challenges.tex 63 KB

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  1. \documentclass{llncs}
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  12. \begin{document}
  13. \title{Challenges in practical low-latency stream anonymity (DRAFT)}
  14. \author{Roger Dingledine and Nick Mathewson}
  15. \institute{The Free Haven Project\\
  16. \email{\{arma,nickm\}@freehaven.net}}
  17. \maketitle
  18. \pagestyle{empty}
  19. \begin{abstract}
  20. foo
  21. \end{abstract}
  22. \section{Introduction}
  23. Tor is a low-latency anonymous communication overlay network designed
  24. to be practical and usable for protecting TCP streams over the
  25. Internet~\cite{tor-design}. We have been operating a publicly deployed
  26. Tor network since October 2003 that has grown to over a hundred volunteer
  27. nodes and carries on average over 70 megabits of traffic per second.
  28. Tor has a weaker threat model than many anonymity designs in the
  29. literature, because our foremost goal is to deploy a
  30. practical and useful network for interactive (low-latency) communications.
  31. Subject to this restriction, we try to
  32. provide as much anonymity as we can. In particular, because we
  33. support interactive communications without impractically expensive padding,
  34. we fall prey to a variety
  35. of intra-network~\cite{attack-tor-oak05,flow-correlation04,bar} and
  36. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  37. Tor is secure so long as adversaries are unable to
  38. observe connections as they both enter and leave the Tor network.
  39. Therefore, Tor's defense lies in having a diverse enough set of servers
  40. that most real-world
  41. adversaries are unlikely to be in the right places to attack users.
  42. Specifically,
  43. Tor aims to resist observers and insiders by distributing each transaction
  44. over several nodes in the network. This ``distributed trust'' approach
  45. means the Tor network can be safely operated and used by a wide variety
  46. of mutually distrustful users, providing more sustainability and security
  47. than some previous attempts at anonymizing networks.
  48. The Tor network has a broad range of users, including ordinary citizens
  49. concerned about their privacy, corporations
  50. who don't want to reveal information to their competitors, and law
  51. enforcement and government intelligence agencies who need
  52. to do operations on the Internet without being noticed.
  53. Tor research and development has been funded by the U.S. Navy, for use
  54. in securing government
  55. communications, and also by the Electronic Frontier Foundation, for use
  56. in maintaining civil liberties for ordinary citizens online. The Tor
  57. protocol is one of the leading choices
  58. to be the anonymizing layer in the European Union's PRIME directive to
  59. help maintain privacy in Europe. The University of Dresden in Germany
  60. has integrated an independent implementation of the Tor protocol into
  61. their popular Java Anon Proxy anonymizing client. This wide variety of
  62. interests helps maintain both the stability and the security of the
  63. network.
  64. %awk
  65. Tor's principal research strategy, in attempting to deploy a network that is
  66. practical, useful, and anonymous, has been to insist, when trade-offs arise
  67. between these properties, on remaining useful enough to attract many users,
  68. and practical enough to support them. Subject to these
  69. constraints, we aim to maximize anonymity. This is not the only possible
  70. direction in anonymity research: designs exist that provide more anonymity
  71. than Tor at the expense of significantly increased resource requirements, or
  72. decreased flexibility in application support (typically because of increased
  73. latency). Such research does not typically abandon aspirations towards
  74. deployability or utility, but instead tries to maximize deployability and
  75. utility subject to a certain degree of inherent anonymity (inherent because
  76. usability and practicality affect usage which affects the actual anonymity
  77. provided by the network \cite{back01,econymics}). We believe that these
  78. approaches can be promising and useful, but that by focusing on deploying a
  79. usable system in the wild, Tor helps us experiment with the actual parameters
  80. of what makes a system ``practical'' for volunteer operators and ``useful''
  81. for home users, and helps illuminate undernoticed issues which any deployed
  82. volunteer anonymity network will need to address.
  83. While~\cite{tor-design} gives an overall view of the Tor design and goals,
  84. this paper describes the policy and technical issues that Tor faces as
  85. we continue deployment. Rather than trying to provide complete solutions
  86. to every problem here, we lay out the assumptions and constraints
  87. that we have observed through deploying Tor in the wild. In doing so, we
  88. aim to create a research agenda for others to
  89. help in addressing these issues. Section~\ref{sec:what-is-tor} gives an
  90. overview of the Tor
  91. design and ours goals. Sections~\ref{sec:crossroads-policy}
  92. and~\ref{sec:crossroads-technical} go on to describe the practical challenges,
  93. both policy and technical respectively, that stand in the way of moving
  94. from a practical useful network to a practical useful anonymous network.
  95. %\section{What Is Tor}
  96. \section{Distributed trust: safety in numbers}
  97. \label{sec:what-is-tor}
  98. Here we give a basic overview of the Tor design and its properties. For
  99. details on the design, assumptions, and security arguments, we refer
  100. the reader to the Tor design paper~\cite{tor-design}.
  101. Tor provides \emph{forward privacy}, so that users can connect to
  102. Internet sites without revealing their logical or physical locations
  103. to those sites or to observers. It also provides \emph{location-hidden
  104. services}, so that critical servers can support authorized users without
  105. giving adversaries an effective vector for physical or online attacks.
  106. The design provides this protection even when a portion of its own
  107. infrastructure is controlled by an adversary.
  108. To create a private network pathway with Tor, the user's software (client)
  109. incrementally builds a \emph{circuit} of encrypted connections through
  110. servers on the network. The circuit is extended one hop at a time, and
  111. each server along the way knows only which server gave it data and which
  112. server it is giving data to. No individual server ever knows the complete
  113. path that a data packet has taken. The client negotiates a separate set
  114. of encryption keys for each hop along the circuit to ensure that each
  115. hop can't trace these connections as they pass through.
  116. Once a circuit has been established, many kinds of data can be exchanged
  117. and several different sorts of software applications can be deployed over
  118. the Tor network. Because each server sees no more than one hop in the
  119. circuit, neither an eavesdropper nor a compromised server can use traffic
  120. analysis to link the connection's source and destination. Tor only works
  121. for TCP streams and can be used by any application with SOCKS support.
  122. For efficiency, the Tor software uses the same circuit for connections
  123. that happen within the same minute or so. Later requests are given a new
  124. circuit, to prevent long-term linkability between different actions by
  125. a single user.
  126. Tor also makes it possible for users to hide their locations while
  127. offering various kinds of services, such as web publishing or an instant
  128. messaging server. Using Tor ``rendezvous points'', other Tor users can
  129. connect to these hidden services, each without knowing the other's network
  130. identity.
  131. Tor attempts to anonymize the transport layer, not the application layer, so
  132. application protocols that include personally identifying information need
  133. additional application-level scrubbing proxies, such as
  134. Privoxy~\cite{privoxy} for HTTP. Furthermore, Tor does not permit arbitrary
  135. IP packets; it only anonymizes TCP and DNS, and only supports connections via
  136. SOCKS (see Section \ref{subsec:tcp-vs-ip}).
  137. Tor differs from other deployed systems for traffic analysis resistance
  138. in its security and flexibility. Mix networks such as
  139. Mixmaster~\cite{mixmaster-spec} or its successor Mixminion~\cite{minion-design}
  140. gain the highest degrees of anonymity at the expense of introducing highly
  141. variable delays, thus making them unsuitable for applications such as web
  142. browsing that require quick response times. Commercial single-hop
  143. proxies~\cite{anonymizer} present a single point of failure, where
  144. a single compromise can expose all users' traffic, and a single-point
  145. eavesdropper can perform traffic analysis on the entire network.
  146. Also, their proprietary implementations place any infrastucture that
  147. depends on these single-hop solutions at the mercy of their providers'
  148. financial health as well as network security.
  149. No organization can achieve this security on its own. If a single
  150. corporation or government agency were to build a private network to
  151. protect its operations, any connections entering or leaving that network
  152. would be obviously linkable to the controlling organization. The members
  153. and operations of that agency would be easier, not harder, to distinguish.
  154. Instead, to protect our networks from traffic analysis, we must
  155. collaboratively blend the traffic from many organizations and private
  156. citizens, so that an eavesdropper can't tell which users are which,
  157. and who is looking for what information. By bringing more users onto
  158. the network, all users become more secure~\cite{econymics}.
  159. Naturally, organizations will not want to depend on others for their
  160. security. If most participating providers are reliable, Tor tolerates
  161. some hostile infiltration of the network. For maximum protection,
  162. the Tor design includes an enclave approach that lets data be encrypted
  163. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  164. hasn't been read or modified. This even works for Internet services that
  165. don't have built-in encryption and authentication, such as unencrypted
  166. HTTP or chat, and it requires no modification of those services to do so.
  167. As of January 2005, the Tor network has grown to around a hundred servers
  168. on four continents, with a total capacity exceeding 1Gbit/s. Appendix A
  169. shows a graph of the number of working servers over time, as well as a
  170. graph of the number of bytes being handled by the network over time. At
  171. this point the network is sufficiently diverse for further development
  172. and testing; but of course we always encourage and welcome new servers
  173. to join the network.
  174. %Tor doesn't try to provide steg (but see Section~\ref{subsec:china}), or
  175. %the other non-goals listed in tor-design.
  176. Tor is not the only anonymity system that aims to be practical and useful.
  177. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  178. open proxies around the Internet~\cite{open-proxies}, can provide good
  179. performance and some security against a weaker attacker. Dresden's Java
  180. Anon Proxy~\cite{web-mix} provides similar functionality to Tor but only
  181. handles web browsing rather than arbitrary TCP. Also, JAP's network
  182. topology uses cascades (fixed routes through the network); since without
  183. end-to-end padding it is just as vulnerable as Tor to end-to-end timing
  184. attacks, its dispersal properties are therefore worse than Tor's.
  185. %Some peer-to-peer file-sharing overlay networks such as
  186. %Freenet~\cite{freenet} and Mute~\cite{mute}
  187. Zero-Knowledge Systems' commercial Freedom
  188. network~\cite{freedom21-security} was even more flexible than Tor in
  189. that it could transport arbitrary IP packets, and it also supported
  190. pseudonymous access rather than just anonymous access; but it had
  191. a different approach to sustainability (collecting money from users
  192. and paying ISPs to run servers), and has shut down due to financial
  193. load. Finally, more scalable designs like Tarzan~\cite{tarzan:ccs02} and
  194. MorphMix~\cite{morphmix:fc04} have been proposed in the literature, but
  195. have not yet been fielded. We direct the interested reader to Section
  196. 2 of~\cite{tor-design} for a more indepth review of related work.
  197. %six-four. crowds. i2p.
  198. have a serious discussion of morphmix's assumptions, since they would
  199. seem to be the direct competition. in fact tor is a flexible architecture
  200. that would encompass morphmix, and they're nearly identical except for
  201. path selection and node discovery. and the trust system morphmix has
  202. seems overkill (and/or insecure) based on the threat model we've picked.
  203. % this para should probably move to the scalability / directory system. -RD
  204. \section{Threat model}
  205. \label{sec:threat-model}
  206. Tor does not attempt to defend against a global observer. Any adversary who
  207. can see a user's connection to the Tor network, and who can see the
  208. corresponding connection as it exits the Tor network, can use the timing
  209. correlation between the two connections to confirm the user's chosen
  210. communication partners. Defeating this attack would seem to require
  211. introducing a prohibitive degree of traffic padding between the user and the
  212. network, or introducing an unacceptable degree of latency (but see
  213. Section \ref{subsec:mid-latency}). Thus, Tor only
  214. attempts to defend against external observers who cannot observe both sides of a
  215. user's connection.
  216. Against internal attackers, who sign up Tor servers, the situation is more
  217. complicated. In the simplest case, if an adversary has compromised $c$ of
  218. $n$ servers on the Tor network, then the adversary will be able to compromise
  219. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  220. initiator chooses hops randomly). But there are
  221. complicating factors:
  222. \begin{tightlist}
  223. \item If the user continues to build random circuits over time, an adversary
  224. is pretty certain to see a statistical sample of the user's traffic, and
  225. thereby can build an increasingly accurate profile of her behavior. (See
  226. \ref{subsec:helper-nodes} for possible solutions.)
  227. \item If an adversary controls a popular service outside of the Tor network,
  228. he can be certain of observing all connections to that service; he
  229. therefore will trace connections to that service with probability
  230. $\frac{c}{n}$.
  231. \item Users do not in fact choose servers with uniform probability; they
  232. favor servers with high bandwidth, and exit servers that permit connections
  233. to their favorite services.
  234. \end{tightlist}
  235. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  236. %the last hop is not $c/n$ since that doesn't take the destination (website)
  237. %into account. so in cases where the adversary does not also control the
  238. %final destination we're in good shape, but if he *does* then we'd be better
  239. %off with a system that lets each hop choose a path.
  240. %
  241. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  242. % dest, we would be just as well off with such as system.'' ? If not, why
  243. % not? -nm
  244. % Sure. In fact, better off, since they seem to scale more easily. -rd
  245. in practice tor's threat model is based entirely on the goal of dispersal
  246. and diversity. george and steven describe an attack \cite{attack-tor-oak05} that
  247. lets them determine the nodes used in a circuit; yet they can't identify
  248. alice or bob through this attack. so it's really just the endpoints that
  249. remain secure. and the enclave model seems particularly threatened by
  250. this, since this attack lets us identify endpoints when they're servers.
  251. see \ref{subsec:helper-nodes} for discussion of some ways to address this
  252. issue.
  253. see \ref{subsec:routing-zones} for discussion of larger
  254. adversaries and our dispersal goals.
  255. [this section will get written once the rest of the paper is farther along]
  256. \section{Crossroads: Policy issues}
  257. \label{sec:crossroads-policy}
  258. Many of the issues the Tor project needs to address are not just a
  259. matter of system design or technology development. In particular, the
  260. Tor project's \emph{image} with respect to its users and the rest of
  261. the Internet impacts the security it can provide.
  262. As an example to motivate this section, some U.S.~Department of Enery
  263. penetration testing engineers are tasked with compromising DoE computers
  264. from the outside. They only have a limited number of ISPs from which to
  265. launch their attacks, and they found that the defenders were recognizing
  266. attacks because they came from the same IP space. These engineers wanted
  267. to use Tor to hide their tracks. First, from a technical standpoint,
  268. Tor does not support the variety of IP packets one would like to use in
  269. such attacks (see Section \ref{subsec:ip-vs-tcp}). But aside from this,
  270. we also decided that it would probably be poor precedent to encourage
  271. such use---even legal use that improves national security---and managed
  272. to dissuade them.
  273. With this image issue in mind, this section discusses the Tor user base and
  274. Tor's interaction with other services on the Internet.
  275. \subsection{Image and security}
  276. A growing field of papers argue that usability for anonymity systems
  277. contributes directly to their security, because how usable the system
  278. is impacts the possible anonymity set~\cite{back01,econymics}. Or
  279. conversely, an unusable system attracts few users and thus can't provide
  280. much anonymity.
  281. This phenomenon has a second-order effect: knowing this, users should
  282. choose which anonymity system to use based in part on how usable
  283. \emph{others} will find it, in order to get the protection of a larger
  284. anonymity set. Thus we might replace the adage ``usability is a security
  285. parameter''~\cite{back01} with a new one: ``perceived usability is a
  286. security parameter.'' From here we can better understand the effects
  287. of publicity and advertising on security: the more convincing your
  288. advertising, the more likely people will believe you have users, and thus
  289. the more users you will attract. Perversely, over-hyped systems (if they
  290. are not too broken) may be a better choice than modestly promoted ones,
  291. if the hype attracts more users~\cite{usability-network-effect}.
  292. So it follows that we should come up with ways to accurately communicate
  293. the available security levels to the user, so she can make informed
  294. decisions. Dresden's JAP project aims to do this, by including a
  295. comforting `anonymity meter' dial in the software's graphical interface,
  296. giving the user an impression of the level of protection for her current
  297. traffic.
  298. However, there's a catch. For users to share the same anonymity set,
  299. they need to act like each other. An attacker who can distinguish
  300. a given user's traffic from the rest of the traffic will not be
  301. distracted by other users on the network. For high-latency systems like
  302. Mixminion, where the threat model is based on mixing messages with each
  303. other, there's an arms race between end-to-end statistical attacks and
  304. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  305. But for low-latency systems like Tor, end-to-end \emph{traffic
  306. confirmation} attacks~\cite{danezis-pet2004,SS03,defensive-dropping}
  307. allow an attacker who watches or controls both ends of a communication
  308. to use statistics to correlate packet timing and volume, quickly linking
  309. the initiator to her destination. This is why Tor's threat model is
  310. based on preventing the adversary from observing both the initiator and
  311. the responder.
  312. Like Tor, the current JAP implementation does not pad connections
  313. (apart from using small fixed-size cells for transport). In fact,
  314. its cascade-based network toplogy may be even more vulnerable to these
  315. attacks, because the network has fewer endpoints. JAP was born out of
  316. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  317. every user had a fixed bandwidth allocation, but in its current context
  318. as a general Internet web anonymizer, adding sufficient padding to JAP
  319. would be prohibitively expensive.\footnote{Even if they could find and
  320. maintain extra funding to run higher-capacity nodes, our experience with
  321. users suggests that many users would not accept the increased per-user
  322. bandwidth requirements, leading to an overall much smaller user base. But
  323. see Section \ref{subsec:mid-latency}.} Therefore, since under this threat
  324. model the number of concurrent users does not seem to have much impact
  325. on the anonymity provided, we suggest that JAP's anonymity meter is not
  326. correctly communicating security levels to its users.
  327. On the other hand, while the number of active concurrent users may not
  328. matter as much as we'd like, it still helps to have some other users
  329. who use the network. We investigate this issue in the next section.
  330. \subsection{Reputability}
  331. Another factor impacting the network's security is its reputability:
  332. the perception of its social value based on its current user base. If I'm
  333. the only user who has ever downloaded the software, it might be socially
  334. accepted, but I'm not getting much anonymity. Add a thousand Communists,
  335. and I'm anonymous, but everyone thinks I'm a Commie. Add a thousand
  336. random citizens (cancer survivors, privacy enthusiasts, and so on)
  337. and now I'm harder to profile.
  338. The more cancer survivors on Tor, the better for the human rights
  339. activists. The more script kiddies, the worse for the normal users. Thus,
  340. reputability is an anonymity issue for two reasons. First, it impacts
  341. the sustainability of the network: a network that's always about to be
  342. shut down has difficulty attracting and keeping users, so its anonymity
  343. set suffers. Second, a disreputable network attracts the attention of
  344. powerful attackers who may not mind revealing the identities of all the
  345. users to uncover a few bad ones.
  346. While people therefore have an incentive for the network to be used for
  347. ``more reputable'' activities than their own, there are still tradeoffs
  348. involved when it comes to anonymity. To follow the above example, a
  349. network used entirely by cancer survivors might welcome some Communists
  350. onto the network, though of course they'd prefer a wider variety of users.
  351. Reputability becomes even more tricky in the case of privacy networks,
  352. since the good uses of the network (such as publishing by journalists in
  353. dangerous countries) are typically kept private, whereas network abuses
  354. or other problems tend to be more widely publicized.
  355. The impact of public perception on security is especially important
  356. during the bootstrapping phase of the network, where the first few
  357. widely publicized uses of the network can dictate the types of users it
  358. attracts next.
  359. \subsection{Usability and bandwidth and sustainability and incentives}
  360. low-pain-threshold users go away until all users are willing to use it
  361. Sustainability. Previous attempts have been commercial which we think
  362. adds a lot of unnecessary complexity and accountability. Freedom didn't
  363. collect enough money to pay its servers; JAP bandwidth is supported by
  364. continued money, and they periodically ask what they will do when it
  365. dries up.
  366. "outside of academia, jap has just lost, permanently"
  367. [nick will write this section]
  368. \subsection{Tor and file-sharing}
  369. [nick will write this section]
  370. Bittorrent and dmca. Should we add an IDS to autodetect protocols and
  371. snipe them?
  372. because only at the exit is it evident what port or protocol a given
  373. tor stream is, you can't choose not to carry file-sharing traffic.
  374. hibernation vs rate-limiting: do we want diversity or throughput? i
  375. think we're shifting back to wanting diversity.
  376. \subsection{Tor and blacklists}
  377. Takedowns and efnet abuse and wikipedia complaints and irc
  378. networks.
  379. It was long expected that, alongside Tor's legitimate users, it would also
  380. attract troublemakers who exploited Tor in order to abuse services on the
  381. Internet. Our initial answer to this situation was to use ``exit policies''
  382. to allow individual Tor servers to block access to specific IP/port ranges.
  383. This approach was meant to make operators more willing to run Tor by allowing
  384. them to prevent their servers from being used for abusing particular
  385. services. For example, all Tor servers currently block SMTP (port 25), in
  386. order to avoid being used to send spam.
  387. This approach is useful, but is insufficient for two reasons. First, since
  388. it is not possible to force all ORs to block access to any given service,
  389. many of those services try to block Tor instead. More broadly, while being
  390. blockable is important to being good netizens, we would like to encourage
  391. services to allow anonymous access; services should not need to decide
  392. between blocking legitimate anonymous use and allowing unlimited abuse.
  393. This is potentially a bigger problem than it may appear.
  394. On the one hand, if people want to refuse connections from you on
  395. their servers it would seem that they should be allowed to. But, a
  396. possible major problem with the blocking of Tor is that it's not just
  397. the decision of the individual server administrator whose deciding if
  398. he wants to post to wikipedia from his Tor node address or allow
  399. people to read wikipedia anonymously through his Tor node. If e.g.,
  400. s/he comes through a campus or corporate NAT, then the decision must
  401. be to have the entire population behind it able to have a Tor exit
  402. node or write access to wikipedia. This is a loss for both of us (Tor
  403. and wikipedia). We don't want to compete for (or divvy up) the NAT
  404. protected entities of the world.
  405. (A related problem is that many IP blacklists are not terribly fine-grained.
  406. No current IP blacklist, for example, allow a service provider to blacklist
  407. only those Tor servers that allow access to a specific IP or port, even
  408. though this information is readily available. One IP blacklist even bans
  409. every class C network that contains a Tor server, and recommends banning SMTP
  410. from these networks even though Tor does not allow SMTP at all.)
  411. Problems of abuse occur mainly with services such as IRC networks and
  412. Wikipedia, which rely on IP-blocking to ban abusive users. While at first
  413. blush this practice might seem to depend on the anachronistic assumption that
  414. each IP is an identifier for a single user, it is actually more reasonable in
  415. practice: it assumes that non-proxy IPs are a costly resource, and that an
  416. abuser can not change IPs at will. By blocking IPs which are used by Tor
  417. servers, open proxies, and service abusers, these systems hope to make
  418. ongoing abuse difficult. Although the system is imperfect, it works
  419. tolerably well for them in practice.
  420. But of course, we would prefer that legitimate anonymous users be able to
  421. access abuse-prone services. One conceivable approach would be to require
  422. would-be IRC users, for instance, to register accounts if they wanted to
  423. access the IRC network from Tor. But in practise, this would not
  424. significantly impede abuse if creating new accounts were easily automatable;
  425. % XXX captcha
  426. this is why services use IP blocking. In order to deter abuse, pseudonymous
  427. identities need to impose a significant switching cost in resources or human
  428. time.
  429. Once approach, similar to that taken by Freedom, would be to bootstrap some
  430. non-anonymous costly identification mechanism to allow access to a
  431. blind-signature pseudonym protocol. This would effectively create costly
  432. pseudonyms, which services could require in order to allow anonymous access.
  433. This approach has difficulties in practise, however:
  434. \begin{tightlist}
  435. \item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  436. be a shame to require payment in order to make Tor useful, or to make
  437. non-paying users second-class citizens.
  438. \item It is hard to think of an underlying resource that would actually work.
  439. We could use IP addresses, but that's the problem, isn't it?
  440. \item Managing single sign-on services is not considered a well-solved
  441. problem in practice. If Microsoft can't get universal acceptance for
  442. passport, why do we think that a Tor-specific solution would do any good?
  443. \item Even if we came up with a perfect authentication system for our needs,
  444. there's no guarantee that any service would actually start using it. It
  445. would require a nonzero effort for them to support it, and it might just
  446. be less hassle for them to block tor anyway.
  447. \end{tightlist}
  448. Squishy IP based ``authentication'' and ``authorization'' is a reality
  449. we must contend with. We should say something more about the analogy
  450. with SSNs.
  451. \subsection{Other}
  452. [Once you build a generic overlay network, everybody wants to use it.]
  453. Tor's scope: How much should Tor aim to do? Applications that leak
  454. data: we can say they're not our problem, but they're somebody's problem.
  455. Also, the more widely deployed Tor becomes, the more people who need a
  456. deployed overlay network tell us they'd like to use us if only we added
  457. the following more features. For example, Blossom \cite{blossom} and
  458. random community wireless projects both want source-routable overlay
  459. networks for their own purposes. Fortunately, our modular design separates
  460. routing from node discovery; so we could implement Morphmix in Tor just
  461. by implementing the Morphmix-specific node discovery and path selection
  462. pieces. On the other hand, we could easily get distracted building a
  463. general-purpose overlay library, and we're only a few developers.
  464. [arma will work on this]
  465. %Should we allow revocation of anonymity if a threshold of
  466. %servers want to?
  467. Logging. Making logs not revealing. A happy coincidence that verbose
  468. logging is our \#2 performance bottleneck. Is there a way to detect
  469. modified servers, or to have them volunteer the information that they're
  470. logging verbosely? Would that actually solve any attacks?
  471. \section{Crossroads: Scaling and Design choices}
  472. \label{sec:crossroads-design}
  473. \subsection{Transporting the stream vs transporting the packets}
  474. \label{subsec:tcp-vs-ip}
  475. We periodically run into ex ZKS employees who tell us that the process of
  476. anonymizing IPs should ``obviously'' be done at the IP layer. Here are
  477. the issues that need to be resolved before we'll be ready to switch Tor
  478. over to arbitrary IP traffic.
  479. \begin{enumerate}
  480. \setlength{\itemsep}{0mm}
  481. \setlength{\parsep}{0mm}
  482. \item \emph{IP packets reveal OS characteristics.} We still need to do
  483. IP-level packet normalization, to stop things like IP fingerprinting
  484. attacks. There likely exist libraries that can help with this.
  485. \item \emph{Application-level streams still need scrubbing.} We still need
  486. Tor to be easy to integrate with user-level application-specific proxies
  487. such as Privoxy. So it's not just a matter of capturing packets and
  488. anonymizing them at the IP layer.
  489. \item \emph{Certain protocols will still leak information.} For example,
  490. DNS requests destined for my local DNS servers need to be rewritten
  491. to be delivered to some other unlinkable DNS server. This requires
  492. understanding the protocols we are transporting.
  493. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  494. approach that can provide security despite
  495. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  496. never publicly specified. %, and we believe it's likely vulnerable to tagging
  497. %attacks \cite{tor-design}.
  498. Also, TLS over UDP is not implemented or even
  499. specified, though some early work has begun on that~\cite{dtls}.
  500. \item \emph{We'll still need to tune network parameters}. Since the above
  501. encryption system will likely need sequence numbers (and maybe more) to do
  502. replay detection, handle duplicate frames, etc, we will be reimplementing
  503. some subset of TCP anyway.
  504. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  505. IDS.} Our server operators tell us that exit policies are one of
  506. the main reasons they're willing to run Tor.
  507. Adding an Intrusion Detection System to handle exit policies would
  508. increase the security complexity of Tor, and would likely not work anyway,
  509. as evidenced by the entire field of IDS and counter-IDS papers. Many
  510. potential abuse issues are resolved by the fact that Tor only transports
  511. valid TCP streams (as opposed to arbitrary IP including malformed packets
  512. and IP floods), so exit policies become even \emph{more} important as
  513. we become able to transport IP packets. We also need a way to compactly
  514. characterize the exit policies and let clients parse them to decide
  515. which nodes will allow which packets to exit.
  516. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  517. support hidden service {\tt{.onion}} addresses, and other special addresses
  518. like {\tt{.exit}} (see Section \ref{subsec:}), by intercepting the addresses
  519. when they are passed to the Tor client.
  520. \end{enumerate}
  521. This list is discouragingly long right now, but we recognize that it
  522. would be good to investigate each of these items in further depth and to
  523. understand which are actual roadblocks and which are easier to resolve
  524. than we think. We certainly wouldn't mind if Tor one day is able to
  525. transport a greater variety of protocols.
  526. \subsection{Mid-latency}
  527. \label{subsec:mid-latency}
  528. Though Tor has always been designed to be practical and usable first
  529. with as much anonymity as can be built in subject to those goals, we
  530. have contemplated that users might need resistance to at least simple
  531. traffic confirmation attacks. Raising the latency of communication
  532. slightly might make this feasible. If the latency could be kept to two
  533. or three times its current overhead, this might be acceptable to the
  534. majority of Tor users. However, it might also destroy much of the user
  535. base, and it is difficult to know in advance. Note also that in
  536. practice, as the network is growing and we accept cable modem, DSL
  537. nodes, and more nodes in various continents, we're \emph{already}
  538. looking at many-second delays for some transactions. The engineering
  539. required to get this lower is going to be extremely hard. It's worth
  540. considering how hard it would be to accept the fixed (higher) latency
  541. and improve the protection we get from it. Thus, it may be most
  542. practical to run a mid-latency option over the Tor network for those
  543. users either willing to experiment or in need of more a priori
  544. anonymity in the network. This will allow us to experiment with both
  545. the anonymity provided and the interest on the part of users.
  546. Adding a mid-latency option should not require significant fundamental
  547. change to the Tor client or server design; circuits can be labeled as
  548. low or mid latency on servers as they are set up. Low-latency traffic
  549. would be processed as now. Packets on circuits that are mid-latency
  550. would be sent in uniform size chunks at synchronized intervals. To
  551. some extent the chunking is already done because traffic moves through
  552. the network in uniform size cells, but this would occur at a coarser
  553. granularity. If servers forward these chunks in roughly synchronous
  554. fashion, it will increase the similarity of data stream timing
  555. signatures. By experimenting with the granularity of data chunks and
  556. of synchronization we can attempt once again to optimize for both
  557. usability and anonymity. Unlike in \cite{sync-batching}, it may be
  558. impractical to synchronize on network batches by dropping chunks from
  559. a batch that arrive late at a given node---unless Tor moves away from
  560. stream processing to a more loss-tolerant processing of traffic (cf.\
  561. Section~\ref{subsec:tcp-vs-ip}). In other words, there would
  562. probably be no direct attempt to synchronize on batches of data
  563. entering the Tor network at the same time. Rather, it is the link
  564. level batching that will add noise to the traffic patterns exiting the
  565. network. Similarly, if end-to-end traffic confirmation is the
  566. concern, there is little point in mixing. It might also be feasible to
  567. pad chunks to uniform size as is done now for cells; if this is link
  568. padding rather than end-to-end, then it will take less overhead,
  569. especially in bursty environments. This is another way in which it
  570. would be fairly practical to set up a mid-latency option within the
  571. existing Tor network. Other padding regimens might supplement the
  572. mid-latency option; however, we should continue the caution with which
  573. we have always approached padding lest the overhead cost us too much
  574. performance or too many volunteers.
  575. The distinction between traffic confirmation and traffic analysis is
  576. not as practically cut and dried as we might wish. In \cite{hintz-pet02} it was
  577. shown that if latencies to and/or data volumes of various popular
  578. responder destinations are catalogued, it may not be necessary to
  579. observe both ends of a stream to confirm a source-destination link.
  580. These are likely to entail high variability and massive storage since
  581. % XXX hintz-pet02 just looked at data volumes of the sites. this
  582. % doesn't require much variability or storage. I think it works
  583. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  584. % attack another level further, to narrow down where you could be
  585. % based on an intersection attack on subpages in a website. -RD
  586. routes through the network to each site will be random even if they
  587. have relatively unique latency or volume characteristics. So these do
  588. not seem an immediate practical threat. Further along similar lines, in
  589. \cite{attack-tor-oak05}, it was shown that an outside attacker can
  590. trace a stream through the Tor network while a stream is still active
  591. simply by observing the latency of his own traffic sent through
  592. various Tor nodes. These attacks are especially significant since they
  593. counter previous results that running one's own onion router protects
  594. better than using the network from the outside. The attacks do not
  595. show the client address, only the first server within the Tor network,
  596. making helper nodes all the more worthy of exploration for enclave
  597. protection. Setting up a mid-latency subnet as described above would
  598. be another significant step to evaluating resistance to such attacks.
  599. The attacks in \cite{attack-tor-oak05} are also dependent on
  600. cooperation of the responding application or the ability to modify or
  601. monitor the responder stream, in order of decreasing attack
  602. effectiveness. So, another way to counter these attacks in some cases
  603. would be to employ caching of responses. This is infeasible for
  604. application data that is not relatively static and from frequently
  605. visited sites; however, it might be useful for DNS lookups. This is
  606. also likely to be trading one practical threat for another. To be
  607. useful, such caches would need to be distributed to any likely exit
  608. nodes of recurred requests for the same data. Aside from the logistic
  609. difficulties and overhead of distribution, they constitute a collected
  610. record of destinations and/or data visited by Tor users. While
  611. limited to network insiders, given the need for wide distribution
  612. they could serve as useful data to an attacker deciding which locations
  613. to target for confirmation.
  614. [nick will work on this]
  615. \subsection{Application support: socks doesn't solve all our problems}
  616. socks4a isn't everywhere. the dns problem. etc.
  617. nick will work on this.
  618. \subsection{Measuring performance and capacity}
  619. How to measure performance without letting people selectively deny service
  620. by distinguishing pings. Heck, just how to measure performance at all. In
  621. practice people have funny firewalls that don't match up to their exit
  622. policies and Tor doesn't deal.
  623. Network investigation: Is all this bandwidth publishing thing a good idea?
  624. How can we collect stats better? Note weasel's smokeping, at
  625. http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  626. which probably gives george and steven enough info to break tor?
  627. [nick will work on this section, unless arma gets there first]
  628. \subsection{Anonymity benefits for running a server}
  629. Does running a server help you or harm you? George's Oakland attack.
  630. Plausible deniability -- without even running your traffic through Tor!
  631. But nobody knows about Tor, and the legal situation is fuzzy, so this
  632. isn't very true really.
  633. We have to pick the path length so adversary can't distinguish client from
  634. server (how many hops is good?).
  635. in practice, plausible deniability is hypothetical and doesn't seem very
  636. convincing. if ISPs find the activity antisocial, they don't care *why*
  637. your computer is doing that behavior.
  638. [arma will write this section]
  639. \subsection{Helper nodes}
  640. When does fixing your entry or exit node help you?
  641. Helper nodes in the literature don't deal with churn, and
  642. especially active attacks to induce churn.
  643. Do general DoS attacks have anonymity implications? See e.g. Adam
  644. Back's IH paper, but I think there's more to be pointed out here.
  645. Game theory for helper nodes: if Alice offers a hidden service on a
  646. server (enclave model), and nobody ever uses helper nodes, then against
  647. George+Steven's attack she's totally nailed. If only Alice uses a helper
  648. node, then she's still identified as the source of the data. If everybody
  649. uses a helper node (including Alice), then the attack identifies the
  650. helper node and also Alice, and knows which one is which. If everybody
  651. uses a helper node (but not Alice), then the attacker figures the real
  652. source was a client that is using Alice as a helper node. [How's my
  653. logic here?]
  654. point to routing-zones section re: helper nodes to defend against
  655. big stuff.
  656. [nick will write this section]
  657. \subsection{Location-hidden services}
  658. [arma will write this section]
  659. Survivable services are new in practice, yes? Hidden services seem
  660. less hidden than we'd like, since they stay in one place and get used
  661. a lot. They're the epitome of the need for helper nodes. This means
  662. that using Tor as a building block for Free Haven is going to be really
  663. hard. Also, they're brittle in terms of intersection and observation
  664. attacks. Would be nice to have hot-swap services, but hard to design.
  665. people are using hidden services as a poor man's vpn and firewall-buster.
  666. rather than playing with dyndns and trying to pierce holes in their
  667. firewall (say, so they can ssh in from the outside), they run a hidden
  668. service on the inside and then rendezvous with that hidden service
  669. externally.
  670. in practice, sites like bloggers without borders (www.b19s.org) are
  671. running tor servers but more important are advertising a hidden-service
  672. address on their front page. doing this can provide increased robustness
  673. if they used the dual-IP approach we describe in tor-design, but in
  674. practice they do it to a) increase visibility of the tor project and their
  675. support for privacy, and b) to offer a way for their users, using vanilla
  676. software, to get end-to-end encryption and end-to-end authentication to
  677. their website.
  678. \subsection{Trust and discovery}
  679. [arma will edit this and expand/retract it]
  680. The published Tor design adopted a deliberately simplistic design for
  681. authorizing new nodes and informing clients about servers and their status.
  682. In the early Tor designs, all ORs periodically uploaded a signed description
  683. of their locations, keys, and capabilities to each of several well-known {\it
  684. directory servers}. These directory servers constructed a signed summary
  685. of all known ORs (a ``directory''), and a signed statement of which ORs they
  686. believed to be operational at any given time (a ``network status''). Clients
  687. periodically downloaded a directory in order to learn the latest ORs and
  688. keys, and more frequently downloaded a network status to learn which ORs are
  689. likely to be running. ORs also operate as directory caches, in order to
  690. lighten the bandwidth on the authoritative directory servers.
  691. In order to prevent Sybil attacks (wherein an adversary signs up many
  692. purportedly independent servers in order to increase her chances of observing
  693. a stream as it enters and leaves the network), the early Tor directory design
  694. required the operators of the authoritative directory servers to manually
  695. approve new ORs. Unapproved ORs were included in the directory, but clients
  696. did not use them at the start or end of their circuits. In practice,
  697. directory administrators performed little actual verification, and tended to
  698. approve any OR whose operator could compose a coherent email. This procedure
  699. may have prevented trivial automated Sybil attacks, but would do little
  700. against a clever attacker.
  701. There are a number of flaws in this system that need to be addressed as we
  702. move forward. They include:
  703. \begin{tightlist}
  704. \item Each directory server represents an independent point of failure; if
  705. any one were compromised, it could immediately compromise all of its users
  706. by recommending only compromised ORs.
  707. \item The more servers appear join the network, the more unreasonable it
  708. becomes to expect clients to know about them all. Directories
  709. become unfeasibly large, and downloading the list of servers becomes
  710. burdonsome.
  711. \item The validation scheme may do as much harm as it does good. It is not
  712. only incapable of preventing clever attackers from mounting Sybil attacks,
  713. but may deter server operators from joining the network. (For instance, if
  714. they expect the validation process to be difficult, or if they do not share
  715. any languages in common with the directory server operators.)
  716. \end{tightlist}
  717. We could try to move the system in several directions, depending on our
  718. choice of threat model and requirements. If we did not need to increase
  719. network capacity in order to support more users, there would be no reason not
  720. to adopt even stricter validation requirements, and reduce the number of
  721. servers in the network to a trusted minimum. But since we want Tor to work
  722. for as many users as it can, we need XXXXX
  723. In order to address the first two issues, it seems wise to move to a system
  724. including a number of semi-trusted directory servers, no one of which can
  725. compromise a user on its own. Ultimately, of course, we cannot escape the
  726. problem of a first introducer: since most users will run Tor in whatever
  727. configuration the software ships with, the Tor distribution itself will
  728. remain a potential single point of failure so long as it includes the seed
  729. keys for directory servers, a list of directory servers, or any other means
  730. to learn which servers are on the network. But omitting this information
  731. from the Tor distribution would only delegate the trust problem to the
  732. individual users, most of whom are presumably less informed about how to make
  733. trust decisions than the Tor developers.
  734. %Network discovery, sybil, node admission, scaling. It seems that the code
  735. %will ship with something and that's our trust root. We could try to get
  736. %people to build a web of trust, but no. Where we go from here depends
  737. %on what threats we have in mind. Really decentralized if your threat is
  738. %RIAA; less so if threat is to application data or individuals or...
  739. \section{Crossroads: Scaling}
  740. %\label{sec:crossroads-scaling}
  741. %P2P + anonymity issues:
  742. Tor is running today with hundreds of servers and tens of thousands of
  743. users, but it will certainly not scale to millions.
  744. Scaling Tor involves three main challenges. First is safe server
  745. discovery, both bootstrapping -- how a Tor client can robustly find an
  746. initial server list -- and ongoing -- how a Tor client can learn about
  747. a fair sample of honest servers and not let the adversary control his
  748. circuits (see Section x). Second is detecting and handling the speed
  749. and reliability of the variety of servers we must use if we want to
  750. accept many servers (see Section y).
  751. Since the speed and reliability of a circuit is limited by its worst link,
  752. we must learn to track and predict performance. Finally, in order to get
  753. a large set of servers in the first place, we must address incentives
  754. for users to carry traffic for others (see Section incentives).
  755. \subsection{Incentives by Design}
  756. [nick will try to make this section shorter and more to the point.]
  757. [most of the technical incentive schemes in the literature introduce
  758. anonymity issues which we don't understand yet, and we seem to be doing
  759. ok without them]
  760. There are three behaviors we need to encourage for each server: relaying
  761. traffic; providing good throughput and reliability while doing it;
  762. and allowing traffic to exit the network from that server.
  763. We encourage these behaviors through \emph{indirect} incentives, that
  764. is, designing the system and educating users in such a way that users
  765. with certain goals will choose to relay traffic. In practice, the
  766. main incentive for running a Tor server is social benefit: volunteers
  767. altruistically donate their bandwidth and time. We also keep public
  768. rankings of the throughput and reliability of servers, much like
  769. seti@home. We further explain to users that they can get \emph{better
  770. security} by operating a server, because they get plausible deniability
  771. (indeed, they may not need to route their own traffic through Tor at all
  772. -- blending directly with other traffic exiting Tor may be sufficient
  773. protection for them), and because they can use their own Tor server
  774. as entry or exit point and be confident it's not run by the adversary.
  775. Finally, we can improve the usability and feature set of the software:
  776. rate limiting support and easy packaging decrease the hassle of
  777. maintaining a server, and our configurable exit policies allow each
  778. operator to advertise a policy describing the hosts and ports to which
  779. he feels comfortable connecting.
  780. Beyond these, however, there is also a need for \emph{direct} incentives:
  781. providing payment or other resources in return for high-quality service.
  782. Paying actual money is problematic: decentralized e-cash systems are
  783. not yet practical, and a centralized collection system not only reduces
  784. robustness, but also has failed in the past (the history of commercial
  785. anonymizing networks is littered with failed attempts). A more promising
  786. option is to use a tit-for-tat incentive scheme: provide better service
  787. to nodes that have provided good service to you.
  788. Unfortunately, such an approach introduces new anonymity problems.
  789. Does the incentive system enable the adversary to attract more traffic by
  790. performing well? Typically a user who chooses evenly from all options is
  791. most resistant to an adversary targetting him, but that approach prevents
  792. us from handling heterogeneous servers \cite{casc-rep}.
  793. When a server (call him Steve) performs well for Alice, does Steve gain
  794. reputation with the entire system, or just with Alice? If the entire
  795. system, how does Alice tell everybody about her experience in a way that
  796. prevents her from lying about it yet still protects her identity? If
  797. Steve's behavior only affects Alice's behavior, does this allow Steve to
  798. selectively perform only for Alice, and then break her anonymity later
  799. when somebody (presumably Alice) routes through his node?
  800. These are difficult and open questions, yet choosing not to scale means
  801. leaving most users to a less secure network or no anonymizing network
  802. at all. We will start with a simplified approach to the tit-for-tat
  803. incentive scheme based on two rules: (1) each node should measure the
  804. service it receives from adjacent nodes, and provide service relative to
  805. the received service, but (2) when a node is making decisions that affect
  806. its own security (e.g. when building a circuit for its own application
  807. connections), it should choose evenly from a sufficiently large set of
  808. nodes that meet some minimum service threshold. This approach allows us
  809. to discourage bad service without opening Alice up as much to attacks.
  810. %XXX rewrite the above so it sounds less like a grant proposal and
  811. %more like a "if somebody were to try to solve this, maybe this is a
  812. %good first step".
  813. %We should implement the above incentive scheme in the
  814. %deployed Tor network, in conjunction with our plans to add the necessary
  815. %associated scalability mechanisms. We will do experiments (simulated
  816. %and/or real) to determine how much the incentive system improves
  817. %efficiency over baseline, and also to determine how far we are from
  818. %optimal efficiency (what we could get if we ignored the anonymity goals).
  819. \subsection{Peer-to-peer / practical issues}
  820. [leave this section for now, and make sure things here are covered
  821. elsewhere. then remove it.]
  822. Making use of servers with little bandwidth. How to handle hammering by
  823. certain applications.
  824. Handling servers that are far away from the rest of the network, e.g. on
  825. the continents that aren't North America and Europe. High latency,
  826. often high packet loss.
  827. Running Tor servers behind NATs, behind great-firewalls-of-China, etc.
  828. Restricted routes. How to propagate to everybody the topology? BGP
  829. style doesn't work because we don't want just *one* path. Point to
  830. Geoff's stuff.
  831. \subsection{Location diversity and ISP-class adversaries}
  832. \label{subsec:routing-zones}
  833. Anonymity networks have long relied on diversity of node location for
  834. protection against attacks---typically an adversary who can observe a
  835. larger fraction of the network can launch a more effective attack. One
  836. way to achieve dispersal involves growing the network so a given adversary
  837. sees less. Alternately, we can arrange the topology so traffic can enter
  838. or exit at many places (for example, by using a free-route network
  839. like Tor rather than a cascade network like JAP). Lastly, we can use
  840. distributed trust to spread each transaction over multiple jurisdictions.
  841. But how do we decide whether two nodes are in related locations?
  842. Feamster and Dingledine defined a \emph{location diversity} metric
  843. in \cite{feamster:wpes2004}, and began investigating a variant of location
  844. diversity based on the fact that the Internet is divided into thousands of
  845. independently operated networks called {\em autonomous systems} (ASes).
  846. The key insight from their paper is that while we typically think of a
  847. connection as going directly from the Tor client to her first Tor node,
  848. actually it traverses many different ASes on each hop. An adversary at
  849. any of these ASes can monitor or influence traffic. Specifically, given
  850. plausible initiators and recipients and path random path selection,
  851. some ASes in the simulation were able to observe 10\% to 30\% of the
  852. transactions (that is, learn both the origin and the destination) on
  853. the deployed Tor network (33 nodes as of June 2004).
  854. The paper concludes that for best protection against the AS-level
  855. adversary, nodes should be in ASes that have the most links to other ASes:
  856. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  857. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  858. initiator and responder are both in the U.S., it actually \emph{hurts}
  859. our location diversity to add far-flung nodes in continents like Asia
  860. or South America.
  861. Many open questions remain. First, it will be an immense engineering
  862. challenge to get an entire BGP routing table to each Tor client, or at
  863. least summarize it sufficiently. Without a local copy, clients won't be
  864. able to safely predict what ASes will be traversed on the various paths
  865. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  866. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  867. determine location diversity; but the above paper showed that in practice
  868. many of the Mixmaster nodes that share a single AS have entirely different
  869. IP prefixes. When the network has scaled to thousands of nodes, does IP
  870. prefix comparison become a more useful approximation?
  871. %
  872. Second, can take advantage of caching certain content at the exit nodes, to
  873. limit the number of requests that need to leave the network at all.
  874. what about taking advantage of caches like akamai's or googles? what
  875. about treating them as adversaries?
  876. %
  877. Third, if we follow the paper's recommendations and tailor path selection
  878. to avoid choosing endpoints in similar locations, how much are we hurting
  879. anonymity against larger real-world adversaries who can take advantage
  880. of knowing our algorithm?
  881. %
  882. Lastly, can we use this knowledge to figure out which gaps in our network
  883. would most improve our robustness to this class of attack, and go recruit
  884. new servers with those ASes in mind?
  885. Tor's security relies in large part on the dispersal properties of its
  886. network. We need to be more aware of the anonymity properties of various
  887. approaches we can make better design decisions in the future.
  888. \subsection{The China problem}
  889. \label{subsec:china}
  890. Citizens in a variety of countries, such as most recently China and
  891. Iran, are periodically blocked from accessing various sites outside
  892. their country. These users try to find any tools available to allow
  893. them to get-around these firewalls. Some anonymity networks, such as
  894. Six-Four~\cite{six-four}, are designed specifically with this goal in
  895. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  896. such as Voice of America to set up a network to encourage `Internet
  897. freedom'~\cite{voice-of-america-anonymizer}. Even though Tor wasn't
  898. designed with ubiquitous access to the network in mind, thousands of
  899. users across the world are trying to use it for exactly this purpose.
  900. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  901. Anti-censorship networks hoping to bridge country-level blocks face
  902. a variety of challenges. One of these is that they need to find enough
  903. exit nodes---servers on the `free' side that are willing to relay
  904. arbitrary traffic from users to their final destinations. Anonymizing
  905. networks including Tor are well-suited to this task, since we have
  906. already gathered a set of exit nodes that are willing to tolerate some
  907. political heat.
  908. The other main challenge is to distribute a list of reachable relays
  909. to the users inside the country, and give them software to use them,
  910. without letting the authorities also enumerate this list and block each
  911. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  912. addresses (or having them donated), abandoning old addresses as they are
  913. `used up', and telling a few users about the new ones. Distributed
  914. anonymizing networks again have an advantage here, in that we already
  915. have tens of thousands of separate IP addresses whose users might
  916. volunteer to provide this service since they've already installed and use
  917. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  918. the Tor protocol separates routing from network discovery (see Section
  919. \ref{do-we-discuss-this?}), volunteers could configure their Tor clients
  920. to generate server descriptors and send them to a special directory
  921. server that gives them out to dissidents who need to get around blocks.
  922. Of course, this still doesn't prevent the adversary
  923. from enumerating all the volunteer relays and blocking them preemptively.
  924. Perhaps a tiered-trust system could be built where a few individuals are
  925. given relays' locations, and they recommend other individuals by telling them
  926. those addresses, thus providing a built-in incentive to avoid letting the
  927. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  928. might help to bound the number of IP addresses leaked to the adversary. Groups
  929. like the W3C are looking into using Tor as a component in an overall system to
  930. help address censorship; we wish them luck.
  931. %\cite{infranet}
  932. \subsection{Non-clique topologies}
  933. [nick will try to shrink this section]
  934. Because of its threat model that is substantially weaker than high
  935. latency mixnets, Tor is actually in a potentially better position to
  936. scale at least initially. From the perspective of a mix network, one
  937. of the worst things that can happen is partitioning. The more
  938. potential senders of messages entering the network the better the
  939. anonymity. Roughly, if a network is, e.g., split in half, then your
  940. anonymity is cut in half. Attacks become half as hard (if they're
  941. linear in network size), etc. In some sense this is still true for
  942. Tor: if you want to know who Alice is talking to, you can watch her
  943. for one end of a circuit. For a half size network, you then only have
  944. to brute force examine half as many nodes to find the other end. But
  945. Tor is not meant to cope with someone directly attacking many dozens
  946. of nodes in a few minutes. It was meant to cope with traffic
  947. confirmation attacks. And, these are independent of the size of the
  948. network. So, a simple possibility when the scale of a Tor network
  949. exceeds some size is to simply split it. Care could be taken in
  950. allocating which nodes go to which network along the lines of
  951. \cite{casc-rep} to insure that collaborating hostile nodes are not
  952. able to gain any advantage in network splitting that they do not
  953. already have in joining a network.
  954. The attacks in \cite{attack-tor-oak05} show that certain types of
  955. brute force attacks are in fact feasible; however they make the
  956. above point stronger not weaker. The attacks do not appear to be
  957. significantly more difficult to mount against a network that is
  958. twice the size. Also, they only identify the Tor nodes used in a
  959. circuit, not the client. Finally note that even if the network is split,
  960. a client does not need to use just one of the two resulting networks.
  961. Alice could use either of them, and it would not be difficult to make
  962. the Tor client able to access several such network on a per circuit
  963. basis. More analysis is needed; we simply note here that splitting
  964. a Tor network is an easy way to achieve moderate scalability and that
  965. it does not necessarily have the same implications as splitting a mixnet.
  966. Alternatively, we can try to scale a single network. Some issues for
  967. scaling include how many neighbors can nodes support and how many
  968. users (and how much application traffic capacity) can the network
  969. handle for each new node that comes into the network. This depends on
  970. many things, most notably the traffic capacity of the new nodes. We
  971. can observe, however, that adding a tor node of any feasible bandwidth
  972. will increase the traffic capacity of the network. This means that, as
  973. a first step to scaling, we can focus on the interconnectivity of the
  974. nodes, followed by directories, discovery, etc.
  975. By reducing the connectivity of the network we increase the total
  976. number of nodes that the network can contain. Anonymity implications
  977. of restricted routes for mix networks have already been explored by
  978. Danezis~\cite{danezis-pets03}. That paper explicitly considered only
  979. traffic analysis resistance provided by a mix network and sidestepped
  980. questions of traffic confirmation resistance. But, Tor is designed
  981. only to resist traffic confirmation. For this and other reasons, we
  982. cannot simply adopt his mixnet results to onion routing networks. If
  983. an attacker gains minimal increase in the likelyhood of compromising
  984. the endpoints of a Tor circuit through a sparse network (vs.\ a clique
  985. on the same node set), then the restriction will have had minimal
  986. impact on the anonymity provided by that network.
  987. The approach Danezis describes is based on expander graphs, i.e.,
  988. graphs in which any subgraph of nodes is likely to have lots of nodes
  989. as neighbors. For Tor, we may not need to have an expander per se, it
  990. may be enough to have a single subnet that is highly connected. As an
  991. example, assume fifty nodes of relatively high traffic capacity. This
  992. \emph{center} forms are a clique. Assume each center node can each
  993. handle 200 connections to other nodes (including the other ones in the
  994. center). Assume every noncenter node connects to three nodes in the
  995. center and anyone out of the center that they want to. Then the
  996. network easily scales to c. 2500 nodes with commensurate increase in
  997. bandwidth. There are many open questions: how directory information
  998. is distributed (presumably information about the center nodes could
  999. be given to any new nodes with their codebase), whether center nodes
  1000. will need to function as a `backbone', etc. As above the point is
  1001. that this would create problems for the expected anonymity for a mixnet,
  1002. but for an onion routing network where anonymity derives largely from
  1003. the edges, it may be feasible.
  1004. Another point is that we already have a non-clique topology.
  1005. Individuals can set up and run Tor nodes without informing the
  1006. directory servers. This will allow, e.g., dissident groups to run a
  1007. local Tor network of such nodes that connects to the public Tor
  1008. network. This network is hidden behind the Tor network and its
  1009. only visible connection to Tor at those points where it connects.
  1010. As far as the public network is concerned or anyone observing it,
  1011. they are running clients.
  1012. \section{The Future}
  1013. \label{sec:conclusion}
  1014. we should put random thoughts here until there are enough for a
  1015. conclusion.
  1016. will our sustainability approach work? we'll see.
  1017. "These are difficult and open questions, yet choosing not to solve them
  1018. means leaving most users to a less secure network or no anonymizing
  1019. network at all."
  1020. \bibliographystyle{plain} \bibliography{tor-design}
  1021. \clearpage
  1022. \appendix
  1023. \begin{figure}[t]
  1024. %\unitlength=1in
  1025. \centering
  1026. %\begin{picture}(6.0,2.0)
  1027. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1028. %\end{picture}
  1029. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1030. \caption{Number of servers over time. Lowest line is number of exit
  1031. nodes that allow connections to port 80. Middle line is total number of
  1032. verified (registered) servers. The line above that represents servers
  1033. that are not yet registered.}
  1034. \label{fig:graphnodes}
  1035. \end{figure}
  1036. \begin{figure}[t]
  1037. \centering
  1038. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1039. \caption{The sum of traffic reported by each server over time. The bottom
  1040. pair show average throughput, and the top pair represent the largest 15
  1041. minute burst in each 4 hour period.}
  1042. \label{fig:graphtraffic}
  1043. \end{figure}
  1044. \end{document}