challenges.tex 82 KB

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