challenges.tex 81 KB

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