challenges2.tex 82 KB

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  19. \begin{document}
  20. \title{Design challenges and social factors 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. We describe the design
  31. philosophy of Tor (the third-generation onion routing network), and,
  32. drawing on our experiences deploying Tor, we describe social
  33. challenges and related technical issues that must be faced in
  34. building, deploying, and sustaining a scalable, distributed,
  35. low-latency anonymity network.
  36. \end{abstract}
  37. \section{Introduction}
  38. % Your network is not practical unless it is sustainable and distributed.
  39. Anonymous communication is full of surprises. This article describes
  40. Tor, a low-latency general-purpose anonymous communication system, and
  41. discusses some unexpected challenges arising from our experiences
  42. deploying Tor. We will discuss
  43. some of the difficulties we have experienced and how we have met them (or how
  44. we plan to meet them, if we know).
  45. % We also discuss some less
  46. % troublesome open problems that we must nevertheless eventually address.
  47. %We will describe both those future challenges that we intend to explore and
  48. %those that we have decided not to explore and why.
  49. Tor is an overlay network for anonymizing TCP streams over the
  50. Internet~\cite{tor-design}. It addresses limitations in earlier Onion
  51. Routing designs~\cite{or-ih96,or-jsac98,or-discex00,or-pet00} by adding
  52. perfect forward secrecy, congestion control, directory servers, data
  53. integrity,
  54. %configurable exit policies, Huh? That was part of the gen. 1 design -PFS
  55. and a revised design for location-hidden services using
  56. rendezvous points. Tor works on the real-world Internet, requires no special
  57. privileges or kernel modifications, requires little synchronization or
  58. coordination between nodes, and provides a reasonable trade-off between
  59. anonymity, usability, and efficiency.
  60. We deployed the public Tor network in October 2003; since then it has
  61. grown to over nine hundred volunteer-operated nodes worldwide
  62. and over 100 megabytes average traffic per second from hundreds of
  63. thousands of concurrent users.
  64. Tor's research strategy has focused on deploying
  65. a network to as many users as possible; thus, we have resisted designs that
  66. would compromise deployability by imposing high resource demands on node
  67. operators, and designs that would compromise usability by imposing
  68. unacceptable restrictions on which applications we support. Although this
  69. strategy has drawbacks (including a weakened threat model, as
  70. discussed below), it has made it possible for Tor to serve many
  71. hundreds of thousands of users and attract funding from diverse
  72. sources whose goals range from security on a national scale down to
  73. individual liberties.
  74. In~\cite{tor-design} we gave an overall view of Tor's design and
  75. goals. Here we review that design at a higher level and describe
  76. some policy and social issues that we face as
  77. we continue deployment. Though we will discuss technical responses to
  78. these, we do not in this article discuss purely technical challenges
  79. facing Tor (e.g., transport protocol, resource scaling issues, moving
  80. to non-clique topologies, performance, etc.), nor do we even cover
  81. all of the social issues: we simply touch on some of the most salient of these.
  82. Also, rather than providing complete solutions to every problem, we
  83. instead lay out the challenges and constraints that we have observed while
  84. deploying Tor. In doing so, we aim to provide a research agenda
  85. of general interest to projects attempting to build
  86. and deploy practical, usable anonymity networks in the wild.
  87. %While the Tor design paper~\cite{tor-design} gives an overall view its
  88. %design and goals,
  89. %this paper describes the policy and technical issues that Tor faces as
  90. %we continue deployment. Rather than trying to provide complete solutions
  91. %to every problem here, we lay out the assumptions and constraints
  92. %that we have observed through deploying Tor in the wild. In doing so, we
  93. %aim to create a research agenda for others to
  94. %help in addressing these issues.
  95. % Section~\ref{sec:what-is-tor} gives an
  96. %overview of the Tor
  97. %design and ours goals. Sections~\ref{sec:crossroads-policy}
  98. %and~\ref{sec:crossroads-design} go on to describe the practical challenges,
  99. %both policy and technical respectively,
  100. %that stand in the way of moving
  101. %from a practical useful network to a practical useful anonymous network.
  102. %\section{What Is Tor}
  103. \section{Background}
  104. Here we give a basic overview of the Tor design and its properties, and
  105. compare Tor to other low-latency anonymity designs.
  106. \subsection{Tor, threat models, and distributed trust}
  107. \label{sec:what-is-tor}
  108. %Here we give a basic overview of the Tor design and its properties. For
  109. %details on the design, assumptions, and security arguments, we refer
  110. %the reader to the Tor design paper~\cite{tor-design}.
  111. Tor provides \emph{forward privacy}, so that users can connect to
  112. Internet sites without revealing their logical or physical locations
  113. to those sites or to observers. It also provides \emph{location-hidden
  114. services}, so that servers can support authorized users without
  115. giving an effective vector for physical or online attackers.
  116. Tor provides these protections even when a portion of its
  117. infrastructure is compromised.
  118. To connect to a remote server via Tor, the client software learns a signed
  119. list of Tor nodes from one of several central \emph{directory servers}, and
  120. incrementally creates a private pathway or \emph{circuit} of encrypted
  121. connections through authenticated Tor nodes on the network, negotiating a
  122. separate set of encryption keys for each hop along the circuit. The circuit
  123. is extended one node at a time, and each node along the way knows only the
  124. immediately previous and following nodes in the circuit, so no individual Tor
  125. node knows the complete path that each fixed-sized data packet (or
  126. \emph{cell}) will take.
  127. %Because each node sees no more than one hop in the
  128. %circuit,
  129. Thus, neither an eavesdropper nor a compromised node can
  130. see both the connection's source and destination. Later requests use a new
  131. circuit, to complicate long-term linkability between different actions by
  132. a single user.
  133. Tor also helps servers hide their locations while
  134. providing services such as web publishing or instant
  135. messaging. Using ``rendezvous points'', other Tor users can
  136. connect to these authenticated hidden services, neither one learning the
  137. other's network identity.
  138. Tor attempts to anonymize the transport layer, not the application layer.
  139. This approach is useful for applications such as SSH
  140. where authenticated communication is desired. However, when anonymity from
  141. those with whom we communicate is desired,
  142. application protocols that include personally identifying information need
  143. additional application-level scrubbing proxies, such as
  144. Privoxy~\cite{privoxy} for HTTP\@. Furthermore, Tor does not relay arbitrary
  145. IP packets; it only anonymizes TCP streams and DNS requests.
  146. %, and only supports
  147. %connections via SOCKS
  148. %(but see Section~\ref{subsec:tcp-vs-ip}).
  149. Most node operators do not want to allow arbitrary TCP traffic. % to leave
  150. %their server.
  151. To address this, Tor provides \emph{exit policies} so
  152. each exit node can block the IP addresses and ports it is unwilling to allow.
  153. Tor nodes advertise their exit policies to the directory servers, so that
  154. client can tell which nodes will support their connections.
  155. As of this writing, the Tor network has grown to around nine hundred nodes
  156. on four continents, with a total average load exceeding 100 MB/s and
  157. a total capacity exceeding %1Gbit/s.
  158. \\***What's the current capacity? -PFS***\\
  159. %Appendix A
  160. %shows a graph of the number of working nodes over time, as well as a
  161. %graph of the number of bytes being handled by the network over time.
  162. %The network is now sufficiently diverse for further development
  163. %and testing; but of course we always encourage new nodes
  164. %to join.
  165. Building from earlier versions of onion routing developed at NRL,
  166. Tor was researched and developed by NRL and FreeHaven under
  167. funding by ONR and DARPA for use in securing government
  168. communications. Continuing development and deployment has also been
  169. funded by the Omidyar Network, the Electronic Frontier Foundation for use
  170. in maintaining civil liberties for ordinary citizens online, and the
  171. International Broadcasting Bureau and Reporters without Borders to combat
  172. blocking and censorship on the Internet. As we will see below,
  173. this wide variety of interests helps maintain both the stability and
  174. the security of the network.
  175. % The Tor
  176. %protocol was chosen
  177. %for the anonymizing layer in the European Union's PRIME directive to
  178. %help maintain privacy in Europe.
  179. %The AN.ON project in Germany
  180. %has integrated an independent implementation of the Tor protocol into
  181. %their popular Java Anon Proxy anonymizing client.
  182. \medskip
  183. \noindent
  184. {\bf Threat models and design philosophy.}
  185. The ideal Tor network would be practical, useful and anonymous. When
  186. trade-offs arise between these properties, Tor's research strategy has been
  187. to remain useful enough to attract many users,
  188. and practical enough to support them. Only subject to these
  189. constraints do we try to maximize
  190. anonymity.\footnote{This is not the only possible
  191. direction in anonymity research: designs exist that provide more anonymity
  192. than Tor at the expense of significantly increased resource requirements, or
  193. decreased flexibility in application support (typically because of increased
  194. latency). Such research does not typically abandon aspirations toward
  195. deployability or utility, but instead tries to maximize deployability and
  196. utility subject to a certain degree of structural anonymity (structural because
  197. usability and practicality affect usage which affects the actual anonymity
  198. provided by the network \cite{econymics,back01}).}
  199. %{We believe that these
  200. %approaches can be promising and useful, but that by focusing on deploying a
  201. %usable system in the wild, Tor helps us experiment with the actual parameters
  202. %of what makes a system ``practical'' for volunteer operators and ``useful''
  203. %for home users, and helps illuminate undernoticed issues which any deployed
  204. %volunteer anonymity network will need to address.}
  205. Because of our strategy, Tor has a weaker threat model than many designs in
  206. the literature. In particular, because we
  207. support interactive communications without impractically expensive padding,
  208. we fall prey to a variety
  209. of intra-network~\cite{back01,attack-tor-oak05,flow-correlation04,hs-attack}
  210. and
  211. end-to-end~\cite{danezis:pet2004,SS03} anonymity-breaking attacks.
  212. Tor does not attempt to defend against a global observer. In general, an
  213. attacker who can measure both ends of a connection through the Tor network
  214. % I say 'measure' rather than 'observe', to encompass murdoch-danezis
  215. % style attacks. -RD
  216. can correlate the timing and volume of data on that connection as it enters
  217. and leaves the network, and so link communication partners.
  218. Known solutions to this attack would seem to require introducing a
  219. prohibitive degree of traffic padding between the user and the network, or
  220. introducing an unacceptable degree of latency.
  221. Also, it is not clear that these methods would
  222. work at all against a minimally active adversary who could introduce timing
  223. patterns or additional traffic. Thus, Tor only attempts to defend against
  224. external observers who cannot observe both sides of a user's connections.
  225. Against internal attackers who sign up Tor nodes, the situation is more
  226. complicated. In the simplest case, if an adversary has compromised $c$ of
  227. $n$ nodes on the Tor network, then the adversary will be able to compromise
  228. a random circuit with probability $\frac{c^2}{n^2}$~\cite{or-pet00}
  229. (since the circuit
  230. initiator chooses hops randomly). But there are
  231. complicating factors:
  232. (1)~If the user continues to build random circuits over time, an adversary
  233. is pretty certain to see a statistical sample of the user's traffic, and
  234. thereby can build an increasingly accurate profile of her behavior.
  235. (2)~An adversary who controls a popular service outside the Tor network
  236. can be certain to observe all connections to that service; he
  237. can therefore trace connections to that service with probability
  238. $\frac{c}{n}$.
  239. (3)~Users do not in fact choose nodes with uniform probability; they
  240. favor nodes with high bandwidth or uptime, and exit nodes that
  241. permit connections to their favorite services.
  242. We demonstrated the severity of these problems in experiments on the
  243. live Tor network in 2006~\cite{hsattack} and introduced \emph{entry
  244. guards} as a means to curtail them. By choosing entry nodes from
  245. a small persistent subset, it becomes difficult for an adversary to
  246. increase the number of circuits observed entering the network from any
  247. given client simply by causing
  248. numerous connections or by watching compromised nodes over time.% (See
  249. %also Section~\ref{subsec:routing-zones} for discussion of larger
  250. %adversaries and our dispersal goals.)
  251. % I'm trying to make this paragraph work without reference to the
  252. % analysis/confirmation distinction, which we haven't actually introduced
  253. % yet, and which we realize isn't very stable anyway. Also, I don't want to
  254. % deprecate these attacks if we can't demonstrate that they don't work, since
  255. % in case they *do* turn out to work well against Tor, we'll look pretty
  256. % foolish. -NM
  257. More powerful attacks may exist. In \cite{hintz-pet02} it was
  258. shown that an attacker who can catalog data volumes of popular
  259. responder destinations (say, websites with consistent data volumes) may not
  260. need to
  261. observe both ends of a stream to learn source-destination links for those
  262. responders. Entry guards should complicate such attacks as well.
  263. Similarly, latencies of going through various routes can be
  264. cataloged~\cite{back01} to connect endpoints.
  265. % Also, \cite{kesdogan:pet2002} takes the
  266. % attack another level further, to narrow down where you could be
  267. % based on an intersection attack on subpages in a website. -RD
  268. It has not yet been shown whether these attacks will succeed or fail
  269. in the presence of the variability and volume quantization introduced by the
  270. Tor network, but it seems likely that these factors will at best delay
  271. the time and data needed for success
  272. rather than prevent the attacks completely.
  273. \workingnote{
  274. Along similar lines, the same paper suggests a ``clogging
  275. attack'' in which the throughput on a circuit is observed to slow
  276. down when an adversary clogs the right nodes with his own traffic.
  277. To determine the nodes in a circuit this attack requires the ability
  278. to continuously monitor the traffic exiting the network on a circuit
  279. that is up long enough to probe all network nodes in binary fashion.
  280. % Though somewhat related, clogging and interference are really different
  281. % attacks with different assumptions about adversary distribution and
  282. % capabilities as well as different techniques. -pfs
  283. Murdoch and Danezis~\cite{attack-tor-oak05} show a practical
  284. interference attack against portions of
  285. the fifty node Tor network as deployed in mid 2004.
  286. An outside attacker can actively trace a circuit through the Tor network
  287. by observing changes in the latency of his
  288. own traffic sent through various Tor nodes. This can be done
  289. simultaneously at multiple nodes; however, like clogging,
  290. this attack only reveals
  291. the Tor nodes in the circuit, not initiator and responder addresses,
  292. so it is still necessary to discover the endpoints to complete an
  293. effective attack. The the size and diversity of the Tor network have
  294. increased many fold since then, and it is unknown if the attacks
  295. can scale to the current Tor network.
  296. }
  297. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  298. %the last hop is not $c/n$ since that doesn't take the destination (website)
  299. %into account. so in cases where the adversary does not also control the
  300. %final destination we're in good shape, but if he *does* then we'd be better
  301. %off with a system that lets each hop choose a path.
  302. %
  303. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  304. % dest, we would be just as well off with such as system.'' ? If not, why
  305. % not? -nm
  306. % Sure. In fact, better off, since they seem to scale more easily. -rd
  307. %Murdoch and Danezis describe an attack
  308. %\cite{attack-tor-oak05} that lets an attacker determine the nodes used
  309. %in a circuit; yet s/he cannot identify the initiator or responder,
  310. %e.g., client or web server, through this attack. So the endpoints
  311. %remain secure, which is the goal. It is conceivable that an
  312. %adversary could attack or set up observation of all connections
  313. %to an arbitrary Tor node in only a few minutes. If such an adversary
  314. %were to exist, s/he could use this probing to remotely identify a node
  315. %for further attack. Of more likely immediate practical concern
  316. %an adversary with active access to the responder traffic
  317. %wants to keep a circuit alive long enough to attack an identified
  318. %node. Thus it is important to prevent the responding end of the circuit
  319. %from keeping it open indefinitely.
  320. %Also, someone could identify nodes in this way and if in their
  321. %jurisdiction, immediately get a subpoena (if they even need one)
  322. %telling the node operator(s) that she must retain all the active
  323. %circuit data she now has.
  324. %Further, the enclave model, which had previously looked to be the most
  325. %generally secure, seems particularly threatened by this attack, since
  326. %it identifies endpoints when they're also nodes in the Tor network:
  327. %see Section~\ref{subsec:helper-nodes} for discussion of some ways to
  328. %address this issue.
  329. \medskip
  330. \noindent
  331. {\bf Distributed trust.}
  332. In practice Tor's threat model is based on
  333. dispersal and diversity.
  334. Our defense lies in having a diverse enough set of nodes
  335. to prevent most real-world
  336. adversaries from being in the right places to attack users,
  337. by distributing each transaction
  338. over several nodes in the network. This ``distributed trust'' approach
  339. means the Tor network can be safely operated and used by a wide variety
  340. of mutually distrustful users, providing sustainability and security.
  341. %than some previous attempts at anonymizing networks.
  342. No organization can achieve this security on its own. If a single
  343. corporation or government agency were to build a private network to
  344. protect its operations, any connections entering or leaving that network
  345. would be obviously linkable to the controlling organization. The members
  346. and operations of that agency would be easier, not harder, to distinguish.
  347. Instead, to protect our networks from traffic analysis, we must
  348. collaboratively blend the traffic from many organizations and private
  349. citizens, so that an eavesdropper can't tell which users are which,
  350. and who is looking for what information. %By bringing more users onto
  351. %the network, all users become more secure~\cite{econymics}.
  352. %[XXX I feel uncomfortable saying this last sentence now. -RD]
  353. %[So, I took it out. I think we can do without it. -PFS]
  354. The Tor network has a broad range of users, including ordinary citizens
  355. concerned about their privacy, corporations
  356. who don't want to reveal information to their competitors, and law
  357. enforcement and government intelligence agencies who need
  358. to do operations on the Internet without being noticed.
  359. Naturally, organizations will not want to depend on others for their
  360. security. If most participating providers are reliable, Tor tolerates
  361. some hostile infiltration of the network. For maximum protection,
  362. the Tor design includes an enclave approach that lets data be encrypted
  363. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  364. hasn't been read or modified. This even works for Internet services that
  365. don't have built-in encryption and authentication, such as unencrypted
  366. HTTP or chat, and it requires no modification of those services.
  367. %\subsection{Related work}
  368. Tor differs from other deployed systems for traffic analysis resistance
  369. in its security and flexibility. Mix networks such as
  370. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  371. gain the highest degrees of anonymity at the expense of introducing highly
  372. variable delays, making them unsuitable for applications such as web
  373. browsing. Commercial single-hop
  374. proxies~\cite{anonymizer} can provide good performance, but
  375. a single compromise can expose all users' traffic, and a single-point
  376. eavesdropper can perform traffic analysis on the entire network.
  377. %Also, their proprietary implementations place any infrastructure that
  378. %depends on these single-hop solutions at the mercy of their providers'
  379. %financial health as well as network security.
  380. The Java
  381. Anon Proxy (JAP)~\cite{web-mix} provides similar functionality to Tor but
  382. handles only web browsing rather than all TCP\@. Because all traffic
  383. passes through fixed ``cascades'' for which the endpoints are predictable,
  384. an adversary can know where to watch for traffic analysis from particular
  385. clients or to particular web servers. The design calls for padding to
  386. complicate this, although it does not appear to be implemented.
  387. %Some peer-to-peer file-sharing overlay networks such as
  388. %Freenet~\cite{freenet} and Mute~\cite{mute}
  389. The Freedom
  390. network from Zero-Knowledge Systems~\cite{freedom21-security}
  391. was even more flexible than Tor in
  392. transporting arbitrary IP packets, and also supported
  393. pseudonymity in addition to anonymity; but it had
  394. a different approach to sustainability (collecting money from users
  395. and paying ISPs to run Tor nodes), and was eventually shut down due to financial
  396. load. Finally, %potentially more scalable
  397. % [I had added 'potentially' because the scalability of these designs
  398. % is not established, and I am uncomfortable making the
  399. % bolder unmodified assertion. Roger took 'potentially' out.
  400. % Here's an attempt at more neutral wording -pfs]
  401. peer-to-peer designs that are intended to be more scalable,
  402. for example Tarzan~\cite{tarzan:ccs02} and
  403. MorphMix~\cite{morphmix:fc04}, have been proposed in the literature but
  404. have not been fielded. These systems differ somewhat
  405. in threat model and presumably practical resistance to threats.
  406. Note that MorphMix differs from Tor only in
  407. node discovery and circuit setup; so Tor's architecture is flexible
  408. enough to contain a MorphMix experiment. Recently,
  409. Tor has adopted from MorphMix the approach of making it harder to
  410. own both ends of a circuit by requiring that nodes be chosen from
  411. different /16 subnets. This requires
  412. an adversary to own nodes in multiple address ranges to even have the
  413. possibility of observing both ends of a circuit. We direct the
  414. interested reader to~\cite{tor-design} for a more in-depth review of
  415. related work.
  416. %XXXX six-four. crowds. i2p.
  417. %XXXX
  418. %have a serious discussion of morphmix's assumptions, since they would
  419. %seem to be the direct competition. in fact tor is a flexible architecture
  420. %that would encompass morphmix, and they're nearly identical except for
  421. %path selection and node discovery. and the trust system morphmix has
  422. %seems overkill (and/or insecure) based on the threat model we've picked.
  423. % this para should probably move to the scalability / directory system. -RD
  424. % Nope. Cut for space, except for small comment added above -PFS
  425. \section{Social challenges}
  426. Many of the issues the Tor project needs to address extend beyond
  427. system design and technology development. In particular, the
  428. Tor project's \emph{image} with respect to its users and the rest of
  429. the Internet impacts the security it can provide.
  430. With this image issue in mind, this section discusses the Tor user base and
  431. Tor's interaction with other services on the Internet.
  432. \subsection{Communicating security}
  433. Usability for anonymity systems
  434. contributes to their security, because usability
  435. affects the possible anonymity set~\cite{econymics,back01}.
  436. Conversely, an unusable system attracts few users and thus can't provide
  437. much anonymity.
  438. This phenomenon has a second-order effect: knowing this, users should
  439. choose which anonymity system to use based in part on how usable
  440. and secure
  441. \emph{others} will find it, in order to get the protection of a larger
  442. anonymity set. Thus we might supplement the adage ``usability is a security
  443. parameter''~\cite{back01} with a new one: ``perceived usability is a
  444. security parameter.'' From here we can better understand the effects
  445. of publicity on security: the more convincing your
  446. advertising, the more likely people will believe you have users, and thus
  447. the more users you will attract. Perversely, over-hyped systems (if they
  448. are not too broken) may be a better choice than modestly promoted ones,
  449. if the hype attracts more users~\cite{usability-network-effect}.
  450. %So it follows that we should come up with ways to accurately communicate
  451. %the available security levels to the user, so she can make informed
  452. %decisions.
  453. %JAP aims to do this by including a
  454. %comforting `anonymity meter' dial in the software's graphical interface,
  455. %giving the user an impression of the level of protection for her current
  456. %traffic.
  457. However, there's a catch. For users to share the same anonymity set,
  458. they need to act like each other. An attacker who can distinguish
  459. a given user's traffic from the rest of the traffic will not be
  460. distracted by anonymity set size. For high-latency systems like
  461. Mixminion, where the threat model is based on mixing messages with each
  462. other, there's an arms race between end-to-end statistical attacks and
  463. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  464. But for low-latency systems like Tor, end-to-end \emph{traffic
  465. correlation} attacks~\cite{danezis:pet2004,defensive-dropping,SS03,hs-attack}
  466. allow an attacker who can observe both ends of a communication
  467. to correlate packet timing and volume, quickly linking
  468. the initiator to her destination.
  469. \workingnote{
  470. Like Tor, the current JAP implementation does not pad connections
  471. apart from using small fixed-size cells for transport. In fact,
  472. JAP's cascade-based network topology may be more vulnerable to these
  473. attacks, because its network has fewer edges. JAP was born out of
  474. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  475. every user had a fixed bandwidth allocation and altering the timing
  476. pattern of packets could be immediately detected. But in its current context
  477. as an Internet web anonymizer, adding sufficient padding to JAP
  478. would probably be prohibitively expensive and ineffective against a
  479. minimally active attacker.\footnote{Even if JAP could
  480. fund higher-capacity nodes indefinitely, our experience
  481. suggests that many users would not accept the increased per-user
  482. bandwidth requirements, leading to an overall much smaller user base.}
  483. Therefore, since under this threat
  484. model the number of concurrent users does not seem to have much impact
  485. on the anonymity provided, we suggest that JAP's anonymity meter is not
  486. accurately communicating security levels to its users.
  487. }
  488. On the other hand, while the number of active concurrent users may not
  489. matter as much as we'd like, it still helps to have some other users
  490. on the network, in particular different types of users.
  491. We investigate this issue next.
  492. \subsection{Reputability and perceived social value}
  493. Another factor impacting the network's security is its reputability:
  494. the perception of its social value based on its current user base. If Alice is
  495. the only user who has ever downloaded the software, it might be socially
  496. accepted, but she's not getting much anonymity. Add a thousand
  497. activists, and she's anonymous, but everyone thinks she's an activist too.
  498. Add a thousand
  499. diverse citizens (cancer survivors, privacy enthusiasts, and so on)
  500. and now she's harder to profile.
  501. Furthermore, the network's reputability affects its operator base: more people
  502. are willing to run a service if they believe it will be used by human rights
  503. workers than if they believe it will be used exclusively for disreputable
  504. ends. This effect becomes stronger if node operators themselves think they
  505. will be associated with their users' disreputable ends.
  506. So the more cancer survivors on Tor, the better for the human rights
  507. activists. The more malicious hackers, the worse for the normal users. Thus,
  508. reputability is an anonymity issue for two reasons. First, it impacts
  509. the sustainability of the network: a network that's always about to be
  510. shut down has difficulty attracting and keeping adequate nodes.
  511. Second, a disreputable network is more vulnerable to legal and
  512. political attacks, since it will attract fewer supporters.
  513. While people therefore have an incentive for the network to be used for
  514. ``more reputable'' activities than their own, there are still trade-offs
  515. involved when it comes to anonymity. To follow the above example, a
  516. network used entirely by cancer survivors might welcome file sharers
  517. onto the network, though of course they'd prefer a wider
  518. variety of users.
  519. Reputability becomes even more tricky in the case of privacy networks,
  520. since the good uses of the network (such as publishing by journalists in
  521. dangerous countries) are typically kept private, whereas network abuses
  522. or other problems tend to be more widely publicized.
  523. The impact of public perception on security is especially important
  524. during the bootstrapping phase of the network, where the first few
  525. widely publicized uses of the network can dictate the types of users it
  526. attracts next.
  527. As an example, some U.S.~Department of Energy
  528. penetration testing engineers are tasked with compromising DoE computers
  529. from the outside. They only have a limited number of ISPs from which to
  530. launch their attacks, and they found that the defenders were recognizing
  531. attacks because they came from the same IP space. These engineers wanted
  532. to use Tor to hide their tracks. First, from a technical standpoint,
  533. Tor does not support the variety of IP packets one would like to use in
  534. such attacks.% (see Section~\ref{subsec:tcp-vs-ip}).
  535. But aside from this, we also decided that it would probably be poor
  536. precedent to encourage such use---even legal use that improves
  537. national security---and managed to dissuade them.
  538. %% "outside of academia, jap has just lost, permanently". (That is,
  539. %% even though the crime detection issues are resolved and are unlikely
  540. %% to go down the same way again, public perception has not been kind.)
  541. \subsection{Sustainability and incentives}
  542. One of the unsolved problems in low-latency anonymity designs is
  543. how to keep the nodes running. ZKS's Freedom network
  544. depended on paying third parties to run its servers; the JAP project's
  545. bandwidth depends on grants to pay for its bandwidth and
  546. administrative expenses. In Tor, bandwidth and administrative costs are
  547. distributed across the volunteers who run Tor nodes, so we at least have
  548. reason to think that the Tor network could survive without continued research
  549. funding.\footnote{It also helps that Tor is implemented with free and open
  550. source software that can be maintained by anybody with the ability and
  551. inclination.} But why are these volunteers running nodes, and what can we
  552. do to encourage more volunteers to do so?
  553. We have not formally surveyed Tor node operators to learn why they are
  554. running nodes, but
  555. from the information they have provided, it seems that many of them run Tor
  556. nodes for reasons of personal interest in privacy issues. It is possible
  557. that others are running Tor nodes to protect their own
  558. anonymity, but of course they are
  559. hardly likely to tell us specifics if they are.
  560. %Significantly, Tor's threat model changes the anonymity incentives for running
  561. %a node. In a high-latency mix network, users can receive additional
  562. %anonymity by running their own node, since doing so obscures when they are
  563. %injecting messages into the network. But, anybody observing all I/O to a Tor
  564. %node can tell when the node is generating traffic that corresponds to
  565. %none of its incoming traffic.
  566. %
  567. %I didn't buy the above for reason's subtle enough that I just cut it -PFS
  568. Tor exit node operators do attain a degree of
  569. ``deniability'' for traffic that originates at that exit node. For
  570. example, it is likely in practice that HTTP requests from a Tor node's IP
  571. will be assumed to be from the Tor network.
  572. More significantly, people and organizations who use Tor for
  573. anonymity depend on the
  574. continued existence of the Tor network to do so; running a node helps to
  575. keep the network operational.
  576. %\item Local Tor entry and exit nodes allow users on a network to run in an
  577. % `enclave' configuration. [XXXX need to resolve this. They would do this
  578. % for E2E encryption + auth?]
  579. %We must try to make the costs of running a Tor node easily minimized.
  580. Since Tor is run by volunteers, the most crucial software usability issue is
  581. usability by operators: when an operator leaves, the network becomes less
  582. usable by everybody. To keep operators pleased, we must try to keep Tor's
  583. resource and administrative demands as low as possible.
  584. Because of ISP billing structures, many Tor operators have underused capacity
  585. that they are willing to donate to the network, at no additional monetary
  586. cost to them. Features to limit bandwidth have been essential to adoption.
  587. Also useful has been a ``hibernation'' feature that allows a Tor node that
  588. wants to provide high bandwidth, but no more than a certain amount in a
  589. giving billing cycle, to become dormant once its bandwidth is exhausted, and
  590. to reawaken at a random offset into the next billing cycle. This feature has
  591. interesting policy implications, however; see
  592. the next section below.
  593. Exit policies help to limit administrative costs by limiting the frequency of
  594. abuse complaints (see Section~\ref{subsec:tor-and-blacklists}).
  595. % We discuss
  596. %technical incentive mechanisms in Section~\ref{subsec:incentives-by-design}.
  597. %[XXXX say more. Why else would you run a node? What else can we do/do we
  598. % already do to make running a node more attractive?]
  599. %[We can enforce incentives; see Section 6.1. We can rate-limit clients.
  600. % We can put "top bandwidth nodes lists" up a la seti@home.]
  601. \workingnote{
  602. \subsection{Bandwidth and file-sharing}
  603. \label{subsec:bandwidth-and-file-sharing}
  604. %One potentially problematical area with deploying Tor has been our response
  605. %to file-sharing applications.
  606. Once users have configured their applications to work with Tor, the largest
  607. remaining usability issue is performance. Users begin to suffer
  608. when websites ``feel slow.''
  609. Clients currently try to build their connections through nodes that they
  610. guess will have enough bandwidth. But even if capacity is allocated
  611. optimally, it seems unlikely that the current network architecture will have
  612. enough capacity to provide every user with as much bandwidth as she would
  613. receive if she weren't using Tor, unless far more nodes join the network.
  614. %Limited capacity does not destroy the network, however. Instead, usage tends
  615. %towards an equilibrium: when performance suffers, users who value performance
  616. %over anonymity tend to leave the system, thus freeing capacity until the
  617. %remaining users on the network are exactly those willing to use that capacity
  618. %there is.
  619. Much of Tor's recent bandwidth difficulties have come from file-sharing
  620. applications. These applications provide two challenges to
  621. any anonymizing network: their intensive bandwidth requirement, and the
  622. degree to which they are associated (correctly or not) with copyright
  623. infringement.
  624. High-bandwidth protocols can make the network unresponsive,
  625. but tend to be somewhat self-correcting as lack of bandwidth drives away
  626. users who need it. Issues of copyright violation,
  627. however, are more interesting. Typical exit node operators want to help
  628. people achieve private and anonymous speech, not to help people (say) host
  629. Vin Diesel movies for download; and typical ISPs would rather not
  630. deal with customers who draw menacing letters
  631. from the MPAA\@. While it is quite likely that the operators are doing nothing
  632. illegal, many ISPs have policies of dropping users who get repeated legal
  633. threats regardless of the merits of those threats, and many operators would
  634. prefer to avoid receiving even meritless legal threats.
  635. So when letters arrive, operators are likely to face
  636. pressure to block file-sharing applications entirely, in order to avoid the
  637. hassle.
  638. But blocking file-sharing is not easy: popular
  639. protocols have evolved to run on non-standard ports to
  640. get around other port-based bans. Thus, exit node operators who want to
  641. block file-sharing would have to find some way to integrate Tor with a
  642. protocol-aware exit filter. This could be a technically expensive
  643. undertaking, and one with poor prospects: it is unlikely that Tor exit nodes
  644. would succeed where so many institutional firewalls have failed. Another
  645. possibility for sensitive operators is to run a restrictive node that
  646. only permits exit connections to a restricted range of ports that are
  647. not frequently associated with file sharing. There are increasingly few such
  648. ports.
  649. Other possible approaches might include rate-limiting connections, especially
  650. long-lived connections or connections to file-sharing ports, so that
  651. high-bandwidth connections do not flood the network. We might also want to
  652. give priority to cells on low-bandwidth connections to keep them interactive,
  653. but this could have negative anonymity implications.
  654. For the moment, it seems that Tor's bandwidth issues have rendered it
  655. unattractive for bulk file-sharing traffic; this may continue to be so in the
  656. future. Nevertheless, Tor will likely remain attractive for limited use in
  657. file-sharing protocols that have separate control and data channels.
  658. %[We should say more -- but what? That we'll see a similar
  659. % equilibriating effect as with bandwidth, where sensitive ops switch to
  660. % middleman, and we become less useful for file-sharing, so the file-sharing
  661. % people back off, so we get more ops since there's less file-sharing, so the
  662. % file-sharers come back, etc.]
  663. %XXXX
  664. %in practice, plausible deniability is hypothetical and doesn't seem very
  665. %convincing. if ISPs find the activity antisocial, they don't care *why*
  666. %your computer is doing that behavior.
  667. }
  668. \subsection{Tor and blacklists}
  669. \label{subsec:tor-and-blacklists}
  670. It was long expected that, alongside legitimate users, Tor would also
  671. attract troublemakers who exploit Tor to abuse services on the
  672. Internet with vandalism, rude mail, and so on.
  673. Our initial answer to this situation was to use ``exit policies''
  674. to allow individual Tor nodes to block access to specific IP/port ranges.
  675. This approach aims to make operators more willing to run Tor by allowing
  676. them to prevent their nodes from being used for abusing particular
  677. services. For example, by default Tor nodes block SMTP (port 25),
  678. to avoid the issue of spam. Note that for spammers, Tor would be
  679. a step back, a much less effective means of distributing spam than
  680. those currently available. This is thus primarily an unmistakable
  681. answer to those confused about Internet communication who might raise
  682. spam as an issue.
  683. Exit policies are useful, but they are insufficient: if not all nodes
  684. block a given service, that service may try to block Tor instead.
  685. While being blockable is important to being good netizens, we would like
  686. to encourage services to allow anonymous access. Services should not
  687. need to decide between blocking legitimate anonymous use and allowing
  688. unlimited abuse. For the time being, blocking by IP address is
  689. an expedient strategy, even if it undermines Internet stability and
  690. functionality in the long run~\cite{netauth}
  691. This is potentially a bigger problem than it may appear.
  692. On the one hand, services should be allowed to refuse connections from
  693. sources of possible abuse.
  694. But when a Tor node administrator decides whether he prefers to be able
  695. to post to Wikipedia from his IP address, or to allow people to read
  696. Wikipedia anonymously through his Tor node, he is making the decision
  697. for others as well. (For a while, Wikipedia
  698. blocked all posting from all Tor nodes based on IP addresses.) If
  699. the Tor node shares an address with a campus or corporate NAT,
  700. then the decision can prevent the entire population from posting.
  701. Similarly, whether intended or not, such blocking supports
  702. repression of free speech. In many locations where Internet access
  703. of various kinds is censored or even punished by imprisonment,
  704. Tor is a path both to the outside world and to others inside.
  705. Blocking posts from Tor makes the job of censoring authorities easier.
  706. This is a loss for both Tor
  707. and Wikipedia: we don't want to compete for (or divvy up) the
  708. NAT-protected entities of the world.
  709. This is also unfortunate because there are relatively simple technical
  710. solutions.
  711. Various schemes for escrowing anonymous posts until they are reviewed
  712. by editors would both prevent abuse and remove incentives for attempts
  713. to abuse. Further, pseudonymous reputation tracking of posters through Tor
  714. would allow those who establish adequate reputation to post without
  715. escrow. Software to support pseudonymous access via Tor designed precisely
  716. to interact with Wikipedia's access mechanism has even been developed
  717. and proposed to Wikimedia by Jason Holt~\cite{nym}, but has not been taken up.
  718. Perhaps worse, many IP blacklists are coarse-grained: they ignore Tor's exit
  719. policies, partly because it's easier to implement and partly
  720. so they can punish
  721. all Tor nodes. One IP blacklist even bans
  722. every class C network that contains a Tor node, and recommends banning SMTP
  723. from these networks even though Tor does not allow SMTP at all. This
  724. strategic decision aims to discourage the
  725. operation of anything resembling an open proxy by encouraging its neighbors
  726. to shut it down to get unblocked themselves. This pressure even
  727. affects Tor nodes running in middleman mode (disallowing all exits) when
  728. those nodes are blacklisted too.
  729. % Perception of Tor as an abuse vector
  730. %is also partly driven by multiple base-rate fallacies~\cite{axelsson00}.
  731. Problems of abuse occur mainly with services such as IRC networks and
  732. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  733. blush this practice might seem to depend on the anachronistic assumption that
  734. each IP is an identifier for a single user, it is actually more reasonable in
  735. practice: it assumes that non-proxy IPs are a costly resource, and that an
  736. abuser can not change IPs at will. By blocking IPs which are used by Tor
  737. nodes, open proxies, and service abusers, these systems hope to make
  738. ongoing abuse difficult. Although the system is imperfect, it works
  739. tolerably well for them in practice.
  740. Of course, we would prefer that legitimate anonymous users be able to
  741. access abuse-prone services. One conceivable approach would require
  742. would-be IRC users, for instance, to register accounts if they want to
  743. access the IRC network from Tor. In practice this would not
  744. significantly impede abuse if creating new accounts were easily automatable;
  745. this is why services use IP blocking. To deter abuse, pseudonymous
  746. identities need to require a significant switching cost in resources or human
  747. time. Some popular webmail applications
  748. impose cost with Reverse Turing Tests, but this step may not deter all
  749. abusers. Freedom used blind signatures to limit
  750. the number of pseudonyms for each paying account, but Tor has neither the
  751. ability nor the desire to collect payment.
  752. We stress that as far as we can tell, most Tor uses are not
  753. abusive. Most services have not complained, and others are actively
  754. working to find ways besides banning to cope with the abuse. For example,
  755. the Freenode IRC network had a problem with a coordinated group of
  756. abusers joining channels and subtly taking over the conversation; but
  757. when they labelled all users coming from Tor IPs as ``anonymous users,''
  758. removing the ability of the abusers to blend in, the abuse stopped.
  759. This is an illustration of how simple technical mechanisms can remove
  760. the ability to abuse anonymously without undermining the ability
  761. to communicate anonymous and can thus remove the incentive to attempt
  762. abusing in this way.
  763. %The use of squishy IP-based ``authentication'' and ``authorization''
  764. %has not broken down even to the level that SSNs used for these
  765. %purposes have in commercial and public record contexts. Externalities
  766. %and misplaced incentives cause a continued focus on fighting identity
  767. %theft by protecting SSNs rather than developing better authentication
  768. %and incentive schemes \cite{price-privacy}. Similarly we can expect a
  769. %continued use of identification by IP number as long as there is no
  770. %workable alternative.
  771. %[XXX Mention correct DNS-RBL implementation. -NM]
  772. \workingnote{
  773. \section{Design choices}
  774. In addition to social issues, Tor also faces some design trade-offs that must
  775. be investigated as the network develops.
  776. \subsection{Transporting the stream vs transporting the packets}
  777. \label{subsec:stream-vs-packet}
  778. \label{subsec:tcp-vs-ip}
  779. Tor transports streams; it does not tunnel packets.
  780. It has often been suggested that like the old Freedom
  781. network~\cite{freedom21-security}, Tor should
  782. ``obviously'' anonymize IP traffic
  783. at the IP layer. Before this could be done, many issues need to be resolved:
  784. \begin{enumerate}
  785. \setlength{\itemsep}{0mm}
  786. \setlength{\parsep}{0mm}
  787. \item \emph{IP packets reveal OS characteristics.} We would still need to do
  788. IP-level packet normalization, to stop things like TCP fingerprinting
  789. attacks. %There likely exist libraries that can help with this.
  790. This is unlikely to be a trivial task, given the diversity and complexity of
  791. TCP stacks.
  792. \item \emph{Application-level streams still need scrubbing.} We still need
  793. Tor to be easy to integrate with user-level application-specific proxies
  794. such as Privoxy. So it's not just a matter of capturing packets and
  795. anonymizing them at the IP layer.
  796. \item \emph{Certain protocols will still leak information.} For example, we
  797. must rewrite DNS requests so they are delivered to an unlinkable DNS server
  798. rather than the DNS server at a user's ISP; thus, we must understand the
  799. protocols we are transporting.
  800. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  801. approach that can provide security despite
  802. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  803. never publicly specified.
  804. Also, TLS over UDP is not yet implemented or
  805. specified, though some early work has begun~\cite{dtls}.
  806. \item \emph{We'll still need to tune network parameters.} Since the above
  807. encryption system will likely need sequence numbers (and maybe more) to do
  808. replay detection, handle duplicate frames, and so on, we will be reimplementing
  809. a subset of TCP anyway---a notoriously tricky path.
  810. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  811. IDS\@.} Our node operators tell us that exit policies are one of
  812. the main reasons they're willing to run Tor.
  813. Adding an Intrusion Detection System to handle exit policies would
  814. increase the security complexity of Tor, and would likely not work anyway,
  815. as evidenced by the entire field of IDS and counter-IDS papers. Many
  816. potential abuse issues are resolved by the fact that Tor only transports
  817. valid TCP streams (as opposed to arbitrary IP including malformed packets
  818. and IP floods), so exit policies become even \emph{more} important as
  819. we become able to transport IP packets. We also need to compactly
  820. describe exit policies so clients can predict
  821. which nodes will allow which packets to exit.
  822. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  823. support hidden service {\tt{.onion}} addresses (and other special addresses,
  824. like {\tt{.exit}} which lets the user request a particular exit node),
  825. by intercepting the addresses when they are passed to the Tor client.
  826. Doing so at the IP level would require a more complex interface between
  827. Tor and the local DNS resolver.
  828. \end{enumerate}
  829. This list is discouragingly long, but being able to transport more
  830. protocols obviously has some advantages. It would be good to learn which
  831. items are actual roadblocks and which are easier to resolve than we think.
  832. To be fair, Tor's stream-based approach has run into
  833. stumbling blocks as well. While Tor supports the SOCKS protocol,
  834. which provides a standardized interface for generic TCP proxies, many
  835. applications do not support SOCKS\@. For them we already need to
  836. replace the networking system calls with SOCKS-aware
  837. versions, or run a SOCKS tunnel locally, neither of which is
  838. easy for the average user. %---even with good instructions.
  839. Even when applications can use SOCKS, they often make DNS requests
  840. themselves before handing an IP address to Tor, which advertises
  841. where the user is about to connect.
  842. We are still working on more usable solutions.
  843. %So to actually provide good anonymity, we need to make sure that
  844. %users have a practical way to use Tor anonymously. Possibilities include
  845. %writing wrappers for applications to anonymize them automatically; improving
  846. %the applications' support for SOCKS; writing libraries to help application
  847. %writers use Tor properly; and implementing a local DNS proxy to reroute DNS
  848. %requests to Tor so that applications can simply point their DNS resolvers at
  849. %localhost and continue to use SOCKS for data only.
  850. \subsection{Mid-latency}
  851. \label{subsec:mid-latency}
  852. Some users need to resist traffic correlation attacks. Higher-latency
  853. mix-networks introduce variability into message
  854. arrival times: as timing variance increases, timing correlation attacks
  855. require increasingly more data~\cite{e2e-traffic}. Can we improve Tor's
  856. resistance without losing too much usability?
  857. We need to learn whether we can trade a small increase in latency
  858. for a large anonymity increase, or if we'd end up trading a lot of
  859. latency for only a minimal security gain. A trade-off might be worthwhile
  860. even if we
  861. could only protect certain use cases, such as infrequent short-duration
  862. transactions. % To answer this question
  863. We might adapt the techniques of~\cite{e2e-traffic} to a lower-latency mix
  864. network, where the messages are batches of cells in temporally clustered
  865. connections. These large fixed-size batches can also help resist volume
  866. signature attacks~\cite{hintz-pet02}. We could also experiment with traffic
  867. shaping to get a good balance of throughput and security.
  868. %Other padding regimens might supplement the
  869. %mid-latency option; however, we should continue the caution with which
  870. %we have always approached padding lest the overhead cost us too much
  871. %performance or too many volunteers.
  872. We must keep usability in mind too. How much can latency increase
  873. before we drive users away? We've already been forced to increase
  874. latency slightly, as our growing network incorporates more DSL and
  875. cable-modem nodes and more nodes in distant continents. Perhaps we can
  876. harness this increased latency to improve anonymity rather than just
  877. reduce usability. Further, if we let clients label certain circuits as
  878. mid-latency as they are constructed, we could handle both types of traffic
  879. on the same network, giving users a choice between speed and security---and
  880. giving researchers a chance to experiment with parameters to improve the
  881. quality of those choices.
  882. \subsection{Enclaves and helper nodes}
  883. \label{subsec:helper-nodes}
  884. It has long been thought that users can improve their anonymity by
  885. running their own node~\cite{tor-design,or-ih96,or-pet00}, and using
  886. it in an \emph{enclave} configuration, where all their circuits begin
  887. at the node under their control. Running Tor clients or servers at
  888. the enclave perimeter is useful when policy or other requirements
  889. prevent individual machines within the enclave from running Tor
  890. clients~\cite{or-jsac98,or-discex00}.
  891. Of course, Tor's default path length of
  892. three is insufficient for these enclaves, since the entry and/or exit
  893. % [edit war: without the ``and/'' the natural reading here
  894. % is aut rather than vel. And the use of the plural verb does not work -pfs]
  895. themselves are sensitive. Tor thus increments path length by one
  896. for each sensitive endpoint in the circuit.
  897. Enclaves also help to protect against end-to-end attacks, since it's
  898. possible that traffic coming from the node has simply been relayed from
  899. elsewhere. However, if the node has recognizable behavior patterns,
  900. an attacker who runs nodes in the network can triangulate over time to
  901. gain confidence that it is in fact originating the traffic. Wright et
  902. al.~\cite{wright03} introduce the notion of a \emph{helper node}---a
  903. single fixed entry node for each user---to combat this \emph{predecessor
  904. attack}.
  905. However, the attack in~\cite{attack-tor-oak05} shows that simply adding
  906. to the path length, or using a helper node, may not protect an enclave
  907. node. A hostile web server can send constant interference traffic to
  908. all nodes in the network, and learn which nodes are involved in the
  909. circuit (though at least in the current attack, he can't learn their
  910. order). Using randomized path lengths may help some, since the attacker
  911. will never be certain he has identified all nodes in the path unless
  912. he probes the entire network, but as
  913. long as the network remains small this attack will still be feasible.
  914. Helper nodes also aim to help Tor clients, because choosing entry and exit
  915. points
  916. randomly and changing them frequently allows an attacker who controls
  917. even a few nodes to eventually link some of their destinations. The goal
  918. is to take the risk once and for all about choosing a bad entry node,
  919. rather than taking a new risk for each new circuit. (Choosing fixed
  920. exit nodes is less useful, since even an honest exit node still doesn't
  921. protect against a hostile website.) But obstacles remain before
  922. we can implement helper nodes.
  923. For one, the literature does not describe how to choose helpers from a list
  924. of nodes that changes over time. If Alice is forced to choose a new entry
  925. helper every $d$ days and $c$ of the $n$ nodes are bad, she can expect
  926. to choose a compromised node around
  927. every $dc/n$ days. Statistically over time this approach only helps
  928. if she is better at choosing honest helper nodes than at choosing
  929. honest nodes. Worse, an attacker with the ability to DoS nodes could
  930. force users to switch helper nodes more frequently, or remove
  931. other candidate helpers.
  932. %Do general DoS attacks have anonymity implications? See e.g. Adam
  933. %Back's IH paper, but I think there's more to be pointed out here. -RD
  934. % Not sure what you want to say here. -NM
  935. %Game theory for helper nodes: if Alice offers a hidden service on a
  936. %server (enclave model), and nobody ever uses helper nodes, then against
  937. %George+Steven's attack she's totally nailed. If only Alice uses a helper
  938. %node, then she's still identified as the source of the data. If everybody
  939. %uses a helper node (including Alice), then the attack identifies the
  940. %helper node and also Alice, and knows which one is which. If everybody
  941. %uses a helper node (but not Alice), then the attacker figures the real
  942. %source was a client that is using Alice as a helper node. [How's my
  943. %logic here?] -RD
  944. %
  945. % Not sure about the logic. For the attack to work with helper nodes, the
  946. %attacker needs to guess that Alice is running the hidden service, right?
  947. %Otherwise, how can he know to measure her traffic specifically? -NM
  948. %
  949. % In the Murdoch-Danezis attack, the adversary measures all servers. -RD
  950. %point to routing-zones section re: helper nodes to defend against
  951. %big stuff.
  952. \subsection{Location-hidden services}
  953. \label{subsec:hidden-services}
  954. % This section is first up against the wall when the revolution comes.
  955. Tor's \emph{rendezvous points}
  956. let users provide TCP services to other Tor users without revealing
  957. the service's location. Since this feature is relatively recent, we describe
  958. here
  959. a couple of our early observations from its deployment.
  960. First, our implementation of hidden services seems less hidden than we'd
  961. like, since they build a different rendezvous circuit for each user,
  962. and an external adversary can induce them to
  963. produce traffic. This insecurity means that they may not be suitable as
  964. a building block for Free Haven~\cite{freehaven-berk} or other anonymous
  965. publishing systems that aim to provide long-term security, though helper
  966. nodes, as discussed above, would seem to help.
  967. \emph{Hot-swap} hidden services, where more than one location can
  968. provide the service and loss of any one location does not imply a
  969. change in service, would help foil intersection and observation attacks
  970. where an adversary monitors availability of a hidden service and also
  971. monitors whether certain users or servers are online. The design
  972. challenges in providing such services without otherwise compromising
  973. the hidden service's anonymity remain an open problem;
  974. however, see~\cite{move-ndss05}.
  975. In practice, hidden services are used for more than just providing private
  976. access to a web server or IRC server. People are using hidden services
  977. as a poor man's VPN and firewall-buster. Many people want to be able
  978. to connect to the computers in their private network via secure shell,
  979. and rather than playing with dyndns and trying to pierce holes in their
  980. firewall, they run a hidden service on the inside and then rendezvous
  981. with that hidden service externally.
  982. News sites like Bloggers Without Borders (www.b19s.org) are advertising
  983. a hidden-service address on their front page. Doing this can provide
  984. increased robustness if they use the dual-IP approach we describe
  985. in~\cite{tor-design},
  986. but in practice they do it to increase visibility
  987. of the Tor project and their support for privacy, and to offer
  988. a way for their users, using unmodified software, to get end-to-end
  989. encryption and authentication to their website.
  990. \subsection{Location diversity and ISP-class adversaries}
  991. \label{subsec:routing-zones}
  992. Anonymity networks have long relied on diversity of node location for
  993. protection against attacks---typically an adversary who can observe a
  994. larger fraction of the network can launch a more effective attack. One
  995. way to achieve dispersal involves growing the network so a given adversary
  996. sees less. Alternately, we can arrange the topology so traffic can enter
  997. or exit at many places (for example, by using a free-route network
  998. like Tor rather than a cascade network like JAP). Lastly, we can use
  999. distributed trust to spread each transaction over multiple jurisdictions.
  1000. But how do we decide whether two nodes are in related locations?
  1001. Feamster and Dingledine defined a \emph{location diversity} metric
  1002. in~\cite{feamster:wpes2004}, and began investigating a variant of location
  1003. diversity based on the fact that the Internet is divided into thousands of
  1004. independently operated networks called {\em autonomous systems} (ASes).
  1005. The key insight from their paper is that while we typically think of a
  1006. connection as going directly from the Tor client to the first Tor node,
  1007. actually it traverses many different ASes on each hop. An adversary at
  1008. any of these ASes can monitor or influence traffic. Specifically, given
  1009. plausible initiators and recipients, and given random path selection,
  1010. some ASes in the simulation were able to observe 10\% to 30\% of the
  1011. transactions (that is, learn both the origin and the destination) on
  1012. the deployed Tor network (33 nodes as of June 2004).
  1013. The paper concludes that for best protection against the AS-level
  1014. adversary, nodes should be in ASes that have the most links to other ASes:
  1015. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  1016. is safest when it starts or ends in a Tier-1 ISP\@. Therefore, assuming
  1017. initiator and responder are both in the U.S., it actually \emph{hurts}
  1018. our location diversity to use far-flung nodes in
  1019. continents like Asia or South America.
  1020. % it's not just entering or exiting from them. using them as the middle
  1021. % hop reduces your effective path length, which you presumably don't
  1022. % want because you chose that path length for a reason.
  1023. %
  1024. % Not sure I buy that argument. Two end nodes in the right ASs to
  1025. % discourage linking are still not known to each other. If some
  1026. % adversary in a single AS can bridge the middle node, it shouldn't
  1027. % therefore be able to identify initiator or responder; although it could
  1028. % contribute to further attacks given more assumptions.
  1029. % Nonetheless, no change to the actual text for now.
  1030. Many open questions remain. First, it will be an immense engineering
  1031. challenge to get an entire BGP routing table to each Tor client, or to
  1032. summarize it sufficiently. Without a local copy, clients won't be
  1033. able to safely predict what ASes will be traversed on the various paths
  1034. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  1035. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  1036. determine location diversity; but the above paper showed that in practice
  1037. many of the Mixmaster nodes that share a single AS have entirely different
  1038. IP prefixes. When the network has scaled to thousands of nodes, does IP
  1039. prefix comparison become a more useful approximation? % Alternatively, can
  1040. %relevant parts of the routing tables be summarized centrally and delivered to
  1041. %clients in a less verbose format?
  1042. %% i already said "or to summarize is sufficiently" above. is that not
  1043. %% enough? -RD
  1044. %
  1045. Second, we can take advantage of caching certain content at the
  1046. exit nodes, to limit the number of requests that need to leave the
  1047. network at all. What about taking advantage of caches like Akamai or
  1048. Google~\cite{shsm03}? (Note that they're also well-positioned as global
  1049. adversaries.)
  1050. %
  1051. Third, if we follow the recommendations in~\cite{feamster:wpes2004}
  1052. and tailor path selection
  1053. to avoid choosing endpoints in similar locations, how much are we hurting
  1054. anonymity against larger real-world adversaries who can take advantage
  1055. of knowing our algorithm?
  1056. %
  1057. Fourth, can we use this knowledge to figure out which gaps in our network
  1058. most affect our robustness to this class of attack, and go recruit
  1059. new nodes with those ASes in mind?
  1060. %Tor's security relies in large part on the dispersal properties of its
  1061. %network. We need to be more aware of the anonymity properties of various
  1062. %approaches so we can make better design decisions in the future.
  1063. \subsection{The Anti-censorship problem}
  1064. \label{subsec:china}
  1065. Citizens in a variety of countries, such as most recently China and
  1066. Iran, are blocked from accessing various sites outside
  1067. their country. These users try to find any tools available to allow
  1068. them to get-around these firewalls. Some anonymity networks, such as
  1069. Six-Four~\cite{six-four}, are designed specifically with this goal in
  1070. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  1071. such as Voice of America to encourage Internet
  1072. freedom. Even though Tor wasn't
  1073. designed with ubiquitous access to the network in mind, thousands of
  1074. users across the world are now using it for exactly this purpose.
  1075. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  1076. Anti-censorship networks hoping to bridge country-level blocks face
  1077. a variety of challenges. One of these is that they need to find enough
  1078. exit nodes---servers on the `free' side that are willing to relay
  1079. traffic from users to their final destinations. Anonymizing
  1080. networks like Tor are well-suited to this task since we have
  1081. already gathered a set of exit nodes that are willing to tolerate some
  1082. political heat.
  1083. The other main challenge is to distribute a list of reachable relays
  1084. to the users inside the country, and give them software to use those relays,
  1085. without letting the censors also enumerate this list and block each
  1086. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  1087. addresses (or having them donated), abandoning old addresses as they are
  1088. `used up,' and telling a few users about the new ones. Distributed
  1089. anonymizing networks again have an advantage here, in that we already
  1090. have tens of thousands of separate IP addresses whose users might
  1091. volunteer to provide this service since they've already installed and use
  1092. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1093. the Tor protocol separates routing from network discovery \cite{tor-design},
  1094. volunteers could configure their Tor clients
  1095. to generate node descriptors and send them to a special directory
  1096. server that gives them out to dissidents who need to get around blocks.
  1097. Of course, this still doesn't prevent the adversary
  1098. from enumerating and preemptively blocking the volunteer relays.
  1099. Perhaps a tiered-trust system could be built where a few individuals are
  1100. given relays' locations. They could then recommend other individuals
  1101. by telling them
  1102. those addresses, thus providing a built-in incentive to avoid letting the
  1103. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1104. might help to bound the number of IP addresses leaked to the adversary. Groups
  1105. like the W3C are looking into using Tor as a component in an overall system to
  1106. help address censorship; we wish them success.
  1107. %\cite{infranet}
  1108. \section{Scaling}
  1109. \label{sec:scaling}
  1110. Tor is running today with hundreds of nodes and hundreds of thousands of
  1111. users, but it will certainly not scale to millions.
  1112. Scaling Tor involves four main challenges. First, to get a
  1113. large set of nodes, we must address incentives for
  1114. users to carry traffic for others. Next is safe node discovery, both
  1115. while bootstrapping (Tor clients must robustly find an initial
  1116. node list) and later (Tor clients must learn about a fair sample
  1117. of honest nodes and not let the adversary control circuits).
  1118. We must also detect and handle node speed and reliability as the network
  1119. becomes increasingly heterogeneous: since the speed and reliability
  1120. of a circuit is limited by its worst link, we must learn to track and
  1121. predict performance. Finally, we must stop assuming that all points on
  1122. the network can connect to all other points.
  1123. \subsection{Incentives by Design}
  1124. \label{subsec:incentives-by-design}
  1125. There are three behaviors we need to encourage for each Tor node: relaying
  1126. traffic; providing good throughput and reliability while doing it;
  1127. and allowing traffic to exit the network from that node.
  1128. We encourage these behaviors through \emph{indirect} incentives: that
  1129. is, by designing the system and educating users in such a way that users
  1130. with certain goals will choose to relay traffic. One
  1131. main incentive for running a Tor node is social: volunteers
  1132. altruistically donate their bandwidth and time. We encourage this with
  1133. public rankings of the throughput and reliability of nodes, much like
  1134. seti@home. We further explain to users that they can get
  1135. deniability for any traffic emerging from the same address as a Tor
  1136. exit node, and they can use their own Tor node
  1137. as an entry or exit point with confidence that it's not run by an adversary.
  1138. Further, users may run a node simply because they need such a network
  1139. to be persistently available and usable, and the value of supporting this
  1140. exceeds any countervening costs.
  1141. Finally, we can encourage operators by improving the usability and feature
  1142. set of the software:
  1143. rate limiting support and easy packaging decrease the hassle of
  1144. maintaining a node, and our configurable exit policies allow each
  1145. operator to advertise a policy describing the hosts and ports to which
  1146. he feels comfortable connecting.
  1147. To date these incentives appear to have been adequate. As the system scales
  1148. or as new issues emerge, however, we may also need to provide
  1149. \emph{direct} incentives:
  1150. providing payment or other resources in return for high-quality service.
  1151. Paying actual money is problematic: decentralized e-cash systems are
  1152. not yet practical, and a centralized collection system not only reduces
  1153. robustness, but also has failed in the past (the history of commercial
  1154. anonymizing networks is littered with failed attempts). A more promising
  1155. option is to use a tit-for-tat incentive scheme, where nodes provide better
  1156. service to nodes that have provided good service for them.
  1157. Unfortunately, such an approach introduces new anonymity problems.
  1158. There are many surprising ways for nodes to game the incentive and
  1159. reputation system to undermine anonymity---such systems are typically
  1160. designed to encourage fairness in storage or bandwidth usage, not
  1161. fairness of provided anonymity. An adversary can attract more traffic
  1162. by performing well or can target individual users by selectively
  1163. performing, to undermine their anonymity. Typically a user who
  1164. chooses evenly from all nodes is most resistant to an adversary
  1165. targeting him, but that approach hampers the efficient use
  1166. of heterogeneous nodes.
  1167. %When a node (call him Steve) performs well for Alice, does Steve gain
  1168. %reputation with the entire system, or just with Alice? If the entire
  1169. %system, how does Alice tell everybody about her experience in a way that
  1170. %prevents her from lying about it yet still protects her identity? If
  1171. %Steve's behavior only affects Alice's behavior, does this allow Steve to
  1172. %selectively perform only for Alice, and then break her anonymity later
  1173. %when somebody (presumably Alice) routes through his node?
  1174. A possible solution is a simplified approach to the tit-for-tat
  1175. incentive scheme based on two rules: (1) each node should measure the
  1176. service it receives from adjacent nodes, and provide service relative
  1177. to the received service, but (2) when a node is making decisions that
  1178. affect its own security (such as building a circuit for its own
  1179. application connections), it should choose evenly from a sufficiently
  1180. large set of nodes that meet some minimum service
  1181. threshold~\cite{casc-rep}. This approach allows us to discourage
  1182. bad service
  1183. without opening Alice up as much to attacks. All of this requires
  1184. further study.
  1185. \subsection{Trust and discovery}
  1186. \label{subsec:trust-and-discovery}
  1187. The published Tor design is deliberately simplistic in how
  1188. new nodes are authorized and how clients are informed about Tor
  1189. nodes and their status.
  1190. All nodes periodically upload a signed description
  1191. of their locations, keys, and capabilities to each of several well-known {\it
  1192. directory servers}. These directory servers construct a signed summary
  1193. of all known Tor nodes (a ``directory''), and a signed statement of which
  1194. nodes they
  1195. believe to be operational then (a ``network status''). Clients
  1196. periodically download a directory to learn the latest nodes and
  1197. keys, and more frequently download a network status to learn which nodes are
  1198. likely to be running. Tor nodes also operate as directory caches, to
  1199. lighten the bandwidth on the directory servers.
  1200. To prevent Sybil attacks (wherein an adversary signs up many
  1201. purportedly independent nodes to increase her network view),
  1202. this design
  1203. requires the directory server operators to manually
  1204. approve new nodes. Unapproved nodes are included in the directory,
  1205. but clients
  1206. do not use them at the start or end of their circuits. In practice,
  1207. directory administrators perform little actual verification, and tend to
  1208. approve any Tor node whose operator can compose a coherent email.
  1209. This procedure
  1210. may prevent trivial automated Sybil attacks, but will do little
  1211. against a clever and determined attacker.
  1212. There are a number of flaws in this system that need to be addressed as we
  1213. move forward. First,
  1214. each directory server represents an independent point of failure: any
  1215. compromised directory server could start recommending only compromised
  1216. nodes.
  1217. Second, as more nodes join the network, %the more unreasonable it
  1218. %becomes to expect clients to know about them all.
  1219. directories
  1220. become infeasibly large, and downloading the list of nodes becomes
  1221. burdensome.
  1222. Third, the validation scheme may do as much harm as it does good. It
  1223. does not prevent clever attackers from mounting Sybil attacks,
  1224. and it may deter node operators from joining the network---if
  1225. they expect the validation process to be difficult, or they do not share
  1226. any languages in common with the directory server operators.
  1227. We could try to move the system in several directions, depending on our
  1228. choice of threat model and requirements. If we did not need to increase
  1229. network capacity to support more users, we could simply
  1230. adopt even stricter validation requirements, and reduce the number of
  1231. nodes in the network to a trusted minimum.
  1232. But, we can only do that if can simultaneously make node capacity
  1233. scale much more than we anticipate to be feasible soon, and if we can find
  1234. entities willing to run such nodes, an equally daunting prospect.
  1235. In order to address the first two issues, it seems wise to move to a system
  1236. including a number of semi-trusted directory servers, no one of which can
  1237. compromise a user on its own. Ultimately, of course, we cannot escape the
  1238. problem of a first introducer: since most users will run Tor in whatever
  1239. configuration the software ships with, the Tor distribution itself will
  1240. remain a single point of failure so long as it includes the seed
  1241. keys for directory servers, a list of directory servers, or any other means
  1242. to learn which nodes are on the network. But omitting this information
  1243. from the Tor distribution would only delegate the trust problem to each
  1244. individual user. %, most of whom are presumably less informed about how to make
  1245. %trust decisions than the Tor developers.
  1246. A well publicized, widely available, authoritatively and independently
  1247. endorsed and signed list of initial directory servers and their keys
  1248. is a possible solution. But, setting that up properly is itself a large
  1249. bootstrapping task.
  1250. %Network discovery, sybil, node admission, scaling. It seems that the code
  1251. %will ship with something and that's our trust root. We could try to get
  1252. %people to build a web of trust, but no. Where we go from here depends
  1253. %on what threats we have in mind. Really decentralized if your threat is
  1254. %RIAA; less so if threat is to application data or individuals or...
  1255. \subsection{Measuring performance and capacity}
  1256. \label{subsec:performance}
  1257. One of the paradoxes with engineering an anonymity network is that we'd like
  1258. to learn as much as we can about how traffic flows so we can improve the
  1259. network, but we want to prevent others from learning how traffic flows in
  1260. order to trace users' connections through the network. Furthermore, many
  1261. mechanisms that help Tor run efficiently
  1262. require measurements about the network.
  1263. Currently, nodes try to deduce their own available bandwidth (based on how
  1264. much traffic they have been able to transfer recently) and include this
  1265. information in the descriptors they upload to the directory. Clients
  1266. choose servers weighted by their bandwidth, neglecting really slow
  1267. servers and capping the influence of really fast ones.
  1268. %
  1269. This is, of course, eminently cheatable. A malicious node can get a
  1270. disproportionate amount of traffic simply by claiming to have more bandwidth
  1271. than it does. But better mechanisms have their problems. If bandwidth data
  1272. is to be measured rather than self-reported, it is usually possible for
  1273. nodes to selectively provide better service for the measuring party, or
  1274. sabotage the measured value of other nodes. Complex solutions for
  1275. mix networks have been proposed, but do not address the issues
  1276. completely~\cite{mix-acc,casc-rep}.
  1277. Even with no cheating, network measurement is complex. It is common
  1278. for views of a node's latency and/or bandwidth to vary wildly between
  1279. observers. Further, it is unclear whether total bandwidth is really
  1280. the right measure; perhaps clients should instead be considering nodes
  1281. based on unused bandwidth or observed throughput.
  1282. %How to measure performance without letting people selectively deny service
  1283. %by distinguishing pings. Heck, just how to measure performance at all. In
  1284. %practice people have funny firewalls that don't match up to their exit
  1285. %policies and Tor doesn't deal.
  1286. %
  1287. %Network investigation: Is all this bandwidth publishing thing a good idea?
  1288. %How can we collect stats better? Note weasel's smokeping, at
  1289. %http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  1290. %which probably gives george and steven enough info to break tor?
  1291. %
  1292. And even if we can collect and use this network information effectively,
  1293. we must ensure
  1294. that it is not more useful to attackers than to us. While it
  1295. seems plausible that bandwidth data alone is not enough to reveal
  1296. sender-recipient connections under most circumstances, it could certainly
  1297. reveal the path taken by large traffic flows under low-usage circumstances.
  1298. \subsection{Non-clique topologies}
  1299. Tor's comparatively weak threat model may allow easier scaling than
  1300. other
  1301. designs. High-latency mix networks need to avoid partitioning attacks, where
  1302. network splits let an attacker distinguish users in different partitions.
  1303. Since Tor assumes the adversary cannot cheaply observe nodes at will,
  1304. a network split may not decrease protection much.
  1305. Thus, one option when the scale of a Tor network
  1306. exceeds some size is simply to split it. Nodes could be allocated into
  1307. partitions while hampering collaborating hostile nodes from taking over
  1308. a single partition~\cite{casc-rep}.
  1309. Clients could switch between
  1310. networks, even on a per-circuit basis.
  1311. %Future analysis may uncover
  1312. %other dangers beyond those affecting mix-nets.
  1313. More conservatively, we can try to scale a single Tor network. Likely
  1314. problems with adding more servers to a single Tor network include an
  1315. explosion in the number of sockets needed on each server as more servers
  1316. join, and increased coordination overhead to keep each users' view of
  1317. the network consistent. As we grow, we will also have more instances of
  1318. servers that can't reach each other simply due to Internet topology or
  1319. routing problems.
  1320. %include restricting the number of sockets and the amount of bandwidth
  1321. %used by each node. The number of sockets is determined by the network's
  1322. %connectivity and the number of users, while bandwidth capacity is determined
  1323. %by the total bandwidth of nodes on the network. The simplest solution to
  1324. %bandwidth capacity is to add more nodes, since adding a Tor node of any
  1325. %feasible bandwidth will increase the traffic capacity of the network. So as
  1326. %a first step to scaling, we should focus on making the network tolerate more
  1327. %nodes, by reducing the interconnectivity of the nodes; later we can reduce
  1328. %overhead associated with directories, discovery, and so on.
  1329. We can address these points by reducing the network's connectivity.
  1330. Danezis~\cite{danezis:pet2003} considers
  1331. the anonymity implications of restricting routes on mix networks and
  1332. recommends an approach based on expander graphs (where any subgraph is likely
  1333. to have many neighbors). It is not immediately clear that this approach will
  1334. extend to Tor, which has a weaker threat model but higher performance
  1335. requirements: instead of analyzing the
  1336. probability of an attacker's viewing whole paths, we will need to examine the
  1337. attacker's likelihood of compromising the endpoints.
  1338. %
  1339. Tor may not need an expander graph per se: it
  1340. may be enough to have a single central subnet that is highly connected, like
  1341. an Internet backbone. % As an
  1342. %example, assume fifty nodes of relatively high traffic capacity. This
  1343. %\emph{center} forms a clique. Assume each center node can
  1344. %handle 200 connections to other nodes (including the other ones in the
  1345. %center). Assume every noncenter node connects to three nodes in the
  1346. %center and anyone out of the center that they want to. Then the
  1347. %network easily scales to c. 2500 nodes with commensurate increase in
  1348. %bandwidth.
  1349. There are many open questions: how to distribute connectivity information
  1350. (presumably nodes will learn about the central nodes
  1351. when they download Tor), whether central nodes
  1352. will need to function as a `backbone', and so on. As above,
  1353. this could reduce the amount of anonymity available from a mix-net,
  1354. but for a low-latency network where anonymity derives largely from
  1355. the edges, it may be feasible.
  1356. %In a sense, Tor already has a non-clique topology.
  1357. %Individuals can set up and run Tor nodes without informing the
  1358. %directory servers. This allows groups to run a
  1359. %local Tor network of private nodes that connects to the public Tor
  1360. %network. This network is hidden behind the Tor network, and its
  1361. %only visible connection to Tor is at those points where it connects.
  1362. %As far as the public network, or anyone observing it, is concerned,
  1363. %they are running clients.
  1364. }
  1365. \section{The Future}
  1366. \label{sec:conclusion}
  1367. Tor is the largest and most diverse low-latency anonymity network
  1368. available, but we are still in the beginning stages of deployment. Several
  1369. major questions remain.
  1370. First, will our volunteer-based approach to sustainability work in the
  1371. long term? As we add more features and destabilize the network, the
  1372. developers spend a lot of time keeping the server operators happy. Even
  1373. though Tor is free software, the network would likely stagnate and die at
  1374. this stage if the developers stopped actively working on it. We may get
  1375. an unexpected boon from the fact that we're a general-purpose overlay
  1376. network: as Tor grows more popular, other groups who need an overlay
  1377. network on the Internet are starting to adapt Tor to their needs.
  1378. %
  1379. Second, Tor is only one of many components that preserve privacy online.
  1380. For applications where it is desirable to
  1381. keep identifying information out of application traffic, someone must build
  1382. more and better protocol-aware proxies that are usable by ordinary people.
  1383. %
  1384. Third, we need to gain a reputation for social good, and learn how to
  1385. coexist with the variety of Internet services and their established
  1386. authentication mechanisms. We can't just keep escalating the blacklist
  1387. standoff forever.
  1388. %
  1389. Fourth, the current Tor
  1390. architecture does not scale even to handle current user demand. We must
  1391. find designs and incentives to let some clients relay traffic too, without
  1392. sacrificing too much anonymity.
  1393. These are difficult and open questions. Yet choosing not to solve them
  1394. means leaving most users to a less secure network or no anonymizing
  1395. network at all.
  1396. \bibliographystyle{plain} \bibliography{tor-design}
  1397. \end{document}
  1398. \clearpage
  1399. \appendix
  1400. \begin{figure}[t]
  1401. %\unitlength=1in
  1402. \centering
  1403. %\begin{picture}(6.0,2.0)
  1404. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1405. %\end{picture}
  1406. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1407. \caption{Number of Tor nodes over time, through January 2005. Lowest
  1408. line is number of exit
  1409. nodes that allow connections to port 80. Middle line is total number of
  1410. verified (registered) Tor nodes. The line above that represents nodes
  1411. that are running but not yet registered.}
  1412. \label{fig:graphnodes}
  1413. \end{figure}
  1414. \begin{figure}[t]
  1415. \centering
  1416. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1417. \caption{The sum of traffic reported by each node over time, through
  1418. January 2005. The bottom
  1419. pair show average throughput, and the top pair represent the largest 15
  1420. minute burst in each 4 hour period.}
  1421. \label{fig:graphtraffic}
  1422. \end{figure}
  1423. %Making use of nodes with little bandwidth, or high latency/packet loss.
  1424. %Running Tor nodes behind NATs, behind great-firewalls-of-China, etc.
  1425. %Restricted routes. How to propagate to everybody the topology? BGP
  1426. %style doesn't work because we don't want just *one* path. Point to
  1427. %Geoff's stuff.