challenges.tex 80 KB

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  1. \documentclass{llncs}
  2. % XXXX NM: Fold ``bandwidth and usability'' into ``Tor and file-sharing'' --
  3. % ``bandwidth and file-sharing''.
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  19. \begin{document}
  20. \title{Challenges in deploying low-latency anonymity}
  21. \author{Roger Dingledine\inst{1} \and
  22. Nick Mathewson\inst{1} \and
  23. Paul Syverson\inst{2}}
  24. \institute{The Free Haven Project \email{<\{arma,nickm\}@freehaven.net>} \and
  25. Naval Research Laboratory \email{<syverson@itd.nrl.navy.mil>}}
  26. \maketitle
  27. \pagestyle{plain}
  28. \begin{abstract}
  29. There are many unexpected or unexpectedly difficult obstacles to
  30. deploying anonymous communications. Drawing on our experiences deploying
  31. Tor (the second-generation onion routing network), we describe social
  32. challenges and technical issues that must be faced
  33. in building, deploying, and sustaining a scalable, distributed, low-latency
  34. anonymity network.
  35. \end{abstract}
  36. \section{Introduction}
  37. % Your network is not practical unless it is sustainable and distributed.
  38. Anonymous communication is full of surprises. This paper discusses some
  39. unexpected challenges arising from our experiences deploying Tor, a
  40. low-latency general-purpose anonymous communication system. We will discuss
  41. some of the difficulties we have experienced and how we have met them (or how
  42. we plan to meet them, if we know). We also discuss some less
  43. troublesome open problems that we must nevertheless eventually address.
  44. %We will describe both those future challenges that we intend to explore and
  45. %those that we have decided not to explore and why.
  46. Tor is an overlay network for anonymizing TCP streams over the
  47. Internet~\cite{tor-design}. It addresses limitations in earlier Onion
  48. Routing designs~\cite{or-ih96,or-jsac98,or-discex00,or-pet00} by adding
  49. perfect forward secrecy, congestion control, directory servers, data
  50. integrity, configurable exit policies, and location-hidden services using
  51. rendezvous points. Tor works on the real-world Internet, requires no special
  52. privileges or kernel modifications, requires little synchronization or
  53. coordination between nodes, and provides a reasonable tradeoff between
  54. anonymity, usability, and efficiency.
  55. We first deployed a public Tor network in October 2003; since then it has
  56. grown to over a hundred volunteer-operated nodes
  57. and as much as 80 megabits of
  58. average traffic per second. Tor's research strategy has focused on deploying
  59. a network to as many users as possible; thus, we have resisted designs that
  60. would compromise deployability by imposing high resource demands on node
  61. operators, and designs that would compromise usability by imposing
  62. unacceptable restrictions on which applications we support. Although this
  63. strategy has
  64. drawbacks (including a weakened threat model, as discussed below), it has
  65. made it possible for Tor to serve many thousands of users and attract
  66. funding from diverse sources whose goals range from security on a
  67. national scale down to individual liberties.
  68. In~\cite{tor-design} we gave an overall view of Tor's
  69. design and goals. Here we describe some policy, social, and technical
  70. issues that we face as we continue deployment.
  71. Rather than providing complete solutions to every problem, we
  72. instead lay out the challenges and constraints that we have observed while
  73. deploying Tor in the wild. In doing so, we aim to provide a research agenda
  74. of general interest to projects attempting to build
  75. and deploy practical, usable anonymity networks in the wild.
  76. %While the Tor design paper~\cite{tor-design} gives an overall view its
  77. %design and goals,
  78. %this paper describes the policy and technical issues that Tor faces as
  79. %we continue deployment. Rather than trying to provide complete solutions
  80. %to every problem here, we lay out the assumptions and constraints
  81. %that we have observed through deploying Tor in the wild. In doing so, we
  82. %aim to create a research agenda for others to
  83. %help in addressing these issues.
  84. % Section~\ref{sec:what-is-tor} gives an
  85. %overview of the Tor
  86. %design and ours goals. Sections~\ref{sec:crossroads-policy}
  87. %and~\ref{sec:crossroads-design} go on to describe the practical challenges,
  88. %both policy and technical respectively,
  89. %that stand in the way of moving
  90. %from a practical useful network to a practical useful anonymous network.
  91. %\section{What Is Tor}
  92. \section{Background}
  93. Here we give a basic overview of the Tor design and its properties, and
  94. compare Tor to other low-latency anonymity designs.
  95. \subsection{Tor, threat models, and distributed trust}
  96. \label{sec:what-is-tor}
  97. %Here we give a basic overview of the Tor design and its properties. For
  98. %details on the design, assumptions, and security arguments, we refer
  99. %the reader to the Tor design paper~\cite{tor-design}.
  100. %\medskip
  101. \noindent
  102. {\bf How Tor works.}
  103. Tor provides \emph{forward privacy}, so that users can connect to
  104. Internet sites without revealing their logical or physical locations
  105. to those sites or to observers. It also provides \emph{location-hidden
  106. services}, so that servers can support authorized users without
  107. giving an effective vector for physical or online attackers.
  108. Tor provides these protections even when a portion of its
  109. infrastructure is compromised.
  110. To connect to a remove server via Tor, the client software learns a signed
  111. list of Tor nodes from one of several central \emph{directory servers}, and
  112. incrementally creates a private pathway or \emph{circuit} of encrypted
  113. connections through authenticated Tor nodes on the network, negotiating a
  114. separate set of encryption keys for each hop along the circuit. The circuit
  115. is extended one node at a time, and each node along the way knows only the
  116. immediately previous and following nodes in the circuit, so no individual Tor
  117. node knows the complete path that each fixed-sized data packet (or
  118. \emph{cell}) will take.
  119. %Because each node sees no more than one hop in the
  120. %circuit,
  121. Thus, neither an eavesdropper nor a compromised node can
  122. see both the connection's source and destination. Later requests use a new
  123. circuit, to complicate long-term linkability between different actions by
  124. a single user.
  125. Tor also helps servers hide their locations while
  126. providing services such as web publishing or instant
  127. messaging. Using ``rendezvous points'', other Tor users can
  128. connect to these authenticated hidden services, neither one learning the
  129. other's network identity.
  130. Tor attempts to anonymize the transport layer, not the application layer.
  131. This approach is useful for applications such as SSH
  132. where authenticated communication is desired. However, when anonymity from
  133. those with whom we communicate is desired,
  134. application protocols that include personally identifying information need
  135. additional application-level scrubbing proxies, such as
  136. Privoxy~\cite{privoxy} for HTTP\@. Furthermore, Tor does not relay arbitrary
  137. IP packets; it only anonymizes TCP streams and DNS requests
  138. %, and only supports
  139. %connections via SOCKS
  140. (but see Section~\ref{subsec:tcp-vs-ip}).
  141. Most node operators do not want to allow arbitary TCP traffic.% to leave
  142. %their server.
  143. To address this, Tor provides \emph{exit policies} so
  144. each exit node can block the IP addresses and ports it is unwilling to allow.
  145. Tor nodes advertise their exit policies to the directory servers, so that
  146. client can tell which nodes will support their connections.
  147. As of January 2005, the Tor network has grown to around a hundred nodes
  148. on four continents, with a total capacity exceeding 1Gbit/s. Appendix A
  149. shows a graph of the number of working nodes over time, as well as a
  150. graph of the number of bytes being handled by the network over time.
  151. The network is now sufficiently diverse for further development
  152. and testing; but of course we always encourage new nodes
  153. to join.
  154. Tor research and development has been funded by ONR and DARPA
  155. for use in securing government
  156. communications, and by the Electronic Frontier Foundation, for use
  157. in maintaining civil liberties for ordinary citizens online. The Tor
  158. protocol is one of the leading choices
  159. for anonymizing layer in the European Union's PRIME directive to
  160. help maintain privacy in Europe.
  161. % XXXX We should credit the specific group, not the whole university.
  162. The University of Dresden in Germany
  163. has integrated an independent implementation of the Tor protocol into
  164. their popular Java Anon Proxy anonymizing client.
  165. % This wide variety of
  166. %interests helps maintain both the stability and the security of the
  167. %network.
  168. \medskip
  169. \noindent
  170. {\bf Threat models and design philosophy.}
  171. The ideal Tor network would be practical, useful and and anonymous. When
  172. trade-offs arise between these properties, Tor's research strategy has been
  173. to remain useful enough to attract many users,
  174. and practical enough to support them. Only subject to these
  175. constraints do we try to maximize
  176. anonymity.\footnote{This is not the only possible
  177. direction in anonymity research: designs exist that provide more anonymity
  178. than Tor at the expense of significantly increased resource requirements, or
  179. decreased flexibility in application support (typically because of increased
  180. latency). Such research does not typically abandon aspirations towards
  181. deployability or utility, but instead tries to maximize deployability and
  182. utility subject to a certain degree of structural anonymity (structural because
  183. usability and practicality affect usage which affects the actual anonymity
  184. provided by the network \cite{econymics,back01}).}
  185. %{We believe that these
  186. %approaches can be promising and useful, but that by focusing on deploying a
  187. %usable system in the wild, Tor helps us experiment with the actual parameters
  188. %of what makes a system ``practical'' for volunteer operators and ``useful''
  189. %for home users, and helps illuminate undernoticed issues which any deployed
  190. %volunteer anonymity network will need to address.}
  191. Because of our strategy, Tor has a weaker threat model than many designs in
  192. the literature. In particular, because we
  193. support interactive communications without impractically expensive padding,
  194. we fall prey to a variety
  195. of intra-network~\cite{back01,attack-tor-oak05,flow-correlation04} and
  196. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  197. Tor does not attempt to defend against a global observer. In general, an
  198. attacker who can observe both ends of a connection through the Tor network
  199. can correlate the timing and volume of data on that connection as it enters
  200. and leaves the network, and so link communication partners.
  201. Known solutions to this attack would seem to require introducing a
  202. prohibitive degree of traffic padding between the user and the network, or
  203. introducing an unacceptable degree of latency (but see Section
  204. \ref{subsec:mid-latency}). Also, it is not clear that these methods would
  205. work at all against even a minimally active adversary who could introduce timing
  206. patterns or additional traffic. Thus, Tor only attempts to defend against
  207. external observers who cannot observe both sides of a user's connections.
  208. Against internal attackers who sign up Tor nodes, the situation is more
  209. complicated. In the simplest case, if an adversary has compromised $c$ of
  210. $n$ nodes on the Tor network, then the adversary will be able to compromise
  211. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  212. initiator chooses hops randomly). But there are
  213. complicating factors:
  214. (1)~If the user continues to build random circuits over time, an adversary
  215. is pretty certain to see a statistical sample of the user's traffic, and
  216. thereby can build an increasingly accurate profile of her behavior. (See
  217. Section~\ref{subsec:helper-nodes} for possible solutions.)
  218. (2)~An adversary who controls a popular service outside the Tor network
  219. can be certain to observe all connections to that service; he
  220. can therefore trace connections to that service with probability
  221. $\frac{c}{n}$.
  222. (3)~Users do not in fact choose nodes with uniform probability; they
  223. favor nodes with high bandwidth or uptime, and exit nodes that
  224. permit connections to their favorite services.
  225. See Section~\ref{subsec:routing-zones} for discussion of larger
  226. adversaries and our dispersal goals.
  227. % I'm trying to make this paragraph work without reference to the
  228. % analysis/confirmation distinction, which we haven't actually introduced
  229. % yet, and which we realize isn't very stable anyway. Also, I don't want to
  230. % deprecate these attacks if we can't demonstrate that they don't work, since
  231. % in case they *do* turn out to work well against Tor, we'll look pretty
  232. % foolish. -NM
  233. More powerful attacks may exist. In \cite{hintz-pet02} it was
  234. shown that an attacker who can catalog data volumes of popular
  235. responder destinations (say, websites with consistant data volumes) may not
  236. need to
  237. observe both ends of a stream to learn source-destination links for those
  238. responders.
  239. %However, it is still essentially confirming
  240. %suspected communicants where the responder suspects are ``stored'' rather
  241. %than observed at the same time as the client.
  242. Similarly latencies of going through various routes can be
  243. cataloged~\cite{back01} to connect endpoints.
  244. % XXX hintz-pet02 just looked at data volumes of the sites. this
  245. % doesn't require much variability or storage. I think it works
  246. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  247. % attack another level further, to narrow down where you could be
  248. % based on an intersection attack on subpages in a website. -RD
  249. %
  250. % I was trying to be terse and simultaneously referring to both the
  251. % Hintz stuff and the Back et al. stuff from Info Hiding 01. I've
  252. % separated the two and added the references. -PFS
  253. It has not yet been shown whether these attacks will succeed or fail
  254. in the presence of the varaibility and volume quantization introduced by the
  255. Tor network, but it seems likely that these factors will at best delay
  256. rather than halt the attacks in the cases where they succeed.
  257. %likely to entail high variability and massive storage since
  258. %routes through the network to each site will be random even if they
  259. %have relatively unique latency characteristics. So this does not seem
  260. %an immediate practical threat.
  261. Along similar lines, the same
  262. paper suggested a ``clogging attack''. In \cite{attack-tor-oak05}, a
  263. version of this was demonstrated to be practical against portions of
  264. the fifty node Tor network as deployed in mid 2004. There it was shown
  265. that an outside attacker can trace a stream through the Tor network
  266. while a stream is still active by observing the latency of his
  267. own traffic sent through various Tor nodes. These attacks do not show
  268. client and server addresses, only the first and last nodes within the Tor
  269. network, so it is still necessary to observe those nodes to complete the
  270. attacks. This may make
  271. helper nodes all the more worthy of exploration (see
  272. Section~\ref{subsec:helper-nodes}).
  273. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  274. %the last hop is not $c/n$ since that doesn't take the destination (website)
  275. %into account. so in cases where the adversary does not also control the
  276. %final destination we're in good shape, but if he *does* then we'd be better
  277. %off with a system that lets each hop choose a path.
  278. %
  279. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  280. % dest, we would be just as well off with such as system.'' ? If not, why
  281. % not? -nm
  282. % Sure. In fact, better off, since they seem to scale more easily. -rd
  283. % XXXX the below paragraph should probably move later, and merge with
  284. % other discussions of attack-tor-oak5.
  285. %Murdoch and Danezis describe an attack
  286. %\cite{attack-tor-oak05} that lets an attacker determine the nodes used
  287. %in a circuit; yet s/he cannot identify the initiator or responder,
  288. %e.g., client or web server, through this attack. So the endpoints
  289. %remain secure, which is the goal. It is conceivable that an
  290. %adversary could attack or set up observation of all connections
  291. %to an arbitrary Tor node in only a few minutes. If such an adversary
  292. %were to exist, s/he could use this probing to remotely identify a node
  293. %for further attack. Of more likely immediate practical concern
  294. %an adversary with active access to the responder traffic
  295. %wants to keep a circuit alive long enough to attack an identified
  296. %node. Thus it is important to prevent the responding end of the circuit
  297. %from keeping it open indefinitely.
  298. %Also, someone could identify nodes in this way and if in their
  299. %jurisdiction, immediately get a subpoena (if they even need one)
  300. %telling the node operator(s) that she must retain all the active
  301. %circuit data she now has.
  302. %Further, the enclave model, which had previously looked to be the most
  303. %generally secure, seems particularly threatened by this attack, since
  304. %it identifies endpoints when they're also nodes in the Tor network:
  305. %see Section~\ref{subsec:helper-nodes} for discussion of some ways to
  306. %address this issue.
  307. \medskip
  308. \noindent
  309. {\bf Distributed trust.}
  310. In practice Tor's threat model is based on
  311. dispersal and diversity.
  312. Our defense lies in having a diverse enough set of nodes
  313. to prevent most real-world
  314. adversaries from being in the right places to attack users,
  315. by distributing each transaction
  316. over several nodes in the network. This ``distributed trust'' approach
  317. means the Tor network can be safely operated and used by a wide variety
  318. of mutually distrustful users, providing sustainability and security.
  319. %than some previous attempts at anonymizing networks.
  320. No organization can achieve this security on its own. If a single
  321. corporation or government agency were to build a private network to
  322. protect its operations, any connections entering or leaving that network
  323. would be obviously linkable to the controlling organization. The members
  324. and operations of that agency would be easier, not harder, to distinguish.
  325. Instead, to protect our networks from traffic analysis, we must
  326. collaboratively blend the traffic from many organizations and private
  327. citizens, so that an eavesdropper can't tell which users are which,
  328. and who is looking for what information. %By bringing more users onto
  329. %the network, all users become more secure~\cite{econymics}.
  330. %[XXX I feel uncomfortable saying this last sentence now. -RD]
  331. %[So, I took it out. I think we can do without it. -PFS]
  332. The Tor network has a broad range of users, including ordinary citizens
  333. concerned about their privacy, corporations
  334. who don't want to reveal information to their competitors, and law
  335. enforcement and government intelligence agencies who need
  336. to do operations on the Internet without being noticed.
  337. Naturally, organizations will not want to depend on others for their
  338. security. If most participating providers are reliable, Tor tolerates
  339. some hostile infiltration of the network. For maximum protection,
  340. the Tor design includes an enclave approach that lets data be encrypted
  341. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  342. hasn't been read or modified. This even works for Internet services that
  343. don't have built-in encryption and authentication, such as unencrypted
  344. HTTP or chat, and it requires no modification of those services.
  345. \subsection{Related work}
  346. Tor is not the only anonymity system that aims to be practical and useful.
  347. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  348. open proxies around the Internet, can provide good
  349. performance and some security against a weaker attacker. The Java
  350. Anon Proxy~\cite{web-mix} provides similar functionality to Tor but
  351. handles only web browsing rather than arbitrary TCP\@.
  352. %Some peer-to-peer file-sharing overlay networks such as
  353. %Freenet~\cite{freenet} and Mute~\cite{mute}
  354. Zero-Knowledge Systems' commercial Freedom
  355. network~\cite{freedom21-security} was even more flexible than Tor in
  356. transporting arbitrary IP packets, and also supported
  357. pseudonymous in addition to anonymity; but it has
  358. a different approach to sustainability (collecting money from users
  359. and paying ISPs to run Tor nodes), and was eventually shut down due to financial
  360. load. Finally, potentially
  361. more scalable peer-to-peer designs like Tarzan~\cite{tarzan:ccs02} and
  362. MorphMix~\cite{morphmix:fc04} have been proposed in the literature, but
  363. have not yet been fielded. These systems differ somewhat
  364. in threat model and presumably practical resistance to threats.
  365. Morphmix is close to Tor in circuit setup, and, by separating
  366. node discovery from route selection from circuit setup, Tor is
  367. flexible enough to potentially contain a Morphmix experiment within
  368. it. We direct the interested reader
  369. to~\cite{tor-design} for a more in-depth review of related work.
  370. Tor also differs from other deployed systems for traffic analysis resistance
  371. in its security and flexibility. Mix networks such as
  372. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  373. gain the highest degrees of anonymity at the expense of introducing highly
  374. variable delays, thus making them unsuitable for applications such as web
  375. browsing. Commercial single-hop
  376. proxies~\cite{anonymizer} present a single point of failure, where
  377. a single compromise can expose all users' traffic, and a single-point
  378. eavesdropper can perform traffic analysis on the entire network.
  379. Also, their proprietary implementations place any infrastucture that
  380. depends on these single-hop solutions at the mercy of their providers'
  381. financial health as well as network security.
  382. %XXXX six-four. crowds. i2p.
  383. %XXXX
  384. %have a serious discussion of morphmix's assumptions, since they would
  385. %seem to be the direct competition. in fact tor is a flexible architecture
  386. %that would encompass morphmix, and they're nearly identical except for
  387. %path selection and node discovery. and the trust system morphmix has
  388. %seems overkill (and/or insecure) based on the threat model we've picked.
  389. % this para should probably move to the scalability / directory system. -RD
  390. % Nope. Cut for space, except for small comment added above -PFS
  391. \section{Social challenges}
  392. Many of the issues the Tor project needs to address extend beyond
  393. system design and technology development. In particular, the
  394. Tor project's \emph{image} with respect to its users and the rest of
  395. the Internet impacts the security it can provide.
  396. % No image, no sustainability -NM
  397. With this image issue in mind, this section discusses the Tor user base and
  398. Tor's interaction with other services on the Internet.
  399. \subsection{Communicating security}
  400. Usability for anonymity systems
  401. contributes directly to their security, because usability
  402. effects the possible anonymity set~\cite{econymics,back01}.
  403. Conversely, an unusable system attracts few users and thus can't provide
  404. much anonymity.
  405. This phenomenon has a second-order effect: knowing this, users should
  406. choose which anonymity system to use based in part on how usable
  407. and secure
  408. \emph{others} will find it, in order to get the protection of a larger
  409. anonymity set. Thus we might supplement the adage ``usability is a security
  410. parameter''~\cite{back01} with a new one: ``perceived usability is a
  411. security parameter.'' From here we can better understand the effects
  412. of publicity on security: the more convincing your
  413. advertising, the more likely people will believe you have users, and thus
  414. the more users you will attract. Perversely, over-hyped systems (if they
  415. are not too broken) may be a better choice than modestly promoted ones,
  416. if the hype attracts more users~\cite{usability-network-effect}.
  417. So it follows that we should come up with ways to accurately communicate
  418. the available security levels to the user, so she can make informed
  419. decisions. JAP aims to do this by including a
  420. comforting `anonymity meter' dial in the software's graphical interface,
  421. giving the user an impression of the level of protection for her current
  422. traffic.
  423. However, there's a catch. For users to share the same anonymity set,
  424. they need to act like each other. An attacker who can distinguish
  425. a given user's traffic from the rest of the traffic will not be
  426. distracted by anonymity set size. For high-latency systems like
  427. Mixminion, where the threat model is based on mixing messages with each
  428. other, there's an arms race between end-to-end statistical attacks and
  429. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  430. But for low-latency systems like Tor, end-to-end \emph{traffic
  431. correlation} attacks~\cite{danezis-pet2004,defensive-dropping,SS03}
  432. allow an attacker who can observe both ends of a communication
  433. to correlate packet timing and volume, quickly linking
  434. the initiator to her destination.% This is why Tor's threat model is
  435. %based on preventing the adversary from observing both the initiator and
  436. %the responder.
  437. Like Tor, the current JAP implementation does not pad connections
  438. apart from using small fixed-size cells for transport. In fact,
  439. JAP's cascade-based network topology may be more vulnerable to these
  440. attacks, because the network has fewer edges. JAP was born out of
  441. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  442. every user had a fixed bandwidth allocation and altering the timing
  443. pattern of packets could be immediately detected, but in its current context
  444. as a general Internet web anonymizer, adding sufficient padding to JAP
  445. would probably be prohibitively expensive and ineffective against a
  446. minimally active attacker.\footnote{Even if JAP could
  447. fund higher-capacity nodes indefinitely, our experience
  448. suggests that many users would not accept the increased per-user
  449. bandwidth requirements, leading to an overall much smaller user base. But
  450. see Section~\ref{subsec:mid-latency}.} Therefore, since under this threat
  451. model the number of concurrent users does not seem to have much impact
  452. on the anonymity provided, we suggest that JAP's anonymity meter is not
  453. accurately communicating security levels to its users.
  454. % because more users don't help anonymity much, we need to rely more
  455. % on other incentive schemes, both policy-based (see sec x) and
  456. % technically enforced (see sec y)
  457. On the other hand, while the number of active concurrent users may not
  458. matter as much as we'd like, it still helps to have some other users
  459. on the network. We investigate this issue next.
  460. \subsection{Reputability and perceived social value}
  461. Another factor impacting the network's security is its reputability:
  462. the perception of its social value based on its current user base. If Alice is
  463. the only user who has ever downloaded the software, it might be socially
  464. accepted, but she's not getting much anonymity. Add a thousand
  465. activists, and she's anonymous, but everyone thinks she's an activist too.
  466. Add a thousand
  467. diverse citizens (cancer survivors, privacy enthusiasts, and so on)
  468. and now she's harder to profile.
  469. Furthermore, the network's reputability affects its operator base: more people
  470. are willing to run a service if they believe it will be used by human rights
  471. workers than if they believe it will be used exclusively for disreputable
  472. ends. This effect becomes stronger if node operators themselves think they
  473. will be associated with their users' disreputable ends.
  474. So the more cancer survivors on Tor, the better for the human rights
  475. activists. The more malicious hackers, the worse for the normal users. Thus,
  476. reputability is an anonymity issue for two reasons. First, it impacts
  477. the sustainability of the network: a network that's always about to be
  478. shut down has difficulty attracting and keeping adquate nodes.
  479. Second, a disreputable network is more vulnerable to legal and
  480. political attacks, since it will attract fewer supporters.
  481. While people therefore have an incentive for the network to be used for
  482. ``more reputable'' activities than their own, there are still tradeoffs
  483. involved when it comes to anonymity. To follow the above example, a
  484. network used entirely by cancer survivors might welcome file sharers
  485. onto the network, though of course they'd prefer a wider
  486. variety of users.
  487. Reputability becomes even more tricky in the case of privacy networks,
  488. since the good uses of the network (such as publishing by journalists in
  489. dangerous countries) are typically kept private, whereas network abuses
  490. or other problems tend to be more widely publicized.
  491. The impact of public perception on security is especially important
  492. during the bootstrapping phase of the network, where the first few
  493. widely publicized uses of the network can dictate the types of users it
  494. attracts next.
  495. As an example, some U.S.~Department of Energy
  496. penetration testing engineers are tasked with compromising DoE computers
  497. from the outside. They only have a limited number of ISPs from which to
  498. launch their attacks, and they found that the defenders were recognizing
  499. attacks because they came from the same IP space. These engineers wanted
  500. to use Tor to hide their tracks. First, from a technical standpoint,
  501. Tor does not support the variety of IP packets one would like to use in
  502. such attacks (see Section~\ref{subsec:tcp-vs-ip}). But aside from this,
  503. we also decided that it would probably be poor precedent to encourage
  504. such use---even legal use that improves national security---and managed
  505. to dissuade them.
  506. %% "outside of academia, jap has just lost, permanently". (That is,
  507. %% even though the crime detection issues are resolved and are unlikely
  508. %% to go down the same way again, public perception has not been kind.)
  509. \subsection{Sustainability and incentives}
  510. One of the unsolved problems in low-latency anonymity designs is
  511. how to keep the nodes running. Zero-Knowledge Systems's Freedom network
  512. depended on paying third parties to run its servers; the JAP project's
  513. bandwidth depends on grants to pay for its bandwidth and
  514. administrative expenses. In Tor, bandwidth and administrative costs are
  515. distributed across the volunteers who run Tor nodes, so we at least have
  516. reason to think that the Tor network could survive without continued research
  517. funding.\footnote{It also helps that Tor is implemented with free and open
  518. source software that can be maintained by anybody with the ability and
  519. inclination.} But why are these volunteers running nodes, and what can we
  520. do to encourage more volunteers to do so?
  521. We have not formally surveyed Tor node operators to learn why they are
  522. running nodes, but
  523. from the information they have provided, it seems that many of them run Tor
  524. nodes for reasons of personal interest in privacy issues. It is possible
  525. that others are running Tor for their own
  526. anonymity reasons, but of course they are
  527. hardly likely to tell us specifics if they are.
  528. %Significantly, Tor's threat model changes the anonymity incentives for running
  529. %a node. In a high-latency mix network, users can receive additional
  530. %anonymity by running their own node, since doing so obscures when they are
  531. %injecting messages into the network. But, anybody observing all I/O to a Tor
  532. %node can tell when the node is generating traffic that corresponds to
  533. %none of its incoming traffic.
  534. %
  535. %I didn't buy the above for reason's subtle enough that I just cut it -PFS
  536. Tor exit node operators do attain a degree of
  537. ``deniability'' for traffic that originates at that exit node. For
  538. example, it is likely in practice that HTTP requests from a Tor node's IP
  539. will be assumed to be from the Tor network.
  540. More significantly, people and organizations who use Tor for
  541. anonymity depend on the
  542. continued existence of the Tor network to do so; running a node helps to
  543. keep the network operational.
  544. %\item Local Tor entry and exit nodes allow users on a network to run in an
  545. % `enclave' configuration. [XXXX need to resolve this. They would do this
  546. % for E2E encryption + auth?]
  547. %We must try to make the costs of running a Tor node easily minimized.
  548. Since Tor is run by volunteers, the most crucial software usability issue is
  549. usability by operators: when an operator leaves, the network becomes less
  550. usable by everybody. To keep operators pleased, we must try to keep Tor's
  551. resource and administrative demands as low as possible.
  552. Because of ISP billing structures, many Tor operators have underused capacity
  553. that they are willing to donate to the network, at no additional monetary
  554. cost to them. Features to limit bandwidth have been essential to adoption.
  555. Also useful has been a ``hibernation'' feature that allows a Tor node that
  556. wants to provide high bandwidth, but no more than a certain amount in a
  557. giving billing cycle, to become dormant once its bandwidth is exhausted, and
  558. to reawaken at a random offset into the next billing cycle. This feature has
  559. interesting policy implications, however; see
  560. the next section below.
  561. Exit policies help to limit administrative costs by limiting the frequency of
  562. abuse complaints. (See Section~\ref{subsec:tor-and-blacklists}.)
  563. %[XXXX say more. Why else would you run a node? What else can we do/do we
  564. % already do to make running a node more attractive?]
  565. %[We can enforce incentives; see Section 6.1. We can rate-limit clients.
  566. % We can put "top bandwidth nodes lists" up a la seti@home.]
  567. \subsection{Bandwidth and file-sharing}
  568. \label{subsec:bandwidth-and-file-sharing}
  569. %One potentially problematical area with deploying Tor has been our response
  570. %to file-sharing applications.
  571. Once users have configured their applications to work with Tor, the largest
  572. remaining usability issue is performance. Users begin to suffer
  573. when websites ``feel slow.''
  574. Clients currently try to build their connections through nodes that they
  575. guess will have enough bandwidth. But even if capacity is allocated
  576. optimally, it seems unlikely that the current network architecture will have
  577. enough capacity to provide every user with as much bandwidth as she would
  578. receive if she weren't using Tor, unless far more nodes join the network.
  579. %Limited capacity does not destroy the network, however. Instead, usage tends
  580. %towards an equilibrium: when performance suffers, users who value performance
  581. %over anonymity tend to leave the system, thus freeing capacity until the
  582. %remaining users on the network are exactly those willing to use that capacity
  583. %there is.
  584. Much of Tor's recent bandwidth difficulties have come from file-sharing
  585. applications. These applications provide two challenges to
  586. any anonymizing network: their intensive bandwidth requirement, and the
  587. degree to which they are associated (correctly or not) with copyright
  588. infringement.
  589. As noted above, high-bandwidth protocols can make the network unresponsive,
  590. but tend to be somewhat self-correcting as lack of bandwidth drives away
  591. users who need it. Issues of copyright violation,
  592. however, are more interesting. Typical exit node operators want to help
  593. people achieve private and anonymous speech, not to help people (say) host
  594. Vin Diesel movies for download; and typical ISPs would rather not
  595. deal with customers who draw menacing letters
  596. from the MPAA\@. While it is quite likely that the operators are doing nothing
  597. illegal, many ISPs have policies of dropping users who get repeated legal
  598. threats regardless of the merits of those threats, and many operators would
  599. prefer to avoid receiving even meritless legal threats.
  600. So when letters arrive, operators are likely to face
  601. pressure to block file-sharing applications entirely, in order to avoid the
  602. hassle.
  603. But blocking file-sharing would not necessarily be easy; many popular
  604. protocols have evolved to run on a non-standard ports in order to
  605. get around other port-based bans. Thus, exit node operators who want to
  606. block file-sharing would have to find some way to integrate Tor with a
  607. protocol-aware exit filter. This could be a technically expensive
  608. undertaking, and one with poor prospects: it is unlikely that Tor exit nodes
  609. would succeed where so many institutional firewalls have failed. Another
  610. possibility for sensitive operators is to run a restrictive node that
  611. only permits exit connections to a restricted range of ports that are
  612. not frequently associated with file sharing. There are increasingly few such
  613. ports.
  614. Other possible approaches might include rate-limiting connections, especially
  615. long-lived connections or connections to file-sharing ports, so that
  616. high-bandwidth connections do not flood the network. We might also want to
  617. give priority to cells on low-bandwidth connections to keep them interactive,
  618. but this could have negative anonymity implications.
  619. For the moment, it seems that Tor's bandwidth issues have rendered it
  620. unattractive for bulk file-sharing traffic; this may continue to be so in the
  621. future. Nevertheless, Tor will likely remain attractive for limited use in
  622. file-sharing protocols that have separate control and data channels.
  623. %[We should say more -- but what? That we'll see a similar
  624. % equilibriating effect as with bandwidth, where sensitive ops switch to
  625. % middleman, and we become less useful for file-sharing, so the file-sharing
  626. % people back off, so we get more ops since there's less file-sharing, so the
  627. % file-sharers come back, etc.]
  628. %XXXX
  629. %in practice, plausible deniability is hypothetical and doesn't seem very
  630. %convincing. if ISPs find the activity antisocial, they don't care *why*
  631. %your computer is doing that behavior.
  632. \subsection{Tor and blacklists}
  633. \label{subsec:tor-and-blacklists}
  634. It was long expected that, alongside legitimate users, Tor would also
  635. attract troublemakers who exploited Tor in order to abuse services on the
  636. Internet with vandalism, rude mail, and so on.
  637. %[XXX we're not talking bandwidth abuse here, we're talking vandalism,
  638. %hate mails via hotmail, attacks, etc.]
  639. Our initial answer to this situation was to use ``exit policies''
  640. to allow individual Tor nodes to block access to specific IP/port ranges.
  641. This approach aims to make operators more willing to run Tor by allowing
  642. them to prevent their nodes from being used for abusing particular
  643. services. For example, all Tor nodes currently block SMTP (port 25), in
  644. order to avoid being used for spam.
  645. This approach is useful, but is insufficient for two reasons. First, since
  646. it is not possible to force all nodes to block access to any given service,
  647. many of those services try to block Tor instead. More broadly, while being
  648. blockable is important to being good netizens, we would like to encourage
  649. services to allow anonymous access; services should not need to decide
  650. between blocking legitimate anonymous use and allowing unlimited abuse.
  651. This is potentially a bigger problem than it may appear.
  652. On the one hand, people should be allowed to refuse connections to
  653. their services. But, it's not just
  654. for himself that a node administrator is deciding when he decides
  655. whether he prefers to be able to post to Wikipedia from his Tor node address,
  656. or to allow
  657. people to read Wikipedia anonymously through his Tor node. (Wikipedia
  658. has blocked all posting from all Tor nodes based on IP addresses.) If
  659. the Tor node shares an address with a campus or corporate NAT,
  660. then the decision can prevent the entire population from posting.
  661. This is a loss for both Tor
  662. and Wikipedia: we don't want to compete for (or divvy up) the
  663. NAT-protected entities of the world.
  664. Worse, many IP blacklists are not terribly fine-grained.
  665. No current IP blacklist, for example, allows a service provider to blacklist
  666. only those Tor nodes that allow access to a specific IP or port, even
  667. though this information is readily available. One IP blacklist even bans
  668. every class C network that contains a Tor node, and recommends banning SMTP
  669. from these networks even though Tor does not allow SMTP at all. This
  670. coarse-grained approach is typically a strategic decision to discourage the
  671. operation of anything resembling an open proxy by encouraging its neighbors
  672. to shut it down in order to get unblocked themselves.
  673. %[****Since this is stupid and we oppose it, shouldn't we name names here -pfs]
  674. %[XXX also, they're making \emph{middleman nodes leave} because they're caught
  675. % up in the standoff!]
  676. %[XXX Mention: it's not dumb, it's strategic!]
  677. %[XXX Mention: for some servops, any blacklist is a blacklist too many,
  678. % because it is risky. (Guy lives in apt _building_ with one IP.)]
  679. Problems of abuse occur mainly with services such as IRC networks and
  680. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  681. blush this practice might seem to depend on the anachronistic assumption that
  682. each IP is an identifier for a single user, it is actually more reasonable in
  683. practice: it assumes that non-proxy IPs are a costly resource, and that an
  684. abuser can not change IPs at will. By blocking IPs which are used by Tor
  685. nodes, open proxies, and service abusers, these systems hope to make
  686. ongoing abuse difficult. Although the system is imperfect, it works
  687. tolerably well for them in practice.
  688. But of course, we would prefer that legitimate anonymous users be able to
  689. access abuse-prone services. One conceivable approach would be to require
  690. would-be IRC users, for instance, to register accounts if they wanted to
  691. access the IRC network from Tor. In practice this would not
  692. significantly impede abuse if creating new accounts were easily automatable;
  693. this is why services use IP blocking. In order to deter abuse, pseudonymous
  694. identities need to require a significant switching cost in resources or human
  695. time.
  696. % XXX Mention captchas?
  697. %One approach, similar to that taken by Freedom, would be to bootstrap some
  698. %non-anonymous costly identification mechanism to allow access to a
  699. %blind-signature pseudonym protocol. This would effectively create costly
  700. %pseudonyms, which services could require in order to allow anonymous access.
  701. %This approach has difficulties in practise, however:
  702. %\begin{tightlist}
  703. %\item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  704. % be a shame to require payment in order to make Tor useful, or to make
  705. % non-paying users second-class citizens.
  706. %\item It is hard to think of an underlying resource that would actually work.
  707. % We could use IP addresses, but that's the problem, isn't it?
  708. %\item Managing single sign-on services is not considered a well-solved
  709. % problem in practice. If Microsoft can't get universal acceptance for
  710. % Passport, why do we think that a Tor-specific solution would do any good?
  711. %\item Even if we came up with a perfect authentication system for our needs,
  712. % there's no guarantee that any service would actually start using it. It
  713. % would require a nonzero effort for them to support it, and it might just
  714. % be less hassle for them to block tor anyway.
  715. %\end{tightlist}
  716. %The use of squishy IP-based ``authentication'' and ``authorization''
  717. %has not broken down even to the level that SSNs used for these
  718. %purposes have in commercial and public record contexts. Externalities
  719. %and misplaced incentives cause a continued focus on fighting identity
  720. %theft by protecting SSNs rather than developing better authentication
  721. %and incentive schemes \cite{price-privacy}. Similarly we can expect a
  722. %continued use of identification by IP number as long as there is no
  723. %workable alternative.
  724. %[XXX Mention correct DNS-RBL implementation. -NM]
  725. \section{Design choices}
  726. In addition to social issues, Tor also faces some design tradeoffs that must
  727. be investigated as the network develops.
  728. \subsection{Transporting the stream vs transporting the packets}
  729. \label{subsec:stream-vs-packet}
  730. \label{subsec:tcp-vs-ip}
  731. Tor transports streams; it does not tunnel packets.
  732. It has often been suggested that like the old Freedom
  733. network~\cite{freedom21-security}, Tor should
  734. ``obviously'' anonymize IP traffic
  735. at the IP layer. Before this could be done, many issues need to be resolved:
  736. \begin{enumerate}
  737. \setlength{\itemsep}{0mm}
  738. \setlength{\parsep}{0mm}
  739. \item \emph{IP packets reveal OS characteristics.} We would still need to do
  740. IP-level packet normalization, to stop things like TCP fingerprinting
  741. attacks.%There likely exist libraries that can help with this.
  742. This is unlikely to be a trivial task, given the diversity and complexity of
  743. various TCP stacks.
  744. \item \emph{Application-level streams still need scrubbing.} We still need
  745. Tor to be easy to integrate with user-level application-specific proxies
  746. such as Privoxy. So it's not just a matter of capturing packets and
  747. anonymizing them at the IP layer.
  748. \item \emph{Certain protocols will still leak information.} For example, we
  749. must rewrite DNS requests so they are delivered to an unlinkable DNS server
  750. rather than a DNS server at a user's ISP;thus, we must understand the
  751. protocols we are transporting.
  752. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  753. approach that can provide security despite
  754. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  755. never publicly specified.
  756. Also, TLS over UDP is not yet implemented or
  757. specified, though some early work has begun on that~\cite{dtls}.
  758. \item \emph{We'll still need to tune network parameters.} Since the above
  759. encryption system will likely need sequence numbers (and maybe more) to do
  760. replay detection, handle duplicate frames, and so on, we will be reimplementing
  761. a subset of TCP anyway---a notoriously tricky path.
  762. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  763. IDS\@.} Our node operators tell us that exit policies are one of
  764. the main reasons they're willing to run Tor.
  765. Adding an Intrusion Detection System to handle exit policies would
  766. increase the security complexity of Tor, and would likely not work anyway,
  767. as evidenced by the entire field of IDS and counter-IDS papers. Many
  768. potential abuse issues are resolved by the fact that Tor only transports
  769. valid TCP streams (as opposed to arbitrary IP including malformed packets
  770. and IP floods), so exit policies become even \emph{more} important as
  771. we become able to transport IP packets. We also need to compactly
  772. describe exit policies so clients can predict
  773. which nodes will allow which packets to exit.
  774. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  775. support hidden service {\tt{.onion}} addresses (and other special addresses,
  776. like {\tt{.exit}} which lets the user request a particular exit node),
  777. by intercepting the addresses when they are passed to the Tor client.
  778. Doing so at the IP level would require more complex interface between
  779. Tor and local DNS resolver.
  780. \end{enumerate}
  781. This list is discouragingly long, but being able to transport more
  782. protocols obviously has some advantages. It would be good to learn which
  783. items are actual roadblocks and which are easier to resolve than we think.
  784. To be fair, Tor's stream-based approach has run into
  785. stumbling blocks as well. While Tor supports the SOCKS protocol,
  786. which provides a standardized interface for generic TCP proxies, many
  787. applications do not support SOCKS\@. For them we already need to
  788. replace the networking system calls with SOCKS-aware
  789. versions, or run a SOCKS tunnel locally, neither of which is
  790. easy for the average user. %---even with good instructions.
  791. Even when applications can use SOCKS, they often make DNS requests
  792. themselves before handing an IP address to Tor, which advertises
  793. where the user is about to connect.
  794. We are still working on more usable solutions.
  795. %So in order to actually provide good anonymity, we need to make sure that
  796. %users have a practical way to use Tor anonymously. Possibilities include
  797. %writing wrappers for applications to anonymize them automatically; improving
  798. %the applications' support for SOCKS; writing libraries to help application
  799. %writers use Tor properly; and implementing a local DNS proxy to reroute DNS
  800. %requests to Tor so that applications can simply point their DNS resolvers at
  801. %localhost and continue to use SOCKS for data only.
  802. \subsection{Mid-latency}
  803. \label{subsec:mid-latency}
  804. Some users need to resist traffic correlation attacks. Higher-latency
  805. mix-networks introduce variability into message
  806. arrival times: as timing variance increases, timing correlation attacks
  807. require increasingly more data~\cite{e2e-traffic}. Can we improve Tor's
  808. resistance without losing too much usability?
  809. We need to learn whether we can trade a small increase in latency
  810. for a large anonymity increase, or if we'd end up trading a lot of
  811. latency for only a minimal security gain. A trade-off might be worthwhile
  812. even if we
  813. could only protect certain use cases, such as infrequent short-duration
  814. transactions. % To answer this question
  815. We might adapt the techniques of~\cite{e2e-traffic} to a lower-latency mix
  816. network, where the messages are batches of cells in temporally clustered
  817. connections. These large fixed-size batches can also help resist volume
  818. signature attacks~\cite{hintz-pet02}. We could also experiment with traffic
  819. shaping to get a good balance of throughput and security.
  820. %Other padding regimens might supplement the
  821. %mid-latency option; however, we should continue the caution with which
  822. %we have always approached padding lest the overhead cost us too much
  823. %performance or too many volunteers.
  824. We must keep usability in mind too. How much can latency increase
  825. before we drive users away? We've already been forced to increase
  826. latency slightly, as our growing network incorporates more DSL and
  827. cable-modem nodes and more nodes in distant continents. Perhaps we can
  828. harness this increased latency to improve anonymity rather than just
  829. reduce usability. Further, if we let clients label certain circuits as
  830. mid-latency as they are constructed, we could handle both types of traffic
  831. on the same network, giving users a choice between speed and security---and
  832. giving researchers a chance to experiment with parameters to improve the
  833. quality of those choices.
  834. \subsection{Enclaves and helper nodes}
  835. \label{subsec:helper-nodes}
  836. It has long been thought that the best anonymity comes from running your
  837. own node~\cite{tor-design,or-ih96,or-pet00}. This is called using Tor in an
  838. \emph{enclave} configuration. By running Tor clients only on Tor nodes
  839. at the enclave perimeter, enclave configuration can also permit anonymity
  840. protection even when policy or other requiremnts prevent individual machines
  841. within the enclave from running Tor clients~\cite{or-jsac98,or-discex00}.
  842. Of course, Tor's default path length of
  843. three is insufficient for these enclaves, since the entry and/or exit
  844. themselves are sensitive. Tor thus increments the path length by one
  845. for each sensitive endpoint in the circuit.
  846. Enclaves also help to protect against end-to-end attacks, since it's
  847. possible that traffic coming from the node has simply been relayed from
  848. elsewhere. However, if the node has recognizable behavior patterns,
  849. an attacker who runs nodes in the network can triangulate over time to
  850. gain confidence that it is in fact originating the traffic. Wright et
  851. al.~\cite{wright03} introduce the notion of a \emph{helper node}---a
  852. single fixed entry node for each user---to combat this \emph{predecessor
  853. attack}.
  854. However, the attack in~\cite{attack-tor-oak05} shows that simply adding
  855. to the path length, or using a helper node, may not protect an enclave
  856. node. A hostile web server can send constant interference traffic to
  857. all nodes in the network, and learn which nodes are involved in the
  858. circuit (though at least in the current attack, he can't learn their
  859. order). Using randomized path lengths may help some, since the attacker
  860. will never be certain he has identified all nodes in the path, but as
  861. long as the network remains small this attack will still be feasible.
  862. Helper nodes also aim to help Tor clients, because choosing entry and exit
  863. points
  864. randomly and changing them frequently allows an attacker who controls
  865. even a few nodes to eventually link some of their destinations. The goal
  866. is to take the risk once and for all about choosing a bad entry node,
  867. rather than taking a new risk for each new circuit. (Choosing fixed
  868. exit nodes is less useful, since even an honest exit node still doesn't
  869. protect against a hostile website.) But obstacles still remain before
  870. we can implement them.
  871. For one, the literature does not describe how to choose helpers from a list
  872. of nodes that changes over time. If Alice is forced to choose a new entry
  873. helper every $d$ days and $c$ of the $n$ nodes are bad, she can expect
  874. to choose a compromised node around
  875. every $dc/n$ days. Statistically over time this approach only helps
  876. if she is better at choosing honest helper nodes than at choosing
  877. honest nodes. Worse, an attacker with the ability to DoS nodes could
  878. force users to switch helper nodes more frequently and/or remove
  879. other candidate helpers.
  880. %Do general DoS attacks have anonymity implications? See e.g. Adam
  881. %Back's IH paper, but I think there's more to be pointed out here. -RD
  882. % Not sure what you want to say here. -NM
  883. %Game theory for helper nodes: if Alice offers a hidden service on a
  884. %server (enclave model), and nobody ever uses helper nodes, then against
  885. %George+Steven's attack she's totally nailed. If only Alice uses a helper
  886. %node, then she's still identified as the source of the data. If everybody
  887. %uses a helper node (including Alice), then the attack identifies the
  888. %helper node and also Alice, and knows which one is which. If everybody
  889. %uses a helper node (but not Alice), then the attacker figures the real
  890. %source was a client that is using Alice as a helper node. [How's my
  891. %logic here?] -RD
  892. %
  893. % Not sure about the logic. For the attack to work with helper nodes, the
  894. %attacker needs to guess that Alice is running the hidden service, right?
  895. %Otherwise, how can he know to measure her traffic specifically? -NM
  896. %
  897. % In the Murdoch-Danezis attack, the adversary measures all servers. -RD
  898. %point to routing-zones section re: helper nodes to defend against
  899. %big stuff.
  900. \subsection{Location-hidden services}
  901. \label{subsec:hidden-services}
  902. Tor's \emph{rendezvous points}
  903. let users provide TCP services to other Tor users without revealing
  904. the service's location. Since this feature is relatively recent, we describe here
  905. a couple of our early observations from its deployment.
  906. First, our implementation of hidden services seems less hidden than we'd
  907. like, since they are configured on a single client and get used over
  908. and over---particularly because an external adversary can induce them to
  909. produce traffic. They seem the ideal use case for our above discussion
  910. of helper nodes. This insecurity means that they may not be suitable as
  911. a building block for Free Haven~\cite{freehaven-berk} or other anonymous
  912. publishing systems that aim to provide long-term security.
  913. \emph{Hot-swap} hidden services, where more than one location can
  914. provide the service and loss of any one location does not imply a
  915. change in service, would help foil intersection and observation attacks
  916. where an adversary monitors availability of a hidden service and also
  917. monitors whether certain users or servers are online. The design
  918. challenges in providing such services without otherwise compromising
  919. the hidden service's anonymity remain an open problem;
  920. however, see~\cite{move-ndss05}.
  921. In practice, hidden services are used for more than just providing private
  922. access to a web server or IRC server. People are using hidden services
  923. as a poor man's VPN and firewall-buster. Many people want to be able
  924. to connect to the computers in their private network via secure shell,
  925. and rather than playing with dyndns and trying to pierce holes in their
  926. firewall, they run a hidden service on the inside and then rendezvous
  927. with that hidden service externally.
  928. News sites like Bloggers Without Borders (www.b19s.org) are advertising
  929. a hidden-service address on their front page. Doing this can provide
  930. increased robustness if they use the dual-IP approach we describe
  931. in~\cite{tor-design},
  932. but in practice they do it firstly to increase visibility
  933. of the Tor project and their support for privacy, and secondly to offer
  934. a way for their users, using unmodified software, to get end-to-end
  935. encryption and end-to-end authentication to their website.
  936. \subsection{Location diversity and ISP-class adversaries}
  937. \label{subsec:routing-zones}
  938. Anonymity networks have long relied on diversity of node location for
  939. protection against attacks---typically an adversary who can observe a
  940. larger fraction of the network can launch a more effective attack. One
  941. way to achieve dispersal involves growing the network so a given adversary
  942. sees less. Alternately, we can arrange the topology so traffic can enter
  943. or exit at many places (for example, by using a free-route network
  944. like Tor rather than a cascade network like JAP). Lastly, we can use
  945. distributed trust to spread each transaction over multiple jurisdictions.
  946. But how do we decide whether two nodes are in related locations?
  947. Feamster and Dingledine defined a \emph{location diversity} metric
  948. in~\cite{feamster:wpes2004}, and began investigating a variant of location
  949. diversity based on the fact that the Internet is divided into thousands of
  950. independently operated networks called {\em autonomous systems} (ASes).
  951. The key insight from their paper is that while we typically think of a
  952. connection as going directly from the Tor client to the first Tor node,
  953. actually it traverses many different ASes on each hop. An adversary at
  954. any of these ASes can monitor or influence traffic. Specifically, given
  955. plausible initiators and recipients, and given random path selection,
  956. some ASes in the simulation were able to observe 10\% to 30\% of the
  957. transactions (that is, learn both the origin and the destination) on
  958. the deployed Tor network (33 nodes as of June 2004).
  959. The paper concludes that for best protection against the AS-level
  960. adversary, nodes should be in ASes that have the most links to other ASes:
  961. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  962. is safest when it starts or ends in a Tier-1 ISP\@. Therefore, assuming
  963. initiator and responder are both in the U.S., it actually \emph{hurts}
  964. our location diversity to enter or exit from far-flung nodes in
  965. continents like Asia or South America.
  966. Many open questions remain. First, it will be an immense engineering
  967. challenge to get an entire BGP routing table to each Tor client, or to
  968. summarize it sufficiently. Without a local copy, clients won't be
  969. able to safely predict what ASes will be traversed on the various paths
  970. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  971. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  972. determine location diversity; but the above paper showed that in practice
  973. many of the Mixmaster nodes that share a single AS have entirely different
  974. IP prefixes. When the network has scaled to thousands of nodes, does IP
  975. prefix comparison become a more useful approximation?
  976. %
  977. Second, we can take advantage of caching certain content at the
  978. exit nodes, to limit the number of requests that need to leave the
  979. network at all. What about taking advantage of caches like Akamai or
  980. Google~\cite{shsm03}? (Note that they're also well-positioned as global
  981. adversaries.)
  982. %
  983. Third, if we follow the recommendations in~\cite{feamster:wpes2004}
  984. and tailor path selection
  985. to avoid choosing endpoints in similar locations, how much are we hurting
  986. anonymity against larger real-world adversaries who can take advantage
  987. of knowing our algorithm?
  988. %
  989. Lastly, can we use this knowledge to figure out which gaps in our network
  990. would most improve our robustness to this class of attack, and go recruit
  991. new nodes with those ASes in mind?
  992. %Tor's security relies in large part on the dispersal properties of its
  993. %network. We need to be more aware of the anonymity properties of various
  994. %approaches so we can make better design decisions in the future.
  995. \subsection{The China problem}
  996. \label{subsec:china}
  997. Citizens in a variety of countries, such as most recently China and
  998. Iran, are periodically blocked from accessing various sites outside
  999. their country. These users try to find any tools available to allow
  1000. them to get-around these firewalls. Some anonymity networks, such as
  1001. Six-Four~\cite{six-four}, are designed specifically with this goal in
  1002. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  1003. such as Voice of America to set up a network to encourage Internet
  1004. freedom. Even though Tor wasn't
  1005. designed with ubiquitous access to the network in mind, thousands of
  1006. users across the world are trying to use it for exactly this purpose.
  1007. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  1008. Anti-censorship networks hoping to bridge country-level blocks face
  1009. a variety of challenges. One of these is that they need to find enough
  1010. exit nodes---servers on the `free' side that are willing to relay
  1011. arbitrary traffic from users to their final destinations. Anonymizing
  1012. networks including Tor are well-suited to this task, since we have
  1013. already gathered a set of exit nodes that are willing to tolerate some
  1014. political heat.
  1015. The other main challenge is to distribute a list of reachable relays
  1016. to the users inside the country, and give them software to use them,
  1017. without letting the authorities also enumerate this list and block each
  1018. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  1019. addresses (or having them donated), abandoning old addresses as they are
  1020. `used up', and telling a few users about the new ones. Distributed
  1021. anonymizing networks again have an advantage here, in that we already
  1022. have tens of thousands of separate IP addresses whose users might
  1023. volunteer to provide this service since they've already installed and use
  1024. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1025. the Tor protocol separates routing from network discovery \cite{tor-design},
  1026. volunteers could configure their Tor clients
  1027. to generate node descriptors and send them to a special directory
  1028. server that gives them out to dissidents who need to get around blocks.
  1029. Of course, this still doesn't prevent the adversary
  1030. from enumerating all the volunteer relays and blocking them preemptively.
  1031. Perhaps a tiered-trust system could be built where a few individuals are
  1032. given relays' locations, and they recommend other individuals by telling them
  1033. those addresses, thus providing a built-in incentive to avoid letting the
  1034. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1035. might help to bound the number of IP addresses leaked to the adversary. Groups
  1036. like the W3C are looking into using Tor as a component in an overall system to
  1037. help address censorship; we wish them luck.
  1038. %\cite{infranet}
  1039. \section{Scaling}
  1040. \label{sec:scaling}
  1041. Tor is running today with hundreds of nodes and tens of thousands of
  1042. users, but it will certainly not scale to millions.
  1043. Scaling Tor involves three main challenges. First is safe node
  1044. discovery, both bootstrapping -- how a Tor client can robustly find an
  1045. initial node list -- and ongoing -- how a Tor client can learn about
  1046. a fair sample of honest nodes and not let the adversary control his
  1047. circuits (see Section~\ref{subsec:trust-and-discovery}). Second is detecting and handling the speed
  1048. and reliability of the variety of nodes we must use if we want to
  1049. accept many nodes (see Section~\ref{subsec:performance}).
  1050. Since the speed and reliability of a circuit is limited by its worst link,
  1051. we must learn to track and predict performance. Finally, in order to get
  1052. a large set of nodes in the first place, we must address incentives
  1053. for users to carry traffic for others.
  1054. \subsection{Incentives by Design}
  1055. There are three behaviors we need to encourage for each Tor node: relaying
  1056. traffic; providing good throughput and reliability while doing it;
  1057. and allowing traffic to exit the network from that node.
  1058. We encourage these behaviors through \emph{indirect} incentives, that
  1059. is, designing the system and educating users in such a way that users
  1060. with certain goals will choose to relay traffic. One
  1061. main incentive for running a Tor node is social benefit: volunteers
  1062. altruistically donate their bandwidth and time. We also keep public
  1063. rankings of the throughput and reliability of nodes, much like
  1064. seti@home. We further explain to users that they can get plausible
  1065. deniability for any traffic emerging from the same address as a Tor
  1066. exit node, and they can use their own Tor node
  1067. as entry or exit point and be confident it's not run by the adversary.
  1068. Further, users may run a node simply because they need such a network
  1069. to be persistently available and usable.
  1070. And, the value of supporting this exceeds any countervening costs.
  1071. Finally, we can improve the usability and feature set of the software:
  1072. rate limiting support and easy packaging decrease the hassle of
  1073. maintaining a node, and our configurable exit policies allow each
  1074. operator to advertise a policy describing the hosts and ports to which
  1075. he feels comfortable connecting.
  1076. To date these appear to have been adequate. As the system scales or as
  1077. new issues emerge, however, we may also need to provide
  1078. \emph{direct} incentives:
  1079. providing payment or other resources in return for high-quality service.
  1080. Paying actual money is problematic: decentralized e-cash systems are
  1081. not yet practical, and a centralized collection system not only reduces
  1082. robustness, but also has failed in the past (the history of commercial
  1083. anonymizing networks is littered with failed attempts). A more promising
  1084. option is to use a tit-for-tat incentive scheme: provide better service
  1085. to nodes that have provided good service to you.
  1086. Unfortunately, such an approach introduces new anonymity problems.
  1087. There are many surprising ways for nodes to game the incentive and
  1088. reputation system to undermine anonymity because such systems are
  1089. designed to encourage fairness in storage or bandwidth usage not
  1090. fairness of provided anonymity. An adversary can attract more traffic
  1091. by performing well or can provide targeted differential performance to
  1092. individual users to undermine their anonymity. Typically a user who
  1093. chooses evenly from all options is most resistant to an adversary
  1094. targeting him, but that approach precludes the efficient use
  1095. of heterogeneous nodes.
  1096. %When a node (call him Steve) performs well for Alice, does Steve gain
  1097. %reputation with the entire system, or just with Alice? If the entire
  1098. %system, how does Alice tell everybody about her experience in a way that
  1099. %prevents her from lying about it yet still protects her identity? If
  1100. %Steve's behavior only affects Alice's behavior, does this allow Steve to
  1101. %selectively perform only for Alice, and then break her anonymity later
  1102. %when somebody (presumably Alice) routes through his node?
  1103. A possible solution is a simplified approach to the tit-for-tat
  1104. incentive scheme based on two rules: (1) each node should measure the
  1105. service it receives from adjacent nodes, and provide service relative
  1106. to the received service, but (2) when a node is making decisions that
  1107. affect its own security (e.g. when building a circuit for its own
  1108. application connections), it should choose evenly from a sufficiently
  1109. large set of nodes that meet some minimum service threshold
  1110. \cite{casc-rep}. This approach allows us to discourage bad service
  1111. without opening Alice up as much to attacks. All of this requires
  1112. further study.
  1113. %XXX rewrite the above so it sounds less like a grant proposal and
  1114. %more like a "if somebody were to try to solve this, maybe this is a
  1115. %good first step".
  1116. %We should implement the above incentive scheme in the
  1117. %deployed Tor network, in conjunction with our plans to add the necessary
  1118. %associated scalability mechanisms. We will do experiments (simulated
  1119. %and/or real) to determine how much the incentive system improves
  1120. %efficiency over baseline, and also to determine how far we are from
  1121. %optimal efficiency (what we could get if we ignored the anonymity goals).
  1122. \subsection{Trust and discovery}
  1123. \label{subsec:trust-and-discovery}
  1124. The published Tor design adopted a deliberately simplistic design for
  1125. authorizing new nodes and informing clients about Tor nodes and their status.
  1126. In preliminary Tor designs, all nodes periodically uploaded a
  1127. signed description
  1128. of their locations, keys, and capabilities to each of several well-known {\it
  1129. directory servers}. These directory servers constructed a signed summary
  1130. of all known Tor nodes (a ``directory''), and a signed statement of which
  1131. nodes they
  1132. believed to be operational at any given time (a ``network status''). Clients
  1133. periodically downloaded a directory in order to learn the latest nodes and
  1134. keys, and more frequently downloaded a network status to learn which nodes were
  1135. likely to be running. Tor nodes also operate as directory caches, in order to
  1136. lighten the bandwidth on the authoritative directory servers.
  1137. In order to prevent Sybil attacks (wherein an adversary signs up many
  1138. purportedly independent nodes in order to increase her chances of observing
  1139. a stream as it enters and leaves the network), the early Tor directory design
  1140. required the operators of the authoritative directory servers to manually
  1141. approve new nodes. Unapproved nodes were included in the directory,
  1142. but clients
  1143. did not use them at the start or end of their circuits. In practice,
  1144. directory administrators performed little actual verification, and tended to
  1145. approve any Tor node whose operator could compose a coherent email.
  1146. This procedure
  1147. may have prevented trivial automated Sybil attacks, but would do little
  1148. against a clever and determined attacker.
  1149. There are a number of flaws in this system that need to be addressed as we
  1150. move forward. They include:
  1151. \begin{tightlist}
  1152. \item Each directory server represents an independent point of failure; if
  1153. any one were compromised, it could immediately compromise all of its users
  1154. by recommending only compromised nodes.
  1155. \item The more nodes join the network, the more unreasonable it
  1156. becomes to expect clients to know about them all. Directories
  1157. become infeasibly large, and downloading the list of nodes becomes
  1158. burdensome.
  1159. \item The validation scheme may do as much harm as it does good. It is not
  1160. only incapable of preventing clever attackers from mounting Sybil attacks,
  1161. but may deter node operators from joining the network. (For instance, if
  1162. they expect the validation process to be difficult, or if they do not share
  1163. any languages in common with the directory server operators.)
  1164. \end{tightlist}
  1165. We could try to move the system in several directions, depending on our
  1166. choice of threat model and requirements. If we did not need to increase
  1167. network capacity in order to support more users, we could simply
  1168. adopt even stricter validation requirements, and reduce the number of
  1169. nodes in the network to a trusted minimum.
  1170. But, we can only do that if can simultaneously make node capacity
  1171. scale much more than we anticipate to be feasible soon, and if we can find
  1172. entities willing to run such nodes, an equally daunting prospect.
  1173. In order to address the first two issues, it seems wise to move to a system
  1174. including a number of semi-trusted directory servers, no one of which can
  1175. compromise a user on its own. Ultimately, of course, we cannot escape the
  1176. problem of a first introducer: since most users will run Tor in whatever
  1177. configuration the software ships with, the Tor distribution itself will
  1178. remain a potential single point of failure so long as it includes the seed
  1179. keys for directory servers, a list of directory servers, or any other means
  1180. to learn which nodes are on the network. But omitting this information
  1181. from the Tor distribution would only delegate the trust problem to the
  1182. individual users, most of whom are presumably less informed about how to make
  1183. trust decisions than the Tor developers.
  1184. %Network discovery, sybil, node admission, scaling. It seems that the code
  1185. %will ship with something and that's our trust root. We could try to get
  1186. %people to build a web of trust, but no. Where we go from here depends
  1187. %on what threats we have in mind. Really decentralized if your threat is
  1188. %RIAA; less so if threat is to application data or individuals or...
  1189. \subsection{Measuring performance and capacity}
  1190. \label{subsec:performance}
  1191. One of the paradoxes with engineering an anonymity network is that we'd like
  1192. to learn as much as we can about how traffic flows so we can improve the
  1193. network, but we want to prevent others from learning how traffic flows in
  1194. order to trace users' connections through the network. Furthermore, many
  1195. mechanisms that help Tor run efficiently
  1196. require measurements about the network.
  1197. Currently, nodes try to deduce their own available bandwidth (based on how
  1198. much traffic they have been able to transfer recently) and include this
  1199. information in the descriptors they upload to the directory. Clients
  1200. choose servers weighted by their bandwidth, neglecting really slow
  1201. servers and capping the influence of really fast ones.
  1202. %
  1203. This is, of course, eminently cheatable. A malicious node can get a
  1204. disproportionate amount of traffic simply by claiming to have more bandwidth
  1205. than it does. But better mechanisms have their problems. If bandwidth data
  1206. is to be measured rather than self-reported, it is usually possible for
  1207. nodes to selectively provide better service for the measuring party, or
  1208. sabotage the measured value of other nodes. Complex solutions for
  1209. mix networks have been proposed, but do not address the issues
  1210. completely~\cite{mix-acc,casc-rep}.
  1211. Even with no cheating, network measurement is complex. It is common
  1212. for views of a node's latency and/or bandwidth to vary wildly between
  1213. observers. Further, it is unclear whether total bandwidth is really
  1214. the right measure; perhaps clients should instead be considering nodes
  1215. based on unused bandwidth or observed throughput.
  1216. % XXXX say more here?
  1217. %How to measure performance without letting people selectively deny service
  1218. %by distinguishing pings. Heck, just how to measure performance at all. In
  1219. %practice people have funny firewalls that don't match up to their exit
  1220. %policies and Tor doesn't deal.
  1221. %Network investigation: Is all this bandwidth publishing thing a good idea?
  1222. %How can we collect stats better? Note weasel's smokeping, at
  1223. %http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  1224. %which probably gives george and steven enough info to break tor?
  1225. Even if we can collect and use this network information effectively, we need
  1226. to make sure that it is not more useful to attackers than to us. While it
  1227. seems plausible that bandwidth data alone is not enough to reveal
  1228. sender-recipient connections under most circumstances, it could certainly
  1229. reveal the path taken by large traffic flows under low-usage circumstances.
  1230. \subsection{Non-clique topologies}
  1231. Tor's comparatively weak threat model makes it easier to scale than
  1232. other mix net
  1233. designs. High-latency mix networks need to avoid partitioning attacks, where
  1234. network splits prevent users of the separate partitions from providing cover
  1235. for each other. In Tor, however, we assume that the adversary cannot
  1236. cheaply observe nodes at will, so even if the network becomes split, the
  1237. users do not necessarily receive much less protection.
  1238. Thus, a simple possibility when the scale of a Tor network
  1239. exceeds some size is to simply split it. Care could be taken in
  1240. allocating which nodes go to which network along the lines of
  1241. \cite{casc-rep} to insure that collaborating hostile nodes are not
  1242. able to gain any advantage in network splitting that they do not
  1243. already have in joining a network.
  1244. If the network is split,
  1245. a client does not need to use just one of the two resulting networks.
  1246. Alice could use either of them, and it would not be difficult to make
  1247. the Tor client able to access several such network on a per circuit
  1248. basis. More analysis is needed; we simply note here that splitting
  1249. a Tor network is an easy way to achieve moderate scalability and that
  1250. it does not necessarily have the same implications as splitting a mixnet.
  1251. Alternatively, we can try to scale a single Tor network. Some issues for
  1252. scaling include restricting the number of sockets and the amount of bandwidth
  1253. used by each node. The number of sockets is determined by the network's
  1254. connectivity and the number of users, while bandwidth capacity is determined
  1255. by the total bandwidth of nodes on the network. The simplest solution to
  1256. bandwidth capacity is to add more nodes, since adding a Tor node of any
  1257. feasible bandwidth will increase the traffic capacity of the network. So as
  1258. a first step to scaling, we should focus on making the network tolerate more
  1259. nodes, by reducing the interconnectivity of the nodes; later we can reduce
  1260. overhead associated with directories, discovery, and so on.
  1261. By reducing the connectivity of the network we increase the total number of
  1262. nodes that the network can contain. Danezis~\cite{danezis-pets03} considers
  1263. the anonymity implications of restricting routes on mix networks, and
  1264. recommends an approach based on expander graphs (where any subgraph is likely
  1265. to have many neighbors). It is not immediately clear that this approach will
  1266. extend to Tor, which has a weaker threat model but higher performance
  1267. requirements than the network considered. Instead of analyzing the
  1268. probability of an attacker's viewing whole paths, we will need to examine the
  1269. attacker's likelihood of compromising the endpoints of a Tor circuit through
  1270. a sparse network.
  1271. % Nick edits these next 2 grafs.
  1272. To make matters simpler, Tor may not need an expander graph per se: it
  1273. may be enough to have a single subnet that is highly connected. As an
  1274. example, assume fifty nodes of relatively high traffic capacity. This
  1275. \emph{center} forms a clique. Assume each center node can
  1276. handle 200 connections to other nodes (including the other ones in the
  1277. center). Assume every noncenter node connects to three nodes in the
  1278. center and anyone out of the center that they want to. Then the
  1279. network easily scales to c. 2500 nodes with commensurate increase in
  1280. bandwidth. There are many open questions: how directory information
  1281. is distributed (presumably information about the center nodes could
  1282. be given to any new nodes with their codebase), whether center nodes
  1283. will need to function as a `backbone', etc. As above the point is
  1284. that this would create problems for the expected anonymity for a mixnet,
  1285. but for a low-latency network where anonymity derives largely from
  1286. the edges, it may be feasible.
  1287. Another point is that we already have a non-clique topology.
  1288. Individuals can set up and run Tor nodes without informing the
  1289. directory servers. This will allow, e.g., dissident groups to run a
  1290. local Tor network of such nodes that connects to the public Tor
  1291. network. This network is hidden behind the Tor network, and its
  1292. only visible connection to Tor is at those points where it connects.
  1293. As far as the public network, or anyone observing it, is concerned,
  1294. they are running clients.
  1295. \section{The Future}
  1296. \label{sec:conclusion}
  1297. Tor is the largest and most diverse low-latency anonymity network
  1298. available, but we are still in the beginning stages of deployment. Several
  1299. major questions remain.
  1300. First, will our volunteer-based approach to sustainability work in the
  1301. long term? As we add more features and destabilize the network, the
  1302. developers spend a lot of time keeping the server operators happy. Even
  1303. though Tor is free software, the network would likely stagnate and die at
  1304. this stage if the developers stopped actively working on it. We may get
  1305. an unexpected boon from the fact that we're a general-purpose overlay
  1306. network: as Tor grows more popular, other groups who need an overlay
  1307. network on the Internet are starting to adapt Tor to their needs.
  1308. %
  1309. Second, Tor is only one of many components that preserve privacy online.
  1310. For applications where it is desirable to
  1311. keep identifying information out of application traffic, someone must build
  1312. more and better protocol-aware proxies that are usable by ordinary people.
  1313. %
  1314. Third, we need to gain a reputation for social good, and learn how to
  1315. coexist with the variety of Internet services and their established
  1316. authentication mechanisms. We can't just keep escalating the blacklist
  1317. standoff forever.
  1318. %
  1319. Fourth, the current Tor
  1320. architecture does not scale even to handle current user demand. We must
  1321. find designs and incentives to let some clients relay traffic too, without
  1322. sacrificing too much anonymity.
  1323. These are difficult and open questions, yet choosing not to solve them
  1324. means leaving most users to a less secure network or no anonymizing
  1325. network at all.
  1326. \bibliographystyle{plain} \bibliography{tor-design}
  1327. \clearpage
  1328. \appendix
  1329. \begin{figure}[t]
  1330. %\unitlength=1in
  1331. \centering
  1332. %\begin{picture}(6.0,2.0)
  1333. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1334. %\end{picture}
  1335. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1336. \caption{Number of Tor nodes over time, through January 2005. Lowest
  1337. line is number of exit
  1338. nodes that allow connections to port 80. Middle line is total number of
  1339. verified (registered) Tor nodes. The line above that represents nodes
  1340. that are running but not yet registered.}
  1341. \label{fig:graphnodes}
  1342. \end{figure}
  1343. \begin{figure}[t]
  1344. \centering
  1345. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1346. \caption{The sum of traffic reported by each node over time, through
  1347. January 2005. 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}
  1353. %Making use of nodes with little bandwidth, or high latency/packet loss.
  1354. %Running Tor nodes behind NATs, behind great-firewalls-of-China, etc.
  1355. %Restricted routes. How to propagate to everybody the topology? BGP
  1356. %style doesn't work because we don't want just *one* path. Point to
  1357. %Geoff's stuff.