challenges.tex 63 KB

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  1. \documentclass{llncs}
  2. \usepackage{url}
  3. \usepackage{amsmath}
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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 cconnections
  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. this is why services use IP blocking. In order to deter abuse, pseudonymous
  426. identities need to impose a significant switching cost in resources or human
  427. time.
  428. Once approach, similar to that taken by Freedom, would be to bootstrap some
  429. non-anonymous costly identification mechanism to allow access to a
  430. blind-signature pseudonym protocol. This would effectively create costly
  431. pseudonyms, which services could require in order to allow anonymous access.
  432. This approach has difficulties in practise, however:
  433. \begin{tightlist}
  434. \item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  435. be a shame to require payment in order to make Tor useful, or to make
  436. non-paying users second-class citizens.
  437. \item It is hard to think of an underlying resource that would actually work.
  438. We could use IP addresses, but that's the problem, isn't it?
  439. \item Managing single sign-on services is not considered a well-solved
  440. problem in practice. If Microsoft can't get universal acceptance for
  441. passport, why do we think that a Tor-specific solution would do any good?
  442. \item Even if we came up with a perfect authentication system for our needs,
  443. there's no guarantee that any service would actually start using it. It
  444. would require a nonzero effort for them to support it, and it might just
  445. be less hassle for them to block tor anyway.
  446. \end{tightlist}
  447. Squishy IP based ``authentication'' and ``authorization'' is a reality
  448. we must contend with. We should say something more about the analogy
  449. with SSNs.
  450. \subsection{Other}
  451. [Once you build a generic overlay network, everybody wants to use it.]
  452. Tor's scope: How much should Tor aim to do? Applications that leak
  453. data: we can say they're not our problem, but they're somebody's problem.
  454. Also, the more widely deployed Tor becomes, the more people who need a
  455. deployed overlay network tell us they'd like to use us if only we added
  456. the following more features. For example, Blossom \cite{blossom} and
  457. random community wireless projects both want source-routable overlay
  458. networks for their own purposes. Fortunately, our modular design separates
  459. routing from node discovery; so we could implement Morphmix in Tor just
  460. by implementing the Morphmix-specific node discovery and path selection
  461. pieces. On the other hand, we could easily get distracted building a
  462. general-purpose overlay library, and we're only a few developers.
  463. [arma will work on this]
  464. %Should we allow revocation of anonymity if a threshold of
  465. %servers want to?
  466. Logging. Making logs not revealing. A happy coincidence that verbose
  467. logging is our \#2 performance bottleneck. Is there a way to detect
  468. modified servers, or to have them volunteer the information that they're
  469. logging verbosely? Would that actually solve any attacks?
  470. \section{Crossroads: Scaling and Design choices}
  471. \label{sec:crossroads-design}
  472. \subsection{Transporting the stream vs transporting the packets}
  473. \ref{subsec:stream-vs-packet}
  474. We periodically run into ex ZKS employees who tell us that the process of
  475. anonymizing IPs should ``obviously'' be done at the IP layer. Here are
  476. the issues that need to be resolved before we'll be ready to switch Tor
  477. over to arbitrary IP traffic.
  478. \begin{enumerate}
  479. \setlength{\itemsep}{0mm}
  480. \setlength{\parsep}{0mm}
  481. \item \emph{IP packets reveal OS characteristics.} We still need to do
  482. IP-level packet normalization, to stop things like IP fingerprinting
  483. \cite{ip-fingerprinting}. There exist libraries \cite{ip-normalizing}
  484. 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}. Also, TLS over UDP is not implemented or even
  498. specified, though some early work has begun on that \cite{dtls}.
  499. \item \emph{We'll still need to tune network parameters}. Since the above
  500. encryption system will likely need sequence numbers and maybe more to do
  501. replay detection, handle duplicate frames, etc, we will be reimplementing
  502. some subset of TCP anyway to manage throughput, congestion control, etc.
  503. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  504. IDS.} Our server operators tell us that exit policies are one of
  505. the main reasons they're willing to run Tor over previous attempts
  506. at anonymizing networks. Adding an IDS to handle exit policies would
  507. increase the security complexity of Tor, and would likely not work anyway,
  508. as evidenced by the entire field of IDS and counter-IDS papers. Many
  509. potential abuse issues are resolved by the fact that Tor only transports
  510. valid TCP streams (as opposed to arbitrary IP including malformed packets
  511. and IP floods), so exit policies become even \emph{more} important as
  512. we become able to transport IP packets. We also need a way to compactly
  513. characterize the exit policies and let clients parse them to decide
  514. which nodes will allow which packets to exit.
  515. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  516. support hidden service {\tt{.onion}} addresses, and other special addresses
  517. like {\tt{.exit}} (see Section \ref{subsec:}), by intercepting the addresses
  518. when they are passed to the Tor client.
  519. \end{enumerate}
  520. This list is discouragingly long right now, but we recognize that it
  521. would be good to investigate each of these items in further depth and to
  522. understand which are actual roadblocks and which are easier to resolve
  523. than we think. We certainly wouldn't mind if Tor one day is able to
  524. transport a greater variety of protocols.
  525. \subsection{Mid-latency}
  526. \label{subsec:mid-latency}
  527. Though Tor has always been designed to be practical and usable first
  528. with as much anonymity as can be built in subject to those goals, we
  529. have contemplated that users might need resistance to at least simple
  530. traffic confirmation attacks. Raising the latency of communication
  531. slightly might make this feasible. If the latency could be kept to two
  532. or three times its current overhead, this might be acceptable to the
  533. majority of Tor users. However, it might also destroy much of the user
  534. base, and it is difficult to know in advance. Note also that in
  535. practice, as the network is growing and we accept cable modem, DSL
  536. nodes, and more nodes in various continents, we're \emph{already}
  537. looking at many-second delays for some transactions. The engineering
  538. required to get this lower is going to be extremely hard. It's worth
  539. considering how hard it would be to accept the fixed (higher) latency
  540. and improve the protection we get from it. Thus, it may be most
  541. practical to run a mid-latency option over the Tor network for those
  542. users either willing to experiment or in need of more a priori
  543. anonymity in the network. This will allow us to experiment with both
  544. the anonymity provided and the interest on the part of users.
  545. Adding a mid-latency option should not require significant fundamental
  546. change to the Tor client or server design; circuits can be labeled as
  547. low or mid latency on servers as they are set up. Low-latency traffic
  548. would be processed as now. Packets on circuits that are mid-latency
  549. would be sent in uniform size chunks at synchronized intervals. To
  550. some extent the chunking is already done because traffic moves through
  551. the network in uniform size cells, but this would occur at a courser
  552. granularity. If servers forward these chunks in roughly synchronous
  553. fashion, it will increase the similarity of data stream timing
  554. signatures. By experimenting with the granularity of data chunks and
  555. of synchronization we can attempt once again to optimize for both
  556. usability and anonymity. Unlike in \cite{sync-batching}, it may be
  557. impractical to synchronize on network batches by dropping chunks from
  558. a batch that arrive late at a given node---unless Tor moves away from
  559. stream processing to a more loss-tolerant processing of traffic (cf.\
  560. Section~\ref{subsec:stream-vs-packet}). In other words, there would
  561. probably be no direct attempt to synchronize on batches of data
  562. entering the Tor network at the same time. Rather, it is the link
  563. level batching that will add noise to the traffic patterns exiting the
  564. network. Similarly, if end-to-end traffic confirmation is the
  565. concern, there is little point in mixing. It might also be feasible to
  566. pad chunks to uniform size as is done now for cells; if this is link
  567. padding rather than end-to-end, then it will take less overhead,
  568. especially in bursty environments. This is another way in which it
  569. would be fairly practical to set up a mid-latency option within the
  570. existing Tor network. Other padding regimens might supplement the
  571. mid-latency option; however, we should continue the caution with which
  572. we have always approached padding lest the overhead cost us either
  573. performance or volunteers.
  574. The distinction between traffic confirmation and traffic analysis is
  575. not as practically cut and dried as we might wish. In \cite{} it was
  576. shown that if latencies to and/or data volumes of various popular
  577. responder destinations are catalogued, it may not be necessary to
  578. observe both ends of a stream to confirm a source-destination link.
  579. These are likely to entail high variability and massive storage since
  580. routes through the network to each site will be random even if they
  581. have relatively unique latency or volume characteristics. So these do
  582. not seem an immediate practical threat. Further along similar lines, in
  583. \cite{attack-tor-oak05}, it was shown that an outside attacker can
  584. trace a stream through the Tor network while a stream is still active
  585. simply by observing the latency of his own traffic sent through
  586. various Tor nodes. These attacks are especially significant since they
  587. counter previous results that running one's own onion router protects
  588. better than using the network from the outside. The attacks do not
  589. show the client address, only the first server within the Tor network,
  590. making helper nodes all the more worthy of exploration for enclave
  591. protection. Setting up a mid-latency subnet as described above would
  592. be another significant step to evaluating resistance to such attacks.
  593. The attacks in \cite{attack-tor-oak05} are also dependent on
  594. cooperation of the responding application or the ability to modify or
  595. monitor the responder stream, in order of decreasing attack
  596. effectiveness. So, another way to counter these attacks in some cases
  597. would be to employ caching of responses. This is infeasible for
  598. application data that is not relatively static and from frequently
  599. visited sites; however, it might be useful for DNS lookups. This is
  600. also likely to be trading one practical threat for another. To be
  601. useful, such caches would need to be distributed to any likely exit
  602. nodes of recurred requests for the same data. Aside from the logistic
  603. difficulties and overhead of distribution, they constitute a collected
  604. record of destinations and/or data visited by Tor users. While
  605. limited to network insiders, given the need for wide distribution
  606. they could serve as useful data to an attacker deciding which locations
  607. to target for confirmation.
  608. [nick will work on this]
  609. \subsection{Application support: socks doesn't solve all our problems}
  610. socks4a isn't everywhere. the dns problem. etc.
  611. nick will work on this.
  612. \subsection{Measuring performance and capacity}
  613. How to measure performance without letting people selectively deny service
  614. by distinguishing pings. Heck, just how to measure performance at all. In
  615. practice people have funny firewalls that don't match up to their exit
  616. policies and Tor doesn't deal.
  617. Network investigation: Is all this bandwidth publishing thing a good idea?
  618. How can we collect stats better? Note weasel's smokeping, at
  619. http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  620. which probably gives george and steven enough info to break tor?
  621. [nick will work on this section, unless arma gets there first]
  622. \subsection{Anonymity benefits for running a server}
  623. Does running a server help you or harm you? George's Oakland attack.
  624. Plausible deniability -- without even running your traffic through Tor!
  625. But nobody knows about Tor, and the legal situation is fuzzy, so this
  626. isn't very true really.
  627. We have to pick the path length so adversary can't distinguish client from
  628. server (how many hops is good?).
  629. in practice, plausible deniability is hypothetical and doesn't seem very
  630. convincing. if ISPs find the activity antisocial, they don't care *why*
  631. your computer is doing that behavior.
  632. [arma will write this section]
  633. \subsection{Helper nodes}
  634. When does fixing your entry or exit node help you?
  635. Helper nodes in the literature don't deal with churn, and
  636. especially active attacks to induce churn.
  637. Do general DoS attacks have anonymity implications? See e.g. Adam
  638. Back's IH paper, but I think there's more to be pointed out here.
  639. Game theory for helper nodes: if Alice offers a hidden service on a
  640. server (enclave model), and nobody ever uses helper nodes, then against
  641. George+Steven's attack she's totally nailed. If only Alice uses a helper
  642. node, then she's still identified as the source of the data. If everybody
  643. uses a helper node (including Alice), then the attack identifies the
  644. helper node and also Alice, and knows which one is which. If everybody
  645. uses a helper node (but not Alice), then the attacker figures the real
  646. source was a client that is using Alice as a helper node. [How's my
  647. logic here?]
  648. point to routing-zones section re: helper nodes to defend against
  649. big stuff.
  650. [nick will write this section]
  651. \subsection{Location-hidden services}
  652. [arma will write this section]
  653. Survivable services are new in practice, yes? Hidden services seem
  654. less hidden than we'd like, since they stay in one place and get used
  655. a lot. They're the epitome of the need for helper nodes. This means
  656. that using Tor as a building block for Free Haven is going to be really
  657. hard. Also, they're brittle in terms of intersection and observation
  658. attacks. Would be nice to have hot-swap services, but hard to design.
  659. people are using hidden services as a poor man's vpn and firewall-buster.
  660. rather than playing with dyndns and trying to pierce holes in their
  661. firewall (say, so they can ssh in from the outside), they run a hidden
  662. service on the inside and then rendezvous with that hidden service
  663. externally.
  664. in practice, sites like bloggers without borders (www.b19s.org) are
  665. running tor servers but more important are advertising a hidden-service
  666. address on their front page. doing this can provide increased robustness
  667. if they used the dual-IP approach we describe in tor-design, but in
  668. practice they do it to a) increase visibility of the tor project and their
  669. support for privacy, and b) to offer a way for their users, using vanilla
  670. software, to get end-to-end encryption and end-to-end authentication to
  671. their website.
  672. \subsection{Trust and discovery}
  673. [arma will edit this and expand/retract it]
  674. The published Tor design adopted a deliberately simplistic design for
  675. authorizing new nodes and informing clients about servers and their status.
  676. In the early Tor designs, all ORs periodically uploaded a signed description
  677. of their locations, keys, and capabilities to each of several well-known {\it
  678. directory servers}. These directory servers constructed a signed summary
  679. of all known ORs (a ``directory''), and a signed statement of which ORs they
  680. believed to be operational at any given time (a ``network status''). Clients
  681. periodically downloaded a directory in order to learn the latest ORs and
  682. keys, and more frequently downloaded a network status to learn which ORs are
  683. likely to be running. ORs also operate as directory caches, in order to
  684. lighten the bandwidth on the authoritative directory servers.
  685. In order to prevent Sybil attacks (wherein an adversary signs up many
  686. purportedly independent servers in order to increase her chances of observing
  687. a stream as it enters and leaves the network), the early Tor directory design
  688. required the operators of the authoritative directory servers to manually
  689. approve new ORs. Unapproved ORs were included in the directory, but clients
  690. did not use them at the start or end of their circuits. In practice,
  691. directory administrators performed little actual verification, and tended to
  692. approve any OR whose operator could compose a coherent email. This procedure
  693. may have prevented trivial automated Sybil attacks, but would do little
  694. against a clever attacker.
  695. There are a number of flaws in this system that need to be addressed as we
  696. move forward. They include:
  697. \begin{tightlist}
  698. \item Each directory server represents an independent point of failure; if
  699. any one were compromised, it could immediately compromise all of its users
  700. by recommending only compromised ORs.
  701. \item The more servers appear join the network, the more unreasonable it
  702. becomes to expect clients to know about them all. Directories
  703. become unfeasibly large, and downloading the list of servers becomes
  704. burdonsome.
  705. \item The validation scheme may do as much harm as it does good. It is not
  706. only incapable of preventing clever attackers from mounting Sybil attacks,
  707. but may deter server operators from joining the network. (For instance, if
  708. they expect the validation process to be difficult, or if they do not share
  709. any languages in common with the directory server operators.)
  710. \end{tightlist}
  711. We could try to move the system in several directions, depending on our
  712. choice of threat model and requirements. If we did not need to increase
  713. network capacity in order to support more users, there would be no reason not
  714. to adopt even stricter validation requirements, and reduce the number of
  715. servers in the network to a trusted minimum. But since we want Tor to work
  716. for as many users as it can, we need XXXXX
  717. In order to address the first two issues, it seems wise to move to a system
  718. including a number of semi-trusted directory servers, no one of which can
  719. compromise a user on its own. Ultimately, of course, we cannot escape the
  720. problem of a first introducer: since most users will run Tor in whatever
  721. configuration the software ships with, the Tor distribution itself will
  722. remain a potential single point of failure so long as it includes the seed
  723. keys for directory servers, a list of directory servers, or any other means
  724. to learn which servers are on the network. But omitting this information
  725. from the Tor distribution would only delegate the trust problem to the
  726. individual users, most of whom are presumably less informed about how to make
  727. trust decisions than the Tor developers.
  728. %Network discovery, sybil, node admission, scaling. It seems that the code
  729. %will ship with something and that's our trust root. We could try to get
  730. %people to build a web of trust, but no. Where we go from here depends
  731. %on what threats we have in mind. Really decentralized if your threat is
  732. %RIAA; less so if threat is to application data or individuals or...
  733. \section{Crossroads: Scaling}
  734. %\label{sec:crossroads-scaling}
  735. %P2P + anonymity issues:
  736. Tor is running today with hundreds of servers and tens of thousands of
  737. users, but it will certainly not scale to millions.
  738. Scaling Tor involves three main challenges. First is safe server
  739. discovery, both bootstrapping -- how a Tor client can robustly find an
  740. initial server list -- and ongoing -- how a Tor client can learn about
  741. a fair sample of honest servers and not let the adversary control his
  742. circuits (see Section x). Second is detecting and handling the speed
  743. and reliability of the variety of servers we must use if we want to
  744. accept many servers (see Section y).
  745. Since the speed and reliability of a circuit is limited by its worst link,
  746. we must learn to track and predict performance. Finally, in order to get
  747. a large set of servers in the first place, we must address incentives
  748. for users to carry traffic for others (see Section incentives).
  749. \subsection{Incentives by Design}
  750. [nick will try to make this section shorter and more to the point.]
  751. [most of the technical incentive schemes in the literature introduce
  752. anonymity issues which we don't understand yet, and we seem to be doing
  753. ok without them]
  754. There are three behaviors we need to encourage for each server: relaying
  755. traffic; providing good throughput and reliability while doing it;
  756. and allowing traffic to exit the network from that server.
  757. We encourage these behaviors through \emph{indirect} incentives, that
  758. is, designing the system and educating users in such a way that users
  759. with certain goals will choose to relay traffic. In practice, the
  760. main incentive for running a Tor server is social benefit: volunteers
  761. altruistically donate their bandwidth and time. We also keep public
  762. rankings of the throughput and reliability of servers, much like
  763. seti@home. We further explain to users that they can get \emph{better
  764. security} by operating a server, because they get plausible deniability
  765. (indeed, they may not need to route their own traffic through Tor at all
  766. -- blending directly with other traffic exiting Tor may be sufficient
  767. protection for them), and because they can use their own Tor server
  768. as entry or exit point and be confident it's not run by the adversary.
  769. Finally, we can improve the usability and feature set of the software:
  770. rate limiting support and easy packaging decrease the hassle of
  771. maintaining a server, and our configurable exit policies allow each
  772. operator to advertise a policy describing the hosts and ports to which
  773. he feels comfortable connecting.
  774. Beyond these, however, there is also a need for \emph{direct} incentives:
  775. providing payment or other resources in return for high-quality service.
  776. Paying actual money is problematic: decentralized e-cash systems are
  777. not yet practical, and a centralized collection system not only reduces
  778. robustness, but also has failed in the past (the history of commercial
  779. anonymizing networks is littered with failed attempts). A more promising
  780. option is to use a tit-for-tat incentive scheme: provide better service
  781. to nodes that have provided good service to you.
  782. Unfortunately, such an approach introduces new anonymity problems.
  783. Does the incentive system enable the adversary to attract more traffic by
  784. performing well? Typically a user who chooses evenly from all options is
  785. most resistant to an adversary targetting him, but that approach prevents
  786. us from handling heterogeneous servers \cite{casc-rep}.
  787. When a server (call him Steve) performs well for Alice, does Steve gain
  788. reputation with the entire system, or just with Alice? If the entire
  789. system, how does Alice tell everybody about her experience in a way that
  790. prevents her from lying about it yet still protects her identity? If
  791. Steve's behavior only affects Alice's behavior, does this allow Steve to
  792. selectively perform only for Alice, and then break her anonymity later
  793. when somebody (presumably Alice) routes through his node?
  794. These are difficult and open questions, yet choosing not to scale means
  795. leaving most users to a less secure network or no anonymizing network
  796. at all. We will start with a simplified approach to the tit-for-tat
  797. incentive scheme based on two rules: (1) each node should measure the
  798. service it receives from adjacent nodes, and provide service relative to
  799. the received service, but (2) when a node is making decisions that affect
  800. its own security (e.g. when building a circuit for its own application
  801. connections), it should choose evenly from a sufficiently large set of
  802. nodes that meet some minimum service threshold. This approach allows us
  803. to discourage bad service without opening Alice up as much to attacks.
  804. %XXX rewrite the above so it sounds less like a grant proposal and
  805. %more like a "if somebody were to try to solve this, maybe this is a
  806. %good first step".
  807. %We should implement the above incentive scheme in the
  808. %deployed Tor network, in conjunction with our plans to add the necessary
  809. %associated scalability mechanisms. We will do experiments (simulated
  810. %and/or real) to determine how much the incentive system improves
  811. %efficiency over baseline, and also to determine how far we are from
  812. %optimal efficiency (what we could get if we ignored the anonymity goals).
  813. \subsection{Peer-to-peer / practical issues}
  814. [leave this section for now, and make sure things here are covered
  815. elsewhere. then remove it.]
  816. Making use of servers with little bandwidth. How to handle hammering by
  817. certain applications.
  818. Handling servers that are far away from the rest of the network, e.g. on
  819. the continents that aren't North America and Europe. High latency,
  820. often high packet loss.
  821. Running Tor servers behind NATs, behind great-firewalls-of-China, etc.
  822. Restricted routes. How to propagate to everybody the topology? BGP
  823. style doesn't work because we don't want just *one* path. Point to
  824. Geoff's stuff.
  825. \subsection{Location diversity and ISP-class adversaries}
  826. \label{subsec:routing-zones}
  827. Anonymity networks have long relied on diversity of node location for
  828. protection against attacks---typically an adversary who can observe a
  829. larger fraction of the network can launch a more effective attack. One
  830. way to achieve dispersal involves growing the network so a given adversary
  831. sees less. Alternately, we can arrange the topology so traffic can enter
  832. or exit at many places (for example, by using a free-route network
  833. like Tor rather than a cascade network like JAP). Lastly, we can use
  834. distributed trust to spread each transaction over multiple jurisdictions.
  835. But how do we decide whether two nodes are in related locations?
  836. Feamster and Dingledine defined a \emph{location diversity} metric
  837. in \cite{feamster:wpes2004}, and began investigating a variant of location
  838. diversity based on the fact that the Internet is divided into thousands of
  839. independently operated networks called {\em autonomous systems} (ASes).
  840. The key insight from this paper is that while we typically think of a
  841. connection as going directly from the Tor client to her first Tor node,
  842. actually it traverses many different ASes on each hop. An adversary at
  843. any of these ASes can monitor or influence traffic. Specifically, given
  844. plausible initiators and recipients and path random path selection,
  845. some ASes in the simulation were able to observe 10\% to 30\% of the
  846. transactions (that is, learn both the origin and the destination) on
  847. the deployed Tor network (33 nodes as of June 2004).
  848. The paper concludes that for best protection against the AS-level
  849. adversary, nodes should be in ASes that have the most links to other ASes:
  850. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  851. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  852. initiator and responder are both in the U.S., it actually \emph{hurts}
  853. our location diversity to add far-flung nodes in continents like Asia
  854. or South America.
  855. Many open questions remain. First, it will be an immense engineering
  856. challenge to get an entire BGP routing table to each Tor client, or at
  857. least summarize it sufficiently. Without a local copy, clients won't be
  858. able to safely predict what ASes will be traversed on the various paths
  859. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  860. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  861. determine location diversity; but the above paper showed that in practice
  862. many of the Mixmaster nodes that share a single AS have entirely different
  863. IP prefixes. When the network has scaled to thousands of nodes, does IP
  864. prefix comparison become a more useful approximation?
  865. %
  866. Second, can take advantage of caching certain content at the exit nodes, to
  867. limit the number of requests that need to leave the network at all.
  868. what about taking advantage of caches like akamai's or googles? what
  869. about treating them as adversaries?
  870. %
  871. Third, if we follow the paper's recommendations and tailor path selection
  872. to avoid choosing endpoints in similar locations, how much are we hurting
  873. anonymity against larger real-world adversaries who can take advantage
  874. of knowing our algorithm?
  875. %
  876. Lastly, can we use this knowledge to figure out which gaps in our network
  877. would most improve our robustness to this class of attack, and go recruit
  878. new servers with those ASes in mind?
  879. Tor's security relies in large part on the dispersal properties of its
  880. network. We need to be more aware of the anonymity properties of various
  881. approaches we can make better design decisions in the future.
  882. \subsection{The China problem}
  883. \label{subsec:china}
  884. Citizens in a variety of countries, such as most recently China and
  885. Iran, are periodically blocked from accessing various sites outside
  886. their country. These users try to find any tools available to allow
  887. them to get-around these firewalls. Some anonymity networks, such as
  888. Six-Four~\cite{six-four}, are designed specifically with this goal in
  889. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  890. such as Voice of America to set up a network to encourage `Internet
  891. freedom'~\cite{voice-of-america-anonymizer}. Even though Tor wasn't
  892. designed with ubiquitous access to the network in mind, thousands of
  893. users across the world are trying to use it for exactly this purpose.
  894. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  895. Anti-censorship networks hoping to bridge country-level blocks face
  896. a variety of challenges. One of these is that they need to find enough
  897. exit nodes---servers on the `free' side that are willing to relay
  898. arbitrary traffic from users to their final destinations. Anonymizing
  899. networks including Tor are well-suited to this task, since we have
  900. already gathered a set of exit nodes that are willing to tolerate some
  901. political heat.
  902. The other main challenge is to distribute a list of reachable relays
  903. to the users inside the country, and give them software to use them,
  904. without letting the authorities also enumerate this list and block each
  905. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  906. addresses (or having them donated), abandoning old addresses as they are
  907. `used up', and telling a few users about the new ones. Distributed
  908. anonymizing networks again have an advantage here, in that we already
  909. have tens of thousands of separate IP addresses whose users might
  910. volunteer to provide this service since they've already installed and use
  911. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  912. the Tor protocol separates routing from network discovery (see Section
  913. \ref{do-we-discuss-this?}), volunteers could configure their Tor clients
  914. to generate server descriptors and send them to a special directory
  915. server that gives them out to dissidents who need to get around blocks.
  916. Of course, this still doesn't prevent the adversary
  917. from enumerating all the volunteer relays and blocking them preemptively.
  918. Perhaps a tiered-trust system could be built where a few individuals are
  919. given relays' locations, and they recommend other individuals by telling them
  920. those addresses, thus providing a built-in incentive to avoid letting the
  921. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  922. might help to bound the number of IP addresses leaked to the adversary. Groups
  923. like the W3C are looking into using Tor as a component in an overall system to
  924. help address censorship; we wish them luck.
  925. %\cite{infranet}
  926. \subsection{Non-clique topologies}
  927. [nick will try to shrink this section]
  928. Because of its threat model that is substantially weaker than high
  929. latency mixnets, Tor is actually in a potentially better position to
  930. scale at least initially. From the perspective of a mix network, one
  931. of the worst things that can happen is partitioning. The more
  932. potential senders of messages entering the network the better the
  933. anonymity. Roughly, if a network is, e.g., split in half, then your
  934. anonymity is cut in half. Attacks become half as hard (if they're
  935. linear in network size), etc. In some sense this is still true for
  936. Tor: if you want to know who Alice is talking to, you can watch her
  937. for one end of a circuit. For a half size network, you then only have
  938. to brute force examine half as many nodes to find the other end. But
  939. Tor is not meant to cope with someone directly attacking many dozens
  940. of nodes in a few minutes. It was meant to cope with traffic
  941. confirmation attacks. And, these are independent of the size of the
  942. network. So, a simple possibility when the scale of a Tor network
  943. exceeds some size is to simply split it. Care could be taken in
  944. allocating which nodes go to which network along the lines of
  945. \cite{casc-rep} to insure that collaborating hostile nodes are not
  946. able to gain any advantage in network splitting that they do not
  947. already have in joining a network.
  948. The attacks in \cite{attack-tor-oak05} show that certain types of
  949. brute force attacks are in fact feasible; however they make the
  950. above point stronger not weaker. The attacks do not appear to be
  951. significantly more difficult to mount against a network that is
  952. twice the size. Also, they only identify the Tor nodes used in a
  953. circuit, not the client. Finally note that even if the network is split,
  954. a client does not need to use just one of the two resulting networks.
  955. Alice could use either of them, and it would not be difficult to make
  956. the Tor client able to access several such network on a per circuit
  957. basis. More analysis is needed; we simply note here that splitting
  958. a Tor network is an easy way to achieve moderate scalability and that
  959. it does not necessarily have the same implications as splitting a mixnet.
  960. Alternatively, we can try to scale a single network. Some issues for
  961. scaling include how many neighbors can nodes support and how many
  962. users (and how much application traffic capacity) can the network
  963. handle for each new node that comes into the network. This depends on
  964. many things, most notably the traffic capacity of the new nodes. We
  965. can observe, however, that adding a tor node of any feasible bandwidth
  966. will increase the traffic capacity of the network. This means that, as
  967. a first step to scaling, we can focus on the interconnectivity of the
  968. nodes, followed by directories, discovery, etc.
  969. By reducing the connectivity of the network we increase the total
  970. number of nodes that the network can contain. Anonymity implications
  971. of restricted routes for mix networks have already been explored by
  972. Danezis~\cite{danezis-pets03}. That paper explicitly considered only
  973. traffic analysis resistance provided by a mix network and sidestepped
  974. questions of traffic confirmation resistance. But, Tor is designed
  975. only to resist traffic confirmation. For this and other reasons, we
  976. cannot simply adopt his mixnet results to onion routing networks. If
  977. an attacker gains minimal increase in the likelyhood of compromising
  978. the endpoints of a Tor circuit through a sparse network (vs.\ a clique
  979. on the same node set), then the restriction will have had minimal
  980. impact on the anonymity provided by that network.
  981. The approach Danezis describes is based on expander graphs, i.e.,
  982. graphs in which any subgraph of nodes is likely to have lots of nodes
  983. as neighbors. For Tor, we may not need to have an expander per se, it
  984. may be enough to have a single subnet that is highly connected. As an
  985. example, assume fifty nodes of relatively high traffic capacity. This
  986. \emph{center} forms are a clique. Assume each center node can each
  987. handle 200 connections to other nodes (including the other ones in the
  988. center). Assume every noncenter node connects to three nodes in the
  989. center and anyone out of the center that they want to. Then the
  990. network easily scales to c. 2500 nodes with commensurate increase in
  991. bandwidth. There are many open questions: how directory information
  992. is distributed (presumably information about the center nodes could
  993. be given to any new nodes with their codebase), whether center nodes
  994. will need to function as a `backbone', etc. As above the point is
  995. that this would create problems for the expected anonymity for a mixnet,
  996. but for an onion routing network where anonymity derives largely from
  997. the edges, it may be feasible.
  998. Another point is that we already have a non-clique topology.
  999. Individuals can set up and run Tor nodes without informing the
  1000. directory servers. This will allow, e.g., dissident groups to run a
  1001. local Tor network of such nodes that connects to the public Tor
  1002. network. This network is hidden behind the Tor network and its
  1003. only visible connection to Tor at those points where it connects.
  1004. As far as the public network is concerned or anyone observing it,
  1005. they are running clients.
  1006. \section{The Future}
  1007. \label{sec:conclusion}
  1008. we should put random thoughts here until there are enough for a
  1009. conclusion.
  1010. will our sustainability approach work? we'll see.
  1011. "These are difficult and open questions, yet choosing not to solve them
  1012. means leaving most users to a less secure network or no anonymizing
  1013. network at all."
  1014. \bibliographystyle{plain} \bibliography{tor-design}
  1015. \appendix
  1016. \begin{figure}[t]
  1017. %\unitlength=1in
  1018. \centering
  1019. %\begin{picture}(6.0,2.0)
  1020. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1021. %\end{picture}
  1022. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1023. \caption{Number of servers over time. Lowest line is number of exit
  1024. nodes that allow connections to port 80. Middle line is total number of
  1025. verified (registered) servers. The line above that represents servers
  1026. that are not yet registered.}
  1027. \label{fig:graphnodes}
  1028. \end{figure}
  1029. \begin{figure}[t]
  1030. \centering
  1031. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1032. \caption{The sum of traffic reported by each server over time. The bottom
  1033. pair show average throughput, and the top pair represent the largest 15
  1034. minute burst in each 4 hour period.}
  1035. \label{fig:graphtraffic}
  1036. \end{figure}
  1037. \end{document}