challenges.tex 68 KB

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  1. \documentclass{llncs}
  2. \usepackage{url}
  3. \usepackage{amsmath}
  4. \usepackage{epsfig}
  5. \newenvironment{tightlist}{\begin{list}{$\bullet$}{
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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-design} 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}).
  214. And, it is not clear that padding works at all if we assume a
  215. minimally active adversary that merely modifies the timing of packets
  216. to or from the user. Thus, Tor only attempts to defend against
  217. external observers who cannot observe both sides of a user's
  218. connection.
  219. Against internal attackers, who sign up Tor servers, the situation is more
  220. complicated. In the simplest case, if an adversary has compromised $c$ of
  221. $n$ servers on the Tor network, then the adversary will be able to compromise
  222. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  223. initiator chooses hops randomly). But there are
  224. complicating factors:
  225. \begin{tightlist}
  226. \item If the user continues to build random circuits over time, an adversary
  227. is pretty certain to see a statistical sample of the user's traffic, and
  228. thereby can build an increasingly accurate profile of her behavior. (See
  229. \ref{subsec:helper-nodes} for possible solutions.)
  230. \item If an adversary controls a popular service outside of the Tor network,
  231. he can be certain of observing all connections to that service; he
  232. therefore will trace connections to that service with probability
  233. $\frac{c}{n}$.
  234. \item Users do not in fact choose servers with uniform probability; they
  235. favor servers with high bandwidth, and exit servers that permit connections
  236. to their favorite services.
  237. \end{tightlist}
  238. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  239. %the last hop is not $c/n$ since that doesn't take the destination (website)
  240. %into account. so in cases where the adversary does not also control the
  241. %final destination we're in good shape, but if he *does* then we'd be better
  242. %off with a system that lets each hop choose a path.
  243. %
  244. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  245. % dest, we would be just as well off with such as system.'' ? If not, why
  246. % not? -nm
  247. % Sure. In fact, better off, since they seem to scale more easily. -rd
  248. In practice Tor's threat model is based entirely on the goal of
  249. dispersal and diversity. Murdoch and Danezis describe an attack
  250. \cite{attack-tor-oak05} that lets an attacker determine the nodes used
  251. in a circuit; yet s/he cannot identify the initiator or responder,
  252. e.g., client or web server, through this attack. So the endpoints
  253. remain secure, which is the goal. On the other hand we can imagine an
  254. adversary that could attack or set up observation of all connections
  255. to an arbitrary Tor node in only a few minutes. If such an adversary
  256. were to exist, s/he could use this probing to remotely identify a node
  257. for further attack. Also, the enclave model seems particularly
  258. threatened by this attack, since it identifies endpoints when they're
  259. also nodes in the Tor network: see Section~\ref{subsec:helper-nodes}
  260. for discussion of some ways to address this issue.
  261. [*****Suppose an adversary with active access to the responder traffic
  262. wants to keep a circuit alive long enough to attack an identified
  263. node. Could s/he do this without the overt cooperation of the client
  264. proxy? More immediately, someone could identify nodes in this way and
  265. if in their jurisdiction, immediately get a subpoena (if they even
  266. need one) and tell the node operator(s) that she must retain all the
  267. active circuit data she now has at that moment. That \emph{can} be
  268. done in real time.********** We should say something about this
  269. here or later in the paper -pfs]
  270. see \ref{subsec:routing-zones} for discussion of larger
  271. adversaries and our dispersal goals.
  272. [this section will get written once the rest of the paper is farther along]
  273. \section{Crossroads: Policy issues}
  274. \label{sec:crossroads-policy}
  275. Many of the issues the Tor project needs to address are not just a
  276. matter of system design or technology development. In particular, the
  277. Tor project's \emph{image} with respect to its users and the rest of
  278. the Internet impacts the security it can provide.
  279. As an example to motivate this section, some U.S.~Department of Enery
  280. penetration testing engineers are tasked with compromising DoE computers
  281. from the outside. They only have a limited number of ISPs from which to
  282. launch their attacks, and they found that the defenders were recognizing
  283. attacks because they came from the same IP space. These engineers wanted
  284. to use Tor to hide their tracks. First, from a technical standpoint,
  285. Tor does not support the variety of IP packets one would like to use in
  286. such attacks (see Section~\ref{subsec:tcp-vs-ip}). But aside from this,
  287. we also decided that it would probably be poor precedent to encourage
  288. such use---even legal use that improves national security---and managed
  289. to dissuade them.
  290. With this image issue in mind, this section discusses the Tor user base and
  291. Tor's interaction with other services on the Internet.
  292. \subsection{Image and security}
  293. A growing field of papers argue that usability for anonymity systems
  294. contributes directly to their security, because how usable the system
  295. is impacts the possible anonymity set~\cite{back01,econymics}. Or
  296. conversely, an unusable system attracts few users and thus can't provide
  297. much anonymity.
  298. This phenomenon has a second-order effect: knowing this, users should
  299. choose which anonymity system to use based in part on how usable
  300. \emph{others} will find it, in order to get the protection of a larger
  301. anonymity set. Thus we might replace the adage ``usability is a security
  302. parameter''~\cite{back01} with a new one: ``perceived usability is a
  303. security parameter.'' From here we can better understand the effects
  304. of publicity and advertising on security: the more convincing your
  305. advertising, the more likely people will believe you have users, and thus
  306. the more users you will attract. Perversely, over-hyped systems (if they
  307. are not too broken) may be a better choice than modestly promoted ones,
  308. if the hype attracts more users~\cite{usability-network-effect}.
  309. So it follows that we should come up with ways to accurately communicate
  310. the available security levels to the user, so she can make informed
  311. decisions. Dresden's JAP project aims to do this, by including a
  312. comforting `anonymity meter' dial in the software's graphical interface,
  313. giving the user an impression of the level of protection for her current
  314. traffic.
  315. However, there's a catch. For users to share the same anonymity set,
  316. they need to act like each other. An attacker who can distinguish
  317. a given user's traffic from the rest of the traffic will not be
  318. distracted by other users on the network. For high-latency systems like
  319. Mixminion, where the threat model is based on mixing messages with each
  320. other, there's an arms race between end-to-end statistical attacks and
  321. counter-strategies~\cite{statistical-disclosure,minion-design,e2e-traffic,trickle02}.
  322. But for low-latency systems like Tor, end-to-end \emph{traffic
  323. confirmation} attacks~\cite{danezis-pet2004,SS03,defensive-dropping}
  324. allow an attacker who watches or controls both ends of a communication
  325. to use statistics to correlate packet timing and volume, quickly linking
  326. the initiator to her destination. This is why Tor's threat model is
  327. based on preventing the adversary from observing both the initiator and
  328. the responder.
  329. Like Tor, the current JAP implementation does not pad connections
  330. (apart from using small fixed-size cells for transport). In fact,
  331. its cascade-based network toplogy may be even more vulnerable to these
  332. attacks, because the network has fewer endpoints. JAP was born out of
  333. the ISDN mix design~\cite{isdn-mixes}, where padding made sense because
  334. every user had a fixed bandwidth allocation, but in its current context
  335. as a general Internet web anonymizer, adding sufficient padding to JAP
  336. would be prohibitively expensive.\footnote{Even if they could find and
  337. maintain extra funding to run higher-capacity nodes, our experience with
  338. users suggests that many users would not accept the increased per-user
  339. bandwidth requirements, leading to an overall much smaller user base. But
  340. see Section \ref{subsec:mid-latency}.} Therefore, since under this threat
  341. model the number of concurrent users does not seem to have much impact
  342. on the anonymity provided, we suggest that JAP's anonymity meter is not
  343. correctly communicating security levels to its users.
  344. On the other hand, while the number of active concurrent users may not
  345. matter as much as we'd like, it still helps to have some other users
  346. who use the network. We investigate this issue in the next section.
  347. \subsection{Reputability}
  348. Another factor impacting the network's security is its reputability:
  349. the perception of its social value based on its current user base. If I'm
  350. the only user who has ever downloaded the software, it might be socially
  351. accepted, but I'm not getting much anonymity. Add a thousand animal rights
  352. activists, and I'm anonymous, but everyone thinks I'm a bambi lover (or
  353. NRA member if you prefer a contrasting example). Add a thousand
  354. random citizens (cancer survivors, privacy enthusiasts, and so on)
  355. and now I'm harder to profile.
  356. The more cancer survivors on Tor, the better for the human rights
  357. activists. The more script kiddies, the worse for the normal users. Thus,
  358. reputability is an anonymity issue for two reasons. First, it impacts
  359. the sustainability of the network: a network that's always about to be
  360. shut down has difficulty attracting and keeping users, so its anonymity
  361. set suffers. Second, a disreputable network attracts the attention of
  362. powerful attackers who may not mind revealing the identities of all the
  363. users to uncover a few bad ones.
  364. While people therefore have an incentive for the network to be used for
  365. ``more reputable'' activities than their own, there are still tradeoffs
  366. involved when it comes to anonymity. To follow the above example, a
  367. network used entirely by cancer survivors might welcome some animal rights
  368. activists onto the network, though of course they'd prefer a wider
  369. variety of users.
  370. Reputability becomes even more tricky in the case of privacy networks,
  371. since the good uses of the network (such as publishing by journalists in
  372. dangerous countries) are typically kept private, whereas network abuses
  373. or other problems tend to be more widely publicized.
  374. The impact of public perception on security is especially important
  375. during the bootstrapping phase of the network, where the first few
  376. widely publicized uses of the network can dictate the types of users it
  377. attracts next.
  378. \subsection{Usability and bandwidth and sustainability and incentives}
  379. low-pain-threshold users go away until all users are willing to use it
  380. Sustainability. Previous attempts have been commercial which we think
  381. adds a lot of unnecessary complexity and accountability. Freedom didn't
  382. collect enough money to pay its servers; JAP bandwidth is supported by
  383. continued money, and they periodically ask what they will do when it
  384. dries up.
  385. "outside of academia, jap has just lost, permanently"
  386. [nick will write this section]
  387. \subsection{Tor and file-sharing}
  388. [nick will write this section]
  389. Bittorrent and dmca. Should we add an IDS to autodetect protocols and
  390. snipe them?
  391. because only at the exit is it evident what port or protocol a given
  392. tor stream is, you can't choose not to carry file-sharing traffic.
  393. hibernation vs rate-limiting: do we want diversity or throughput? i
  394. think we're shifting back to wanting diversity.
  395. \subsection{Tor and blacklists}
  396. Takedowns and efnet abuse and wikipedia complaints and irc
  397. networks.
  398. It was long expected that, alongside Tor's legitimate users, it would also
  399. attract troublemakers who exploited Tor in order to abuse services on the
  400. Internet. Our initial answer to this situation was to use ``exit policies''
  401. to allow individual Tor servers to block access to specific IP/port ranges.
  402. This approach was meant to make operators more willing to run Tor by allowing
  403. them to prevent their servers from being used for abusing particular
  404. services. For example, all Tor servers currently block SMTP (port 25), in
  405. order to avoid being used to send spam.
  406. This approach is useful, but is insufficient for two reasons. First, since
  407. it is not possible to force all ORs to block access to any given service,
  408. many of those services try to block Tor instead. More broadly, while being
  409. blockable is important to being good netizens, we would like to encourage
  410. services to allow anonymous access; services should not need to decide
  411. between blocking legitimate anonymous use and allowing unlimited abuse.
  412. This is potentially a bigger problem than it may appear.
  413. On the one hand, if people want to refuse connections from you on
  414. their servers it would seem that they should be allowed to. But, a
  415. possible major problem with the blocking of Tor is that it's not just
  416. the decision of the individual server administrator whose deciding if
  417. he wants to post to Wikipedia from his Tor node address or allow
  418. people to read Wikipedia anonymously through his Tor node. (Wikipedia
  419. has blocked all posting from all Tor nodes based in IP address.) If e.g.,
  420. s/he comes through a campus or corporate NAT, then the decision must
  421. be to have the entire population behind it able to have a Tor exit
  422. node or to have write access to Wikipedia. This is a loss for both of us (Tor
  423. and Wikipedia). We don't want to compete for (or divvy up) the NAT
  424. protected entities of the world.
  425. (A related problem is that many IP blacklists are not terribly fine-grained.
  426. No current IP blacklist, for example, allow a service provider to blacklist
  427. only those Tor servers that allow access to a specific IP or port, even
  428. though this information is readily available. One IP blacklist even bans
  429. every class C network that contains a Tor server, and recommends banning SMTP
  430. from these networks even though Tor does not allow SMTP at all.)
  431. [****Since this is stupid and we oppose it, shouldn't we name names here -pfs]
  432. Problems of abuse occur mainly with services such as IRC networks and
  433. Wikipedia, which rely on IP blocking to ban abusive users. While at first
  434. blush this practice might seem to depend on the anachronistic assumption that
  435. each IP is an identifier for a single user, it is actually more reasonable in
  436. practice: it assumes that non-proxy IPs are a costly resource, and that an
  437. abuser can not change IPs at will. By blocking IPs which are used by Tor
  438. servers, open proxies, and service abusers, these systems hope to make
  439. ongoing abuse difficult. Although the system is imperfect, it works
  440. tolerably well for them in practice.
  441. But of course, we would prefer that legitimate anonymous users be able to
  442. access abuse-prone services. One conceivable approach would be to require
  443. would-be IRC users, for instance, to register accounts if they wanted to
  444. access the IRC network from Tor. But in practise, this would not
  445. significantly impede abuse if creating new accounts were easily automatable;
  446. % XXX captcha
  447. this is why services use IP blocking. In order to deter abuse, pseudonymous
  448. identities need to impose a significant switching cost in resources or human
  449. time.
  450. One approach, similar to that taken by Freedom, would be to bootstrap some
  451. non-anonymous costly identification mechanism to allow access to a
  452. blind-signature pseudonym protocol. This would effectively create costly
  453. pseudonyms, which services could require in order to allow anonymous access.
  454. This approach has difficulties in practise, however:
  455. \begin{tightlist}
  456. \item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  457. be a shame to require payment in order to make Tor useful, or to make
  458. non-paying users second-class citizens.
  459. \item It is hard to think of an underlying resource that would actually work.
  460. We could use IP addresses, but that's the problem, isn't it?
  461. \item Managing single sign-on services is not considered a well-solved
  462. problem in practice. If Microsoft can't get universal acceptance for
  463. Passport, why do we think that a Tor-specific solution would do any good?
  464. \item Even if we came up with a perfect authentication system for our needs,
  465. there's no guarantee that any service would actually start using it. It
  466. would require a nonzero effort for them to support it, and it might just
  467. be less hassle for them to block tor anyway.
  468. \end{tightlist}
  469. The use of squishy IP-based ``authentication'' and ``authorization''
  470. has not broken down even to the level that SSNs used for these
  471. purposes have in commercial and public record contexts. Externalities
  472. and misplaced incentives cause a continued focus on fighting identity
  473. theft by protecting SSNs rather than developing better authentication
  474. and incentive schemes \cite{price-privacy}. Similarly we can expect a
  475. continued use of identification by IP number as long as there is no
  476. workable alternative.
  477. \subsection{Other}
  478. [Once you build a generic overlay network, everybody wants to use it.]
  479. Tor's scope: How much should Tor aim to do? Applications that leak
  480. data: we can say they're not our problem, but they're somebody's problem.
  481. Also, the more widely deployed Tor becomes, the more people who need a
  482. deployed overlay network tell us they'd like to use us if only we added
  483. the following more features. For example, Blossom \cite{blossom} and
  484. random community wireless projects both want source-routable overlay
  485. networks for their own purposes. Fortunately, our modular design separates
  486. routing from node discovery; so we could implement Morphmix in Tor just
  487. by implementing the Morphmix-specific node discovery and path selection
  488. pieces. On the other hand, we could easily get distracted building a
  489. general-purpose overlay library, and we're only a few developers.
  490. [arma will work on this]
  491. %Should we allow revocation of anonymity if a threshold of
  492. %servers want to?
  493. Logging. Making logs not revealing. A happy coincidence that verbose
  494. logging is our \#2 performance bottleneck. Is there a way to detect
  495. modified servers, or to have them volunteer the information that they're
  496. logging verbosely? Would that actually solve any attacks?
  497. \section{Crossroads: Scaling and Design choices}
  498. \label{sec:crossroads-design}
  499. \subsection{Transporting the stream vs transporting the packets}
  500. \label{subsec:stream-vs-packet}
  501. \label{subsec:tcp-vs-ip}
  502. We periodically run into ex ZKS employees who tell us that the process of
  503. anonymizing IPs should ``obviously'' be done at the IP layer. Here are
  504. the issues that need to be resolved before we'll be ready to switch Tor
  505. over to arbitrary IP traffic.
  506. \begin{enumerate}
  507. \setlength{\itemsep}{0mm}
  508. \setlength{\parsep}{0mm}
  509. \item \emph{IP packets reveal OS characteristics.} We still need to do
  510. IP-level packet normalization, to stop things like IP fingerprinting
  511. attacks. There likely exist libraries that can help with this.
  512. \item \emph{Application-level streams still need scrubbing.} We still need
  513. Tor to be easy to integrate with user-level application-specific proxies
  514. such as Privoxy. So it's not just a matter of capturing packets and
  515. anonymizing them at the IP layer.
  516. \item \emph{Certain protocols will still leak information.} For example,
  517. DNS requests destined for my local DNS servers need to be rewritten
  518. to be delivered to some other unlinkable DNS server. This requires
  519. understanding the protocols we are transporting.
  520. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  521. approach that can provide security despite
  522. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  523. never publicly specified. %, and we believe it's likely vulnerable to tagging
  524. %attacks \cite{tor-design}.
  525. Also, TLS over UDP is not implemented or even
  526. specified, though some early work has begun on that~\cite{dtls}.
  527. \item \emph{We'll still need to tune network parameters}. Since the above
  528. encryption system will likely need sequence numbers (and maybe more) to do
  529. replay detection, handle duplicate frames, etc, we will be reimplementing
  530. some subset of TCP anyway.
  531. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  532. IDS.} Our server operators tell us that exit policies are one of
  533. the main reasons they're willing to run Tor.
  534. Adding an Intrusion Detection System to handle exit policies would
  535. increase the security complexity of Tor, and would likely not work anyway,
  536. as evidenced by the entire field of IDS and counter-IDS papers. Many
  537. potential abuse issues are resolved by the fact that Tor only transports
  538. valid TCP streams (as opposed to arbitrary IP including malformed packets
  539. and IP floods), so exit policies become even \emph{more} important as
  540. we become able to transport IP packets. We also need a way to compactly
  541. characterize the exit policies and let clients parse them to decide
  542. which nodes will allow which packets to exit.
  543. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  544. support hidden service {\tt{.onion}} addresses, and other special addresses
  545. like {\tt{.exit}} (see Section~\ref{subsec:}), by intercepting the addresses
  546. when they are passed to the Tor client.
  547. \end{enumerate}
  548. This list is discouragingly long right now, but we recognize that it
  549. would be good to investigate each of these items in further depth and to
  550. understand which are actual roadblocks and which are easier to resolve
  551. than we think. We certainly wouldn't mind if Tor one day is able to
  552. transport a greater variety of protocols.
  553. \subsection{Mid-latency}
  554. \label{subsec:mid-latency}
  555. Though Tor has always been designed to be practical and usable first
  556. with as much anonymity as can be built in subject to those goals, we
  557. have contemplated that users might need resistance to at least simple
  558. traffic confirmation attacks. Raising the latency of communication
  559. slightly might make this feasible. If the latency could be kept to two
  560. or three times its current overhead, this might be acceptable to the
  561. majority of Tor users. However, it might also destroy much of the user
  562. base, and it is difficult to know in advance. Note also that in
  563. practice, as the network is growing and we accept cable modem, DSL
  564. nodes, and more nodes in various continents, we're \emph{already}
  565. looking at many-second delays for some transactions. The engineering
  566. required to get this lower is going to be extremely hard. It's worth
  567. considering how hard it would be to accept the fixed (higher) latency
  568. and improve the protection we get from it. Thus, it may be most
  569. practical to run a mid-latency option over the Tor network for those
  570. users either willing to experiment or in need of more a priori
  571. anonymity in the network. This will allow us to experiment with both
  572. the anonymity provided and the interest on the part of users.
  573. Adding a mid-latency option should not require significant fundamental
  574. change to the Tor client or server design; circuits can be labeled as
  575. low or mid latency on servers as they are set up. Low-latency traffic
  576. would be processed as now. Packets on circuits that are mid-latency
  577. would be sent in uniform size chunks at synchronized intervals. To
  578. some extent the chunking is already done because traffic moves through
  579. the network in uniform size cells, but this would occur at a coarser
  580. granularity. If servers forward these chunks in roughly synchronous
  581. fashion, it will increase the similarity of data stream timing
  582. signatures. By experimenting with the granularity of data chunks and
  583. of synchronization we can attempt once again to optimize for both
  584. usability and anonymity. Unlike in \cite{sync-batching}, it may be
  585. impractical to synchronize on network batches by dropping chunks from
  586. a batch that arrive late at a given node---unless Tor moves away from
  587. stream processing to a more loss-tolerant processing of traffic (cf.\
  588. Section~\ref{subsec:tcp-vs-ip}). In other words, there would
  589. probably be no direct attempt to synchronize on batches of data
  590. entering the Tor network at the same time. Rather, it is the link
  591. level batching that will add noise to the traffic patterns entering
  592. and passing through the
  593. network. Similarly, if end-to-end traffic confirmation is the
  594. concern, there is little point in mixing. It might also be feasible to
  595. pad chunks to uniform size as is done now for cells; if this is link
  596. padding rather than end-to-end, then it will take less overhead,
  597. especially in bursty environments. This is another way in which it
  598. would be fairly practical to set up a mid-latency option within the
  599. existing Tor network. Other padding regimens might supplement the
  600. mid-latency option; however, we should continue the caution with which
  601. we have always approached padding lest the overhead cost us too much
  602. performance or too many volunteers.
  603. The distinction between traffic confirmation and traffic analysis is
  604. not as practically cut and dried as we might wish. In \cite{hintz-pet02} it was
  605. shown that if data volumes of various popular
  606. responder destinations are catalogued, it may not be necessary to
  607. observe both ends of a stream to confirm a source-destination link.
  608. This should be fairly effective without simultaneously observing both
  609. ends of the connection. However, it is still essentially confirming
  610. suspected communicants where the responder suspects are ``stored'' rather
  611. than observed at the same time as the client.
  612. Similarly latencies of going through various routes can be
  613. catalogued~\cite{back01} to connect endpoints.
  614. This is likely to entail high variability and massive storage since
  615. % XXX hintz-pet02 just looked at data volumes of the sites. this
  616. % doesn't require much variability or storage. I think it works
  617. % quite well actually. Also, \cite{kesdogan:pet2002} takes the
  618. % attack another level further, to narrow down where you could be
  619. % based on an intersection attack on subpages in a website. -RD
  620. %
  621. % I was trying to be terse and simultaneously referring to both the
  622. % Hintz stuff and the Back et al. stuff from Info Hiding 01. I've
  623. % separated the two and added the references. -PFS
  624. routes through the network to each site will be random even if they
  625. have relatively unique latency characteristics. So the do
  626. not seem an immediate practical threat. Further along similar lines,
  627. the same paper suggested a ``clogging attack''. A version of this
  628. was demonstrated to be practical in
  629. \cite{attack-tor-oak05}. There it was shown that an outside attacker can
  630. trace a stream through the Tor network while a stream is still active
  631. simply by observing the latency of his own traffic sent through
  632. various Tor nodes. These attacks are especially significant since they
  633. counter previous results that running one's own onion router protects
  634. better than using the network from the outside. The attacks do not
  635. show the client address, only the first server within the Tor network,
  636. making helper nodes all the more worthy of exploration for enclave
  637. protection. Setting up a mid-latency subnet as described above would
  638. be another significant step to evaluating resistance to such attacks.
  639. The attacks in \cite{attack-tor-oak05} are also dependent on
  640. cooperation of the responding application or the ability to modify or
  641. monitor the responder stream, in order of decreasing attack
  642. effectiveness. So, another way to counter these attacks in some cases
  643. would be to employ caching of responses. This is infeasible for
  644. application data that is not relatively static and from frequently
  645. visited sites; however, it might be useful for DNS lookups. This is
  646. also likely to be trading one practical threat for another. To be
  647. useful, such caches would need to be distributed to any likely exit
  648. nodes of recurred requests for the same data. Aside from the logistic
  649. difficulties and overhead of distribution, they constitute a collected
  650. record of destinations and/or data visited by Tor users. While
  651. limited to network insiders, given the need for wide distribution
  652. they could serve as useful data to an attacker deciding which locations
  653. to target for confirmation. A way to counter this distribution
  654. threat might be to only cache at certain semitrusted helper nodes.
  655. [nick will work on this]
  656. \subsection{Application support: socks doesn't solve all our problems}
  657. socks4a isn't everywhere. the dns problem. etc.
  658. nick will work on this.
  659. \subsection{Measuring performance and capacity}
  660. How to measure performance without letting people selectively deny service
  661. by distinguishing pings. Heck, just how to measure performance at all. In
  662. practice people have funny firewalls that don't match up to their exit
  663. policies and Tor doesn't deal.
  664. Network investigation: Is all this bandwidth publishing thing a good idea?
  665. How can we collect stats better? Note weasel's smokeping, at
  666. http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  667. which probably gives george and steven enough info to break tor?
  668. [nick will work on this section, unless arma gets there first]
  669. \subsection{Running a Tor server, path length, and helper nodes}
  670. It has been thought for some time that the best anonymity protection
  671. comes from running your own onion router~\cite{or-pet00,tor-design}.
  672. (In fact, in Onion Routing's first design, this was the only option
  673. possible~\cite{or-ih96}.) The first design also had a fixed path
  674. length of five nodes. Middle Onion Routing involved much analysis
  675. (mostly unpublished) of route selection algorithms and path length
  676. algorithms to combine efficiency with unpredictability in routes.
  677. Since, unlike Crowds, nodes in a route cannot all know the ultimate
  678. destination of an application connection, it was generally not
  679. considered significant if a node could determine via latency that it
  680. was second in the route. But if one followed Tor's three node default
  681. path length, an enclave-to-enclave communication (in which two of the
  682. ORs were at each enclave) would be completely compromised by the
  683. middle node. Thus for enclave-to-enclave communication, four is the fewest
  684. number of nodes that preserves the $\frac{c^2}{n^2}$ degree of protection
  685. in any setting.
  686. The Murdoch-Danezis attack, however, shows that simply adding to the
  687. path length may not protect usage of an enclave protecting OR\@. A
  688. hostile web server can determine all of the nodes in a three node Tor
  689. path. The attack only identifies that a node is on the route, not
  690. where. For example, if all of the nodes on the route were enclave
  691. nodes, the attack would not identify which of the two not directly
  692. visible to the attacker was the source. Thus, there remains an
  693. element of plausible deniability that is preserved for enclave nodes.
  694. However, Tor has always sought to be stronger than plausible
  695. deniability. Our assumption is that users of the network are concerned
  696. about being identified by an adversary, not with being proven guilty
  697. beyond any reasonable doubt. Still it is something, and may be desired
  698. in some settings.
  699. It is reasonable to think that this attack can be easily extended to
  700. longer paths should those be used; nonetheless there may be some
  701. advantage to random path length. If the number of nodes is unknown,
  702. then the adversary would need to send streams to all the nodes in the
  703. network and analyze the resulting latency from them to be reasonably
  704. certain that it has not missed the first node in the circuit. Also,
  705. the attack does not identify the order of nodes in a route, so the
  706. longer the route, the greater the uncertainty about which node might
  707. be first. It may be possible to extend the attack to learn the route
  708. node order, but it is not clear that this is practically feasible.
  709. Another way to reduce the threats to both enclaves and simple Tor
  710. clients is to have helper nodes. Helper nodes were introduced
  711. in~\cite{wright03} as a suggested means of protecting the identity
  712. of the initiator of a communication in various anonymity protocols.
  713. The idea is to use a single trusted node as the first one you go to,
  714. that way an attacker cannot ever attack the first nodes you connect
  715. to and do some form of intersection attack. This will not affect the
  716. Danezis-Murdoch attack at all.
  717. We have to pick the path length so adversary can't distinguish client from
  718. server (how many hops is good?).
  719. in practice, plausible deniability is hypothetical and doesn't seem very
  720. convincing. if ISPs find the activity antisocial, they don't care *why*
  721. your computer is doing that behavior.
  722. [arma will write this section]
  723. \subsection{Helper nodes}
  724. \label{subsec:helper-nodes}
  725. When does fixing your entry or exit node help you?
  726. Helper nodes in the literature don't deal with churn, and
  727. especially active attacks to induce churn.
  728. Do general DoS attacks have anonymity implications? See e.g. Adam
  729. Back's IH paper, but I think there's more to be pointed out here.
  730. Game theory for helper nodes: if Alice offers a hidden service on a
  731. server (enclave model), and nobody ever uses helper nodes, then against
  732. George+Steven's attack she's totally nailed. If only Alice uses a helper
  733. node, then she's still identified as the source of the data. If everybody
  734. uses a helper node (including Alice), then the attack identifies the
  735. helper node and also Alice, and knows which one is which. If everybody
  736. uses a helper node (but not Alice), then the attacker figures the real
  737. source was a client that is using Alice as a helper node. [How's my
  738. logic here?]
  739. point to routing-zones section re: helper nodes to defend against
  740. big stuff.
  741. [nick will write this section]
  742. \subsection{Location-hidden services}
  743. [arma will write this section]
  744. Survivable services are new in practice, yes? Hidden services seem
  745. less hidden than we'd like, since they stay in one place and get used
  746. a lot. They're the epitome of the need for helper nodes. This means
  747. that using Tor as a building block for Free Haven is going to be really
  748. hard. Also, they're brittle in terms of intersection and observation
  749. attacks. Would be nice to have hot-swap services, but hard to design.
  750. people are using hidden services as a poor man's vpn and firewall-buster.
  751. rather than playing with dyndns and trying to pierce holes in their
  752. firewall (say, so they can ssh in from the outside), they run a hidden
  753. service on the inside and then rendezvous with that hidden service
  754. externally.
  755. in practice, sites like bloggers without borders (www.b19s.org) are
  756. running tor servers but more important are advertising a hidden-service
  757. address on their front page. doing this can provide increased robustness
  758. if they used the dual-IP approach we describe in tor-design, but in
  759. practice they do it to a) increase visibility of the tor project and their
  760. support for privacy, and b) to offer a way for their users, using vanilla
  761. software, to get end-to-end encryption and end-to-end authentication to
  762. their website.
  763. \subsection{Trust and discovery}
  764. [arma will edit this and expand/retract it]
  765. The published Tor design adopted a deliberately simplistic design for
  766. authorizing new nodes and informing clients about servers and their status.
  767. In the early Tor designs, all ORs periodically uploaded a signed description
  768. of their locations, keys, and capabilities to each of several well-known {\it
  769. directory servers}. These directory servers constructed a signed summary
  770. of all known ORs (a ``directory''), and a signed statement of which ORs they
  771. believed to be operational at any given time (a ``network status''). Clients
  772. periodically downloaded a directory in order to learn the latest ORs and
  773. keys, and more frequently downloaded a network status to learn which ORs are
  774. likely to be running. ORs also operate as directory caches, in order to
  775. lighten the bandwidth on the authoritative directory servers.
  776. In order to prevent Sybil attacks (wherein an adversary signs up many
  777. purportedly independent servers in order to increase her chances of observing
  778. a stream as it enters and leaves the network), the early Tor directory design
  779. required the operators of the authoritative directory servers to manually
  780. approve new ORs. Unapproved ORs were included in the directory, but clients
  781. did not use them at the start or end of their circuits. In practice,
  782. directory administrators performed little actual verification, and tended to
  783. approve any OR whose operator could compose a coherent email. This procedure
  784. may have prevented trivial automated Sybil attacks, but would do little
  785. against a clever attacker.
  786. There are a number of flaws in this system that need to be addressed as we
  787. move forward. They include:
  788. \begin{tightlist}
  789. \item Each directory server represents an independent point of failure; if
  790. any one were compromised, it could immediately compromise all of its users
  791. by recommending only compromised ORs.
  792. \item The more servers appear join the network, the more unreasonable it
  793. becomes to expect clients to know about them all. Directories
  794. become unfeasibly large, and downloading the list of servers becomes
  795. burdonsome.
  796. \item The validation scheme may do as much harm as it does good. It is not
  797. only incapable of preventing clever attackers from mounting Sybil attacks,
  798. but may deter server operators from joining the network. (For instance, if
  799. they expect the validation process to be difficult, or if they do not share
  800. any languages in common with the directory server operators.)
  801. \end{tightlist}
  802. We could try to move the system in several directions, depending on our
  803. choice of threat model and requirements. If we did not need to increase
  804. network capacity in order to support more users, there would be no reason not
  805. to adopt even stricter validation requirements, and reduce the number of
  806. servers in the network to a trusted minimum. But since we want Tor to work
  807. for as many users as it can, we need XXXXX
  808. In order to address the first two issues, it seems wise to move to a system
  809. including a number of semi-trusted directory servers, no one of which can
  810. compromise a user on its own. Ultimately, of course, we cannot escape the
  811. problem of a first introducer: since most users will run Tor in whatever
  812. configuration the software ships with, the Tor distribution itself will
  813. remain a potential single point of failure so long as it includes the seed
  814. keys for directory servers, a list of directory servers, or any other means
  815. to learn which servers are on the network. But omitting this information
  816. from the Tor distribution would only delegate the trust problem to the
  817. individual users, most of whom are presumably less informed about how to make
  818. trust decisions than the Tor developers.
  819. %Network discovery, sybil, node admission, scaling. It seems that the code
  820. %will ship with something and that's our trust root. We could try to get
  821. %people to build a web of trust, but no. Where we go from here depends
  822. %on what threats we have in mind. Really decentralized if your threat is
  823. %RIAA; less so if threat is to application data or individuals or...
  824. \section{Crossroads: Scaling}
  825. %\label{sec:crossroads-scaling}
  826. %P2P + anonymity issues:
  827. Tor is running today with hundreds of servers and tens of thousands of
  828. users, but it will certainly not scale to millions.
  829. Scaling Tor involves three main challenges. First is safe server
  830. discovery, both bootstrapping -- how a Tor client can robustly find an
  831. initial server list -- and ongoing -- how a Tor client can learn about
  832. a fair sample of honest servers and not let the adversary control his
  833. circuits (see Section x). Second is detecting and handling the speed
  834. and reliability of the variety of servers we must use if we want to
  835. accept many servers (see Section y).
  836. Since the speed and reliability of a circuit is limited by its worst link,
  837. we must learn to track and predict performance. Finally, in order to get
  838. a large set of servers in the first place, we must address incentives
  839. for users to carry traffic for others (see Section incentives).
  840. \subsection{Incentives by Design}
  841. [nick will try to make this section shorter and more to the point.]
  842. [most of the technical incentive schemes in the literature introduce
  843. anonymity issues which we don't understand yet, and we seem to be doing
  844. ok without them]
  845. There are three behaviors we need to encourage for each server: relaying
  846. traffic; providing good throughput and reliability while doing it;
  847. and allowing traffic to exit the network from that server.
  848. We encourage these behaviors through \emph{indirect} incentives, that
  849. is, designing the system and educating users in such a way that users
  850. with certain goals will choose to relay traffic. In practice, the
  851. main incentive for running a Tor server is social benefit: volunteers
  852. altruistically donate their bandwidth and time. We also keep public
  853. rankings of the throughput and reliability of servers, much like
  854. seti@home. We further explain to users that they can get \emph{better
  855. security} by operating a server, because they get plausible deniability
  856. (indeed, they may not need to route their own traffic through Tor at all
  857. -- blending directly with other traffic exiting Tor may be sufficient
  858. protection for them), and because they can use their own Tor server
  859. as entry or exit point and be confident it's not run by the adversary.
  860. Finally, we can improve the usability and feature set of the software:
  861. rate limiting support and easy packaging decrease the hassle of
  862. maintaining a server, and our configurable exit policies allow each
  863. operator to advertise a policy describing the hosts and ports to which
  864. he feels comfortable connecting.
  865. Beyond these, however, there is also a need for \emph{direct} incentives:
  866. providing payment or other resources in return for high-quality service.
  867. Paying actual money is problematic: decentralized e-cash systems are
  868. not yet practical, and a centralized collection system not only reduces
  869. robustness, but also has failed in the past (the history of commercial
  870. anonymizing networks is littered with failed attempts). A more promising
  871. option is to use a tit-for-tat incentive scheme: provide better service
  872. to nodes that have provided good service to you.
  873. Unfortunately, such an approach introduces new anonymity problems.
  874. Does the incentive system enable the adversary to attract more traffic by
  875. performing well? Typically a user who chooses evenly from all options is
  876. most resistant to an adversary targetting him, but that approach prevents
  877. us from handling heterogeneous servers \cite{casc-rep}.
  878. When a server (call him Steve) performs well for Alice, does Steve gain
  879. reputation with the entire system, or just with Alice? If the entire
  880. system, how does Alice tell everybody about her experience in a way that
  881. prevents her from lying about it yet still protects her identity? If
  882. Steve's behavior only affects Alice's behavior, does this allow Steve to
  883. selectively perform only for Alice, and then break her anonymity later
  884. when somebody (presumably Alice) routes through his node?
  885. These are difficult and open questions, yet choosing not to scale means
  886. leaving most users to a less secure network or no anonymizing network
  887. at all. We will start with a simplified approach to the tit-for-tat
  888. incentive scheme based on two rules: (1) each node should measure the
  889. service it receives from adjacent nodes, and provide service relative to
  890. the received service, but (2) when a node is making decisions that affect
  891. its own security (e.g. when building a circuit for its own application
  892. connections), it should choose evenly from a sufficiently large set of
  893. nodes that meet some minimum service threshold. This approach allows us
  894. to discourage bad service without opening Alice up as much to attacks.
  895. %XXX rewrite the above so it sounds less like a grant proposal and
  896. %more like a "if somebody were to try to solve this, maybe this is a
  897. %good first step".
  898. %We should implement the above incentive scheme in the
  899. %deployed Tor network, in conjunction with our plans to add the necessary
  900. %associated scalability mechanisms. We will do experiments (simulated
  901. %and/or real) to determine how much the incentive system improves
  902. %efficiency over baseline, and also to determine how far we are from
  903. %optimal efficiency (what we could get if we ignored the anonymity goals).
  904. \subsection{Peer-to-peer / practical issues}
  905. [leave this section for now, and make sure things here are covered
  906. elsewhere. then remove it.]
  907. Making use of servers with little bandwidth. How to handle hammering by
  908. certain applications.
  909. Handling servers that are far away from the rest of the network, e.g. on
  910. the continents that aren't North America and Europe. High latency,
  911. often high packet loss.
  912. Running Tor servers behind NATs, behind great-firewalls-of-China, etc.
  913. Restricted routes. How to propagate to everybody the topology? BGP
  914. style doesn't work because we don't want just *one* path. Point to
  915. Geoff's stuff.
  916. \subsection{Location diversity and ISP-class adversaries}
  917. \label{subsec:routing-zones}
  918. Anonymity networks have long relied on diversity of node location for
  919. protection against attacks---typically an adversary who can observe a
  920. larger fraction of the network can launch a more effective attack. One
  921. way to achieve dispersal involves growing the network so a given adversary
  922. sees less. Alternately, we can arrange the topology so traffic can enter
  923. or exit at many places (for example, by using a free-route network
  924. like Tor rather than a cascade network like JAP). Lastly, we can use
  925. distributed trust to spread each transaction over multiple jurisdictions.
  926. But how do we decide whether two nodes are in related locations?
  927. Feamster and Dingledine defined a \emph{location diversity} metric
  928. in \cite{feamster:wpes2004}, and began investigating a variant of location
  929. diversity based on the fact that the Internet is divided into thousands of
  930. independently operated networks called {\em autonomous systems} (ASes).
  931. The key insight from their paper is that while we typically think of a
  932. connection as going directly from the Tor client to her first Tor node,
  933. actually it traverses many different ASes on each hop. An adversary at
  934. any of these ASes can monitor or influence traffic. Specifically, given
  935. plausible initiators and recipients and path random path selection,
  936. some ASes in the simulation were able to observe 10\% to 30\% of the
  937. transactions (that is, learn both the origin and the destination) on
  938. the deployed Tor network (33 nodes as of June 2004).
  939. The paper concludes that for best protection against the AS-level
  940. adversary, nodes should be in ASes that have the most links to other ASes:
  941. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  942. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  943. initiator and responder are both in the U.S., it actually \emph{hurts}
  944. our location diversity to add far-flung nodes in continents like Asia
  945. or South America.
  946. Many open questions remain. First, it will be an immense engineering
  947. challenge to get an entire BGP routing table to each Tor client, or at
  948. least summarize it sufficiently. Without a local copy, clients won't be
  949. able to safely predict what ASes will be traversed on the various paths
  950. through the Tor network to the final destination. Tarzan~\cite{tarzan:ccs02}
  951. and MorphMix~\cite{morphmix:fc04} suggest that we compare IP prefixes to
  952. determine location diversity; but the above paper showed that in practice
  953. many of the Mixmaster nodes that share a single AS have entirely different
  954. IP prefixes. When the network has scaled to thousands of nodes, does IP
  955. prefix comparison become a more useful approximation?
  956. %
  957. Second, can take advantage of caching certain content at the exit nodes, to
  958. limit the number of requests that need to leave the network at all.
  959. what about taking advantage of caches like akamai's or googles? what
  960. about treating them as adversaries?
  961. %
  962. Third, if we follow the paper's recommendations and tailor path selection
  963. to avoid choosing endpoints in similar locations, how much are we hurting
  964. anonymity against larger real-world adversaries who can take advantage
  965. of knowing our algorithm?
  966. %
  967. Lastly, can we use this knowledge to figure out which gaps in our network
  968. would most improve our robustness to this class of attack, and go recruit
  969. new servers with those ASes in mind?
  970. Tor's security relies in large part on the dispersal properties of its
  971. network. We need to be more aware of the anonymity properties of various
  972. approaches we can make better design decisions in the future.
  973. \subsection{The China problem}
  974. \label{subsec:china}
  975. Citizens in a variety of countries, such as most recently China and
  976. Iran, are periodically blocked from accessing various sites outside
  977. their country. These users try to find any tools available to allow
  978. them to get-around these firewalls. Some anonymity networks, such as
  979. Six-Four~\cite{six-four}, are designed specifically with this goal in
  980. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  981. such as Voice of America to set up a network to encourage `Internet
  982. freedom'~\cite{voice-of-america-anonymizer}. Even though Tor wasn't
  983. designed with ubiquitous access to the network in mind, thousands of
  984. users across the world are trying to use it for exactly this purpose.
  985. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  986. Anti-censorship networks hoping to bridge country-level blocks face
  987. a variety of challenges. One of these is that they need to find enough
  988. exit nodes---servers on the `free' side that are willing to relay
  989. arbitrary traffic from users to their final destinations. Anonymizing
  990. networks including Tor are well-suited to this task, since we have
  991. already gathered a set of exit nodes that are willing to tolerate some
  992. political heat.
  993. The other main challenge is to distribute a list of reachable relays
  994. to the users inside the country, and give them software to use them,
  995. without letting the authorities also enumerate this list and block each
  996. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  997. addresses (or having them donated), abandoning old addresses as they are
  998. `used up', and telling a few users about the new ones. Distributed
  999. anonymizing networks again have an advantage here, in that we already
  1000. have tens of thousands of separate IP addresses whose users might
  1001. volunteer to provide this service since they've already installed and use
  1002. the software for their own privacy~\cite{koepsell:wpes2004}. Because
  1003. the Tor protocol separates routing from network discovery (see Section
  1004. \ref{do-we-discuss-this?}), volunteers could configure their Tor clients
  1005. to generate server descriptors and send them to a special directory
  1006. server that gives them out to dissidents who need to get around blocks.
  1007. Of course, this still doesn't prevent the adversary
  1008. from enumerating all the volunteer relays and blocking them preemptively.
  1009. Perhaps a tiered-trust system could be built where a few individuals are
  1010. given relays' locations, and they recommend other individuals by telling them
  1011. those addresses, thus providing a built-in incentive to avoid letting the
  1012. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  1013. might help to bound the number of IP addresses leaked to the adversary. Groups
  1014. like the W3C are looking into using Tor as a component in an overall system to
  1015. help address censorship; we wish them luck.
  1016. %\cite{infranet}
  1017. \subsection{Non-clique topologies}
  1018. [nick will try to shrink this section]
  1019. Because of its threat model that is substantially weaker than high
  1020. latency mixnets, Tor is actually in a potentially better position to
  1021. scale at least initially. From the perspective of a mix network, one
  1022. of the worst things that can happen is partitioning. The more
  1023. potential senders of messages entering the network the better the
  1024. anonymity. Roughly, if a network is, e.g., split in half, then your
  1025. anonymity is cut in half. Attacks become half as hard (if they're
  1026. linear in network size), etc. In some sense this is still true for
  1027. Tor: if you want to know who Alice is talking to, you can watch her
  1028. for one end of a circuit. For a half size network, you then only have
  1029. to brute force examine half as many nodes to find the other end. But
  1030. Tor is not meant to cope with someone directly attacking many dozens
  1031. of nodes in a few minutes. It was meant to cope with traffic
  1032. confirmation attacks. And, these are independent of the size of the
  1033. network. So, a simple possibility when the scale of a Tor network
  1034. exceeds some size is to simply split it. Care could be taken in
  1035. allocating which nodes go to which network along the lines of
  1036. \cite{casc-rep} to insure that collaborating hostile nodes are not
  1037. able to gain any advantage in network splitting that they do not
  1038. already have in joining a network.
  1039. The attacks in \cite{attack-tor-oak05} show that certain types of
  1040. brute force attacks are in fact feasible; however they make the
  1041. above point stronger not weaker. The attacks do not appear to be
  1042. significantly more difficult to mount against a network that is
  1043. twice the size. Also, they only identify the Tor nodes used in a
  1044. circuit, not the client. Finally note that even if the network is split,
  1045. a client does not need to use just one of the two resulting networks.
  1046. Alice could use either of them, and it would not be difficult to make
  1047. the Tor client able to access several such network on a per circuit
  1048. basis. More analysis is needed; we simply note here that splitting
  1049. a Tor network is an easy way to achieve moderate scalability and that
  1050. it does not necessarily have the same implications as splitting a mixnet.
  1051. Alternatively, we can try to scale a single network. Some issues for
  1052. scaling include how many neighbors can nodes support and how many
  1053. users (and how much application traffic capacity) can the network
  1054. handle for each new node that comes into the network. This depends on
  1055. many things, most notably the traffic capacity of the new nodes. We
  1056. can observe, however, that adding a tor node of any feasible bandwidth
  1057. will increase the traffic capacity of the network. This means that, as
  1058. a first step to scaling, we can focus on the interconnectivity of the
  1059. nodes, followed by directories, discovery, etc.
  1060. By reducing the connectivity of the network we increase the total
  1061. number of nodes that the network can contain. Anonymity implications
  1062. of restricted routes for mix networks have already been explored by
  1063. Danezis~\cite{danezis-pets03}. That paper explicitly considered only
  1064. traffic analysis resistance provided by a mix network and sidestepped
  1065. questions of traffic confirmation resistance. But, Tor is designed
  1066. only to resist traffic confirmation. For this and other reasons, we
  1067. cannot simply adopt his mixnet results to onion routing networks. If
  1068. an attacker gains minimal increase in the likelyhood of compromising
  1069. the endpoints of a Tor circuit through a sparse network (vs.\ a clique
  1070. on the same node set), then the restriction will have had minimal
  1071. impact on the anonymity provided by that network.
  1072. The approach Danezis describes is based on expander graphs, i.e.,
  1073. graphs in which any subgraph of nodes is likely to have lots of nodes
  1074. as neighbors. For Tor, we may not need to have an expander per se, it
  1075. may be enough to have a single subnet that is highly connected. As an
  1076. example, assume fifty nodes of relatively high traffic capacity. This
  1077. \emph{center} forms are a clique. Assume each center node can each
  1078. handle 200 connections to other nodes (including the other ones in the
  1079. center). Assume every noncenter node connects to three nodes in the
  1080. center and anyone out of the center that they want to. Then the
  1081. network easily scales to c. 2500 nodes with commensurate increase in
  1082. bandwidth. There are many open questions: how directory information
  1083. is distributed (presumably information about the center nodes could
  1084. be given to any new nodes with their codebase), whether center nodes
  1085. will need to function as a `backbone', etc. As above the point is
  1086. that this would create problems for the expected anonymity for a mixnet,
  1087. but for an onion routing network where anonymity derives largely from
  1088. the edges, it may be feasible.
  1089. Another point is that we already have a non-clique topology.
  1090. Individuals can set up and run Tor nodes without informing the
  1091. directory servers. This will allow, e.g., dissident groups to run a
  1092. local Tor network of such nodes that connects to the public Tor
  1093. network. This network is hidden behind the Tor network and its
  1094. only visible connection to Tor at those points where it connects.
  1095. As far as the public network is concerned or anyone observing it,
  1096. they are running clients.
  1097. \section{The Future}
  1098. \label{sec:conclusion}
  1099. we should put random thoughts here until there are enough for a
  1100. conclusion.
  1101. will our sustainability approach work? we'll see.
  1102. "These are difficult and open questions, yet choosing not to solve them
  1103. means leaving most users to a less secure network or no anonymizing
  1104. network at all."
  1105. \bibliographystyle{plain} \bibliography{tor-design}
  1106. \clearpage
  1107. \appendix
  1108. \begin{figure}[t]
  1109. %\unitlength=1in
  1110. \centering
  1111. %\begin{picture}(6.0,2.0)
  1112. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  1113. %\end{picture}
  1114. \mbox{\epsfig{figure=graphnodes,width=5in}}
  1115. \caption{Number of servers over time. Lowest line is number of exit
  1116. nodes that allow connections to port 80. Middle line is total number of
  1117. verified (registered) servers. The line above that represents servers
  1118. that are not yet registered.}
  1119. \label{fig:graphnodes}
  1120. \end{figure}
  1121. \begin{figure}[t]
  1122. \centering
  1123. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  1124. \caption{The sum of traffic reported by each server over time. The bottom
  1125. pair show average throughput, and the top pair represent the largest 15
  1126. minute burst in each 4 hour period.}
  1127. \label{fig:graphtraffic}
  1128. \end{figure}
  1129. \end{document}