1198. %http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  1199. %which probably gives george and steven enough info to break tor?
  1200. Even if we can collect and use this network information effectively, we need
  1201. to make sure that it is not more useful to attackers than to us. While it
  1202. seems plausible that bandwidth data alone is not enough to reveal
  1203. sender-recipient connections under most circumstances, it could certainly
  1204. reveal the path taken by large traffic flows under low-usage circumstances.
  1205. \subsection{Non-clique topologies}
  1206. Tor's comparatively weak model makes it easier to scale than other mix net
  1207. designs. High-latency mix networks need to avoid partitioning attacks, where
  1208. network splits prevent users of the separate partitions from providing cover
  1209. for each other. In Tor, however, we assume that the adversary cannot
  1210. cheaply observe nodes at will, so even if the network becomes split, the
  1211. users do not necessarily receive much less protection.
  1212. Thus, a simple possibility when the scale of a Tor network
  1213. exceeds some size is to simply split it. Care could be taken in
  1214. allocating which nodes go to which network along the lines of
  1215. \cite{casc-rep} to insure that collaborating hostile nodes are not
  1216. able to gain any advantage in network splitting that they do not
  1217. already have in joining a network.
  1218. If the network is split,
  1219. a client does not need to use just one of the two resulting networks.
  1220. Alice could use either of them, and it would not be difficult to make
  1221. the Tor client able to access several such network on a per circuit
  1222. basis. More analysis is needed; we simply note here that splitting
  1223. a Tor network is an easy way to achieve moderate scalability and that
  1224. it does not necessarily have the same implications as splitting a mixnet.
  1225. Alternatively, we can try to scale a single Tor network. Some issues for
  1226. scaling include restricting the number of sockets and the amount of bandwidth
  1227. used by each node. The number of sockets is determined by the network's
  1228. connectivity and the number of users, while bandwidth capacity is determined
  1229. by the total bandwidth of nodes on the network. The simplest solution to
  1230. bandwidth capacity is to add more nodes, since adding a tor node of any
  1231. feasible bandwidth will increase the traffic capacity of the network. So as
  1232. a first step to scaling, we should focus on making the network tolerate more
  1233. nodes, by reducing the interconnectivity of the nodes; later we can reduce
  1234. overhead associated with directories, discovery, and so on.
  1235. By reducing the connectivity of the network we increase the total number of
  1236. nodes that the network can contain. Danezis~\cite{danezis-pets03} considers
  1237. the anonymity implications of restricting routes on mix networks, and
  1238. recommends an approach based on expander graphs (where any subgraph is likely
  1239. to have many neighbors). It is not immediately clear that this approach will
  1240. extend to Tor, which has a weaker threat model but higher performance
  1241. requirements than the network considered. Instead of analyzing the
  1242. probability of an attacker's viewing whole paths, we will need to examine the
  1243. attacker's likelihood of compromising the endpoints of a Tor circuit through
  1244. a sparse network.
  1245. % Nick edits these next 2 grafs.
  1246. To make matters simpler, Tor may not need an expander graph per se: it
  1247. may be enough to have a single subnet that is highly connected. As an
  1248. example, assume fifty nodes of relatively high traffic capacity. This
  1249. \emph{center} forms are a clique. Assume each center node can each
  1250. handle 200 connections to other nodes (including the other ones in the
  1251. center). Assume every noncenter node connects to three nodes in the
  1252. center and anyone out of the center that they want to. Then the
  1253. network easily scales to c. 2500 nodes with commensurate increase in
  1254. bandwidth. There are many open questions: how directory information
  1255. is distributed (presumably information about the center nodes could
  1256. be given to any new nodes with their codebase), whether center nodes
  1257. will need to function as a `backbone', etc. As above the point is
  1258. that this would create problems for the expected anonymity for a mixnet,
  1259. but for an onion routing network where anonymity derives largely from
  1260. the edges, it may be feasible.
  1261. Another point is that we already have a non-clique topology.
  1262. Individuals can set up and run Tor nodes without informing the
  1263. directory servers. This will allow, e.g., dissident groups to run a
  1264. local Tor network of such nodes that connects to the public Tor
  1265. network. This network is hidden behind the Tor network and its
  1266. only visible connection to Tor at those points where it connects.
  1267. As far as the public network is concerned or anyone observing it,
  1268. they are running clients.
  1269. \section{The Future}
  1270. \label{sec:conclusion}
  1271. Tor is the largest and most diverse low-latency anonymity network
  1272. available, but we are still in the beginning stages of deployment. Several
  1273. major questions remain.
  1274. First, will our volunteer-based approach to sustainability work in the
  1275. long term? As we add more features and destabilize the network, the
  1276. developers spend a lot of time keeping the server operators happy. Even
  1277. though Tor is free software, the network would likely stagnate and die at
  1278. this stage if the developers stopped actively working on it. We may get
  1279. an unexpected boon from the fact that we're a general-purpose overlay
  1280. network: as Tor grows more popular, other groups who need an overlay
  1281. network on the Internet are starting to adapt Tor to their needs.
  1282. %
  1283. Second, Tor is only one of many components that preserve privacy online.
  1284. To keep identifying information out of application traffic, we must build
  1285. more and better protocol-aware proxies that are usable by ordinary people.
  1286. %
  1287. Third, we need to gain a reputation for social good, and learn how to
  1288. coexist with the variety of Internet services and their established
  1289. authentication mechanisms. We can't just keep escalating the blacklist
  1290. standoff forever.
  1291. %
  1292. Fourth, the current Tor
  1293. architecture does not scale even to handle current user demand. We must
  1294. find designs and incentives to let some clients relay traffic too, without
  1295. sacrificing too much anonymity.
  1296. These are difficult and open questions, yet choosing not to solve them
  1297. means leaving most users to a less secure network or no anonymizing
  1298. network at all.
  1299. \bibliographystyle{plain} \bibliography{tor-design}
  1300. \clearpage
  1301. \appendix
  1302. \begin{figure}[t]
  1303. %\unitlength=1in
  1304. \centering
  1305. %\begin{picture}(6.0,2.0)
  1306. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1307. %\end{picture}
  1308. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1309. \caption{Number of Tor nodes over time, through January 2005. Lowest
  1310. line is number of exit
  1311. nodes that allow connections to port 80. Middle line is total number of
  1312. verified (registered) Tor nodes. The line above that represents nodes
  1313. that are running but not yet registered.}
  1314. \label{fig:graphnodes}
  1315. \end{figure}
  1316. \begin{figure}[t]
  1317. \centering
  1318. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1319. \caption{The sum of traffic reported by each node over time, through
  1320. January 2005. The bottom
  1321. pair show average throughput, and the top pair represent the largest 15
  1322. minute burst in each 4 hour period.}
  1323. \label{fig:graphtraffic}
  1324. \end{figure}
  1325. \end{document}
  1326. Making use of nodes with little bandwidth, or high latency/packet loss.
  1327. Running Tor nodes behind NATs, behind great-firewalls-of-China, etc.
  1328. Restricted routes. How to propagate to everybody the topology? BGP
  1329. style doesn't work because we don't want just *one* path. Point to
  1330. Geoff's stuff.