challenges.tex 58 KB

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  1. \documentclass{llncs}
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  12. \begin{document}
  13. \title{Challenges in practical low-latency stream anonymity (DRAFT)}
  14. \author{Roger Dingledine and Nick Mathewson}
  15. \institute{The Free Haven Project\\
  16. \email{\{arma,nickm\}@freehaven.net}}
  17. \maketitle
  18. \pagestyle{empty}
  19. \begin{abstract}
  20. foo
  21. \end{abstract}
  22. \section{Introduction}
  23. Tor is a low-latency anonymous communication overlay network designed
  24. to be practical and usable for protecting TCP streams over the
  25. Internet~\cite{tor-design}. We have been operating a publicly deployed
  26. Tor network since October 2003 that has grown to over a hundred volunteer
  27. nodes and carries on average over 70 megabits of traffic per second.
  28. Tor has a weaker threat model than many anonymity designs in the
  29. literature, because our foremost goal is to deploy a
  30. practical and useful network for interactive (low-latency) communications.
  31. Subject to this restriction, we try to
  32. provide as much anonymity as we can. In particular, because we
  33. support interactive communications without impractically expensive padding,
  34. we fall prey to a variety
  35. of intra-network~\cite{attack-tor-oak05,flow-correlation04,bar} and
  36. end-to-end~\cite{danezis-pet2004,SS03} anonymity-breaking attacks.
  37. Tor is secure so long as adversaries are unable to
  38. observe connections as they both enter and leave the Tor network.
  39. Therefore, Tor's defense lies in having a diverse enough set of servers
  40. that most real-world
  41. adversaries are unlikely to be in the right places to attack users.
  42. Specifically,
  43. Tor aims to resist observers and insiders by distributing each transaction
  44. over several nodes in the network. This ``distributed trust'' approach
  45. means the Tor network can be safely operated and used by a wide variety
  46. of mutually distrustful users, providing more sustainability and security
  47. than some previous attempts at anonymizing networks.
  48. The Tor network has a broad range of users, including ordinary citizens
  49. concerned about their privacy, corporations
  50. who don't want to reveal information to their competitors, and law
  51. enforcement and government intelligence agencies who need
  52. to do operations on the Internet without being noticed.
  53. Tor research and development has been funded by the U.S. Navy, for use
  54. in securing government
  55. communications, and also by the Electronic Frontier Foundation, for use
  56. in maintaining civil liberties for ordinary citizens online. The Tor
  57. protocol is one of the leading choices
  58. to be the anonymizing layer in the European Union's PRIME directive to
  59. help maintain privacy in Europe. The University of Dresden in Germany
  60. has integrated an independent implementation of the Tor protocol into
  61. their popular Java Anon Proxy anonymizing client. This wide variety of
  62. interests helps maintain both the stability and the security of the
  63. network.
  64. %awk
  65. Tor's principal research strategy, in attempting to deploy a network that is
  66. practical, useful, and anonymous, has been to insist, when trade-offs arise
  67. between these properties, on remaining useful enough to attract many users,
  68. and practical enough to support them. Subject to these
  69. constraints, we aim to maximize anonymity. This is not the only possible
  70. direction in anonymity research: designs exist that provide more anonymity
  71. than Tor at the expense of significantly increased resource requirements, or
  72. decreased flexibility in application support (typically because of increased
  73. latency). Such research does not typically abandon aspirations towards
  74. deployability or utility, but instead tries to maximize deployability and
  75. utility subject to a certain degree of inherent anonymity (inherent because
  76. usability and practicality affect usage which affects the actual anonymity
  77. provided by the network \cite{back01,econymics}). We believe that these
  78. approaches can be promising and useful, but that by focusing on deploying a
  79. usable system in the wild, Tor helps us experiment with the actual parameters
  80. of what makes a system ``practical'' for volunteer operators and ``useful''
  81. for home users, and helps illuminate undernoticed issues which any deployed
  82. volunteer anonymity network will need to address.
  83. While~\cite{tor-design} gives an overall view of the Tor design and goals,
  84. this paper describes the policy and technical issues that Tor faces as
  85. we continue deployment. Rather than trying to provide complete solutions
  86. to every problem here, we lay out the assumptions and constraints
  87. that we have observed through deploying Tor in the wild. In doing so, we
  88. aim to create a research agenda for others to
  89. help in addressing these issues. Section~\ref{sec:what-is-tor} gives an
  90. overview of the Tor
  91. design and ours goals. Sections~\ref{sec:crossroads-policy}
  92. and~\ref{sec:crossroads-technical} go on to describe the practical challenges,
  93. both policy and technical respectively, that stand in the way of moving
  94. from a practical useful network to a practical useful anonymous network.
  95. \section{What Is Tor}
  96. \label{sec:what-is-tor}
  97. Here we give a basic overview of the Tor design and its properties. For
  98. details on the design, assumptions, and security arguments, we refer
  99. the reader to~\cite{tor-design}.
  100. \subsection{Distributed trust: safety in numbers}
  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. %This hidden service functionality could allow Tor users to
  132. %set up a website where people publish material without worrying about
  133. %censorship. Nobody would be able to determine who was offering the site,
  134. %and nobody who offered the site would know who was posting to it.
  135. Tor attempts to anonymize the transport layer, not the application layer, so
  136. application protocols that include personally identifying information need
  137. additional application-level scrubbing proxies, such as
  138. Privoxy~\cite{privoxy} for HTTP. Furthermore, Tor does not permit arbitrary
  139. IP packets; it only anonymizes TCP and DNS, and only supports cconnections
  140. SOCKS (see section \ref{subsec:tcp-vs-ip}).
  141. Tor differs from other deployed systems for traffic analysis resistance
  142. in its security and flexibility. Mix networks such as
  143. Mixmaster~\cite{mixmaster} or its successor Mixminion~\cite{minion-design}
  144. gain the highest degrees of anonymity at the expense of introducing highly
  145. variable delays, thus making them unsuitable for applications such as web
  146. browsing that require quick response times. Commercial single-hop
  147. proxies~\cite{anonymizer} present a single point of failure, where
  148. a single compromise can expose all users' traffic, and a single-point
  149. eavesdropper can perform traffic analysis on the entire network.
  150. Also, their proprietary implementations place any infrastucture that
  151. depends on these single-hop solutions at the mercy of their providers'
  152. financial health as well as network security.
  153. No organization can achieve this security on its own. If a single
  154. corporation or government agency were to build a private network to
  155. protect its operations, any connections entering or leaving that network
  156. would be obviously linkable to the controlling organization. The members
  157. and operations of that agency would be easier, not harder, to distinguish.
  158. Instead, to protect our networks from traffic analysis, we must
  159. collaboratively blend the traffic from many organizations and private
  160. citizens, so that an eavesdropper can't tell which users are which,
  161. and who is looking for what information. By bringing more users onto
  162. the network, all users become more secure \cite{econymics}.
  163. Naturally, organizations will not want to depend on others for their
  164. security. If most participating providers are reliable, Tor tolerates
  165. some hostile infiltration of the network. For maximum protection,
  166. the Tor design includes an enclave approach that lets data be encrypted
  167. (and authenticated) end-to-end, so high-sensitivity users can be sure it
  168. hasn't been read or modified. This even works for Internet services that
  169. don't have built-in encryption and authentication, such as unencrypted
  170. HTTP or chat, and it requires no modification of those services to do so.
  171. weasel's graph of \# nodes and of bandwidth, ideally from week 0.
  172. Tor doesn't try to provide steg (but see Sec \ref{china}), or
  173. the other non-goals listed in tor-design.
  174. [arma will do this part]
  175. Tor is not the only anonymity system that aims to be practical and useful.
  176. Commercial single-hop proxies~\cite{anonymizer}, as well as unsecured
  177. open proxies around the Internet~\cite{open-proxies}, can provide good
  178. performance and some security against a weaker attacker. Dresden's Java
  179. Anon Proxy~\cite{jap} provides similar functionality to Tor but only
  180. handles web browsing rather than arbitrary TCP. Also, JAP's network
  181. topology uses cascades (fixed routes through the network); since without
  182. end-to-end padding it is just as vulnerable as Tor to end-to-end timing
  183. attacks, its dispersal properties are therefore worse than Tor's.
  184. %Some peer-to-peer file-sharing overlay networks such as
  185. %Freenet~\cite{freenet} and Mute~\cite{mute}
  186. Zero-Knowledge Systems' commercial Freedom
  187. network~\cite{freedom21-security} was even more flexible than Tor in
  188. that it could transport arbitrary IP packets, and it also supported
  189. pseudonymous access rather than just anonymous access; but it had
  190. a different approach to sustainability (collecting money from users
  191. and paying ISPs to run servers), and has shut down due to financial
  192. load. Finally, more scalable designs like Tarzan~\cite{tarzan} and
  193. MorphMix~\cite{morphmix} have been proposed in the literature, but
  194. have not yet been fielded. We direct the interested reader to Section
  195. 2 of~\cite{tor-design} for a more indepth review of related work.
  196. %six-four. crowds. i2p.
  197. have a serious discussion of morphmix's assumptions, since they would
  198. seem to be the direct competition. in fact tor is a flexible architecture
  199. that would encompass morphmix, and they're nearly identical except for
  200. path selection and node discovery. and the trust system morphmix has
  201. seems overkill (and/or insecure) based on the threat model we've picked.
  202. % this para should probably move to the scalability / directory system. -RD
  203. \section{Threat model}
  204. Tor does not attempt to defend against a global observer. Any adversary who
  205. can see a user's connection to the Tor network, and who can see the
  206. corresponding connection as it exits the Tor network, can use the timing
  207. correlation between the two connections to confirm the user's chosen
  208. communication partners. Defeating this attack would seem to require
  209. introducing a prohibitive degree of traffic padding between the user and the
  210. network, or introducing an unacceptable degree of latency (but see
  211. \ref{subsec:mid-latency} below). Thus, Tor only
  212. attempts to defend against external observers who can observe both sides of a
  213. user's connection.
  214. Against internal attackers, who sign up Tor servers, the situation is more
  215. complicated. In the simplest case, if an adversary has compromised $c$ of
  216. $n$ servers on the Tor network, then the adversary will be able to compromise
  217. a random circuit with probability $\frac{c^2}{n^2}$ (since the circuit
  218. initiator chooses hops randomly). But there are
  219. complicating factors:
  220. \begin{tightlist}
  221. \item If the user continues to build random circuits over time, an adversary
  222. is pretty certain to see a statistical sample of the user's traffic, and
  223. thereby can build an increasingly accurate profile of her behavior. (See
  224. \ref{subsec:helper-nodes} for possible solutions.)
  225. \item If an adversary controls a popular service outside of the Tor network,
  226. he can be certain of observing all connections to that service; he
  227. therefore will trace connections to that service with probability
  228. $\frac{c}{n}$.
  229. \item Users do not in fact choose servers with uniform probability; they
  230. favor servers with high bandwidth, and exit servers that permit connections
  231. to their favorite services.
  232. \end{tightlist}
  233. %discuss $\frac{c^2}{n^2}$, except how in practice the chance of owning
  234. %the last hop is not $c/n$ since that doesn't take the destination (website)
  235. %into account. so in cases where the adversary does not also control the
  236. %final destination we're in good shape, but if he *does* then we'd be better
  237. %off with a system that lets each hop choose a path.
  238. %
  239. %Isn't it more accurate to say ``If the adversary _always_ controls the final
  240. % dest, we would be just as well off with such as system.'' ? If not, why
  241. % not? -nm
  242. in practice tor's threat model is based entirely on the goal of dispersal
  243. and diversity. george and steven describe an attack \cite{draft} that
  244. lets them determine the nodes used in a circuit; yet they can't identify
  245. alice or bob through this attack. so it's really just the endpoints that
  246. remain secure. and the enclave model seems particularly threatened by
  247. this, since this attack lets us identify endpoints when they're servers.
  248. see \ref{subsec:helper-nodes} for discussion of some ways to address this
  249. issue.
  250. see \ref{subsec:routing-zones} for discussion of larger
  251. adversaries and our dispersal goals.
  252. [this section will get written once the rest of the paper is farther along]
  253. \section{Crossroads: Policy issues}
  254. \label{sec:crossroads-policy}
  255. Many of the issues the Tor project needs to address are not just a
  256. matter of system design or technology development. In particular, the
  257. Tor project's \emph{image} with respect to its users and the rest of
  258. the Internet impacts the security it can provide.
  259. As an example to motivate this section, some U.S.~Department of Enery
  260. penetration testing engineers are tasked with compromising DoE computers
  261. from the outside. They only have a limited number of ISPs from which to
  262. launch their attacks, and they found that the defenders were recognizing
  263. attacks because they came from the same IP space. These engineers wanted
  264. to use Tor to hide their tracks. First, from a technical standpoint,
  265. Tor does not support the variety of IP packets one would like to use in
  266. such attacks (see Section \ref{subsec:ip-vs-tcp}). But aside from this,
  267. we also decided that it would probably be poor precedent to encourage
  268. such use---even legal use that improves national security---and managed
  269. to dissuade them.
  270. With this image issue in mind, here we discuss the Tor user base and
  271. Tor's interaction with other services on the Internet.
  272. \subsection{Image and reputability}
  273. Image: substantial non-infringing uses. Image is a security parameter,
  274. since it impacts user base and perceived sustainability.
  275. grab reputability paragraphs from usability.tex [arma will do this]
  276. A Tor gui, how jap's gui is nice but does not reflect the security
  277. they provide.
  278. Public perception, and thus advertising, is a security parameter.
  279. good uses are kept private, bad uses are publicized. not good.
  280. users do not correlate to anonymity. arma will do this.
  281. \subsection{Usability and bandwidth and sustainability and incentives}
  282. low-pain-threshold users go away until all users are willing to use it
  283. Sustainability. Previous attempts have been commercial which we think
  284. adds a lot of unnecessary complexity and accountability. Freedom didn't
  285. collect enough money to pay its servers; JAP bandwidth is supported by
  286. continued money, and they periodically ask what they will do when it
  287. dries up.
  288. "outside of academia, jap has just lost, permanently"
  289. Usability: fc03 paper was great, except the lower latency you are the
  290. less useful it seems it is.
  291. [nick will write this section]
  292. \subsection{Tor and file-sharing}
  293. [nick will write this section]
  294. Bittorrent and dmca. Should we add an IDS to autodetect protocols and
  295. snipe them?
  296. because only at the exit is it evident what port or protocol a given
  297. tor stream is, you can't choose not to carry file-sharing traffic.
  298. hibernation vs rate-limiting: do we want diversity or throughput? i
  299. think we're shifting back to wanting diversity.
  300. \subsection{Tor and blacklists}
  301. Takedowns and efnet abuse and wikipedia complaints and irc
  302. networks.
  303. It was long expected that, alongside Tor's legitimate users, it would also
  304. attract troublemakers who exploited Tor in order to abuse services on the
  305. Internet. Our initial answer to this situation was to use ``exit policies''
  306. to allow individual Tor servers to block access to specific IP/port ranges.
  307. This approach was meant to make operators more willing to run Tor by allowing
  308. them to prevent their servers from being used for abusing particular
  309. services. For example, all Tor servers currently block SMTP (port 25), in
  310. order to avoid being used to send spam.
  311. This approach is useful, but is insufficient for two reasons. First, since
  312. it is not possible to force all ORs to block access to any given service,
  313. many of those services try to block Tor instead. More broadly, while being
  314. blockable is important to being good netizens, we would like to encourage
  315. services to allow anonymous access; services should not need to decide
  316. between blocking legitimate anonymous use and allowing unlimited abuse.
  317. This is potentially a bigger problem than it may appear.
  318. On the one hand, if people want to refuse connections from you on
  319. their servers it would seem that they should be allowed to. But, a
  320. possible major problem with the blocking of Tor is that it's not just
  321. the decision of the individual server administrator whose deciding if
  322. he wants to post to wikipedia from his Tor node address or allow
  323. people to read wikipedia anonymously through his Tor node. If e.g.,
  324. s/he comes through a campus or corporate NAT, then the decision must
  325. be to have the entire population behind it able to have a Tor exit
  326. node or write access to wikipedia. This is a loss for both of us (Tor
  327. and wikipedia). We don't want to compete for (or divvy up) the NAT
  328. protected entities of the world.
  329. (A related problem is that many IP blacklists are not terribly fine-grained.
  330. No current IP blacklist, for example, allow a service provider to blacklist
  331. only those Tor servers that allow access to a specific IP or port, even
  332. though this information is readily available. One IP blacklist even bans
  333. every class C network that contains a Tor server, and recommends banning SMTP
  334. from these networks even though Tor does not allow SMTP at all.)
  335. Problems of abuse occur mainly with services such as IRC networks and
  336. Wikipedia, which rely on IP-blocking to ban abusive users. While at first
  337. blush this practice might seem to depend on the anachronistic assumption that
  338. each IP is an identifier for a single user, it is actually more reasonable in
  339. practice: it assumes that non-proxy IPs are a costly resource, and that an
  340. abuser can not change IPs at will. By blocking IPs which are used by Tor
  341. servers, open proxies, and service abusers, these systems hope to make
  342. ongoing abuse difficult. Although the system is imperfect, it works
  343. tolerably well for them in practice.
  344. But of course, we would prefer that legitimate anonymous users be able to
  345. access abuse-prone services. One conceivable approach would be to require
  346. would-be IRC users, for instance, to register accounts if they wanted to
  347. access the IRC network from Tor. But in practise, this would not
  348. significantly impede abuse if creating new accounts were easily automatable;
  349. this is why services use IP blocking. In order to deter abuse, pseudonymous
  350. identities need to impose a significant switching cost in resources or human
  351. time.
  352. Once approach, similar to that taken by Freedom, would be to bootstrap some
  353. non-anonymous costly identification mechanism to allow access to a
  354. blind-signature pseudonym protocol. This would effectively create costly
  355. pseudonyms, which services could require in order to allow anonymous access.
  356. This approach has difficulties in practise, however:
  357. \begin{tightlist}
  358. \item Unlike Freedom, Tor is not a commercial service. Therefore, it would
  359. be a shame to require payment in order to make Tor useful, or to make
  360. non-paying users second-class citizens.
  361. \item It is hard to think of an underlying resource that would actually work.
  362. We could use IP addresses, but that's the problem, isn't it?
  363. \item Managing single sign-on services is not considered a well-solved
  364. problem in practice. If Microsoft can't get universal acceptance for
  365. passport, why do we think that a Tor-specific solution would do any good?
  366. \item Even if we came up with a perfect authentication system for our needs,
  367. there's no guarantee that any service would actually start using it. It
  368. would require a nonzero effort for them to support it, and it might just
  369. be less hassle for them to block tor anyway.
  370. \end{tightlist}
  371. Squishy IP based ``authentication'' and ``authorization'' is a reality
  372. we must contend with. We should say something more about the analogy
  373. with SSNs.
  374. \subsection{Other}
  375. [Once you build a generic overlay network, everybody wants to use it.]
  376. Tor's scope: How much should Tor aim to do? Applications that leak
  377. data: we can say they're not our problem, but they're somebody's problem.
  378. Also, the more widely deployed Tor becomes, the more people who need a
  379. deployed overlay network tell us they'd like to use us if only we added
  380. the following more features. For example, Blossom \cite{blossom} and
  381. random community wireless projects both want source-routable overlay
  382. networks for their own purposes. Fortunately, our modular design separates
  383. routing from node discovery; so we could implement Morphmix in Tor just
  384. by implementing the Morphmix-specific node discovery and path selection
  385. pieces. On the other hand, we could easily get distracted building a
  386. general-purpose overlay library, and we're only a few developers.
  387. [arma will work on this]
  388. %Should we allow revocation of anonymity if a threshold of
  389. %servers want to?
  390. Logging. Making logs not revealing. A happy coincidence that verbose
  391. logging is our \#2 performance bottleneck. Is there a way to detect
  392. modified servers, or to have them volunteer the information that they're
  393. logging verbosely? Would that actually solve any attacks?
  394. \section{Crossroads: Scaling and Design choices}
  395. \label{sec:crossroads-design}
  396. \subsection{Transporting the stream vs transporting the packets}
  397. \ref{subsec:stream-vs-packet}
  398. We periodically run into ex ZKS employees who tell us that the process of
  399. anonymizing IPs should ``obviously'' be done at the IP layer. Here are
  400. the issues that need to be resolved before we'll be ready to switch Tor
  401. over to arbitrary IP traffic.
  402. \begin{enumerate}
  403. \setlength{\itemsep}{0mm}
  404. \setlength{\parsep}{0mm}
  405. \item \emph{IP packets reveal OS characteristics.} We still need to do
  406. IP-level packet normalization, to stop things like IP fingerprinting
  407. \cite{ip-fingerprinting}. There exist libraries \cite{ip-normalizing}
  408. that can help with this.
  409. \item \emph{Application-level streams still need scrubbing.} We still need
  410. Tor to be easy to integrate with user-level application-specific proxies
  411. such as Privoxy. So it's not just a matter of capturing packets and
  412. anonymizing them at the IP layer.
  413. \item \emph{Certain protocols will still leak information.} For example,
  414. DNS requests destined for my local DNS servers need to be rewritten
  415. to be delivered to some other unlinkable DNS server. This requires
  416. understanding the protocols we are transporting.
  417. \item \emph{The crypto is unspecified.} First we need a block-level encryption
  418. approach that can provide security despite
  419. packet loss and out-of-order delivery. Freedom allegedly had one, but it was
  420. never publicly specified, and we believe it's likely vulnerable to tagging
  421. attacks \cite{tor-design}. Also, TLS over UDP is not implemented or even
  422. specified, though some early work has begun on that \cite{ben-tls-udp}.
  423. \item \emph{We'll still need to tune network parameters}. Since the above
  424. encryption system will likely need sequence numbers and maybe more to do
  425. replay detection, handle duplicate frames, etc, we will be reimplementing
  426. some subset of TCP anyway to manage throughput, congestion control, etc.
  427. \item \emph{Exit policies for arbitrary IP packets mean building a secure
  428. IDS.} Our server operators tell us that exit policies are one of
  429. the main reasons they're willing to run Tor over previous attempts
  430. at anonymizing networks. Adding an IDS to handle exit policies would
  431. increase the security complexity of Tor, and would likely not work anyway,
  432. as evidenced by the entire field of IDS and counter-IDS papers. Many
  433. potential abuse issues are resolved by the fact that Tor only transports
  434. valid TCP streams (as opposed to arbitrary IP including malformed packets
  435. and IP floods), so exit policies become even \emph{more} important as
  436. we become able to transport IP packets. We also need a way to compactly
  437. characterize the exit policies and let clients parse them to decide
  438. which nodes will allow which packets to exit.
  439. \item \emph{The Tor-internal name spaces would need to be redesigned.} We
  440. support hidden service {\tt{.onion}} addresses, and other special addresses
  441. like {\tt{.exit}} (see Section \ref{subsec:}), by intercepting the addresses
  442. when they are passed to the Tor client.
  443. \end{enumerate}
  444. This list is discouragingly long right now, but we recognize that it
  445. would be good to investigate each of these items in further depth and to
  446. understand which are actual roadblocks and which are easier to resolve
  447. than we think. We certainly wouldn't mind if Tor one day is able to
  448. transport a greater variety of protocols.
  449. \subsection{Mid-latency}
  450. \label{subsec:mid-latency}
  451. Though Tor has always been designed to be practical and usable first
  452. with as much anonymity as can be built in subject to those goals, we
  453. have contemplated that users might need resistance to at least simple
  454. traffic confirmation attacks. Raising the latency of communication
  455. slightly might make this feasible. If the latency could be kept to two
  456. or three times its current overhead, this might be acceptable to the
  457. majority of Tor users. However, it might also destroy much of the user
  458. base, and it is difficult to know in advance. Note also that in
  459. practice, as the network is growing and we accept cable modem, DSL
  460. nodes, and more nodes in various continents, we're \emph{already}
  461. looking at many-second delays for some transactions. The engineering
  462. required to get this lower is going to be extremely hard. It's worth
  463. considering how hard it would be to accept the fixed (higher) latency
  464. and improve the protection we get from it. Thus, it may be most
  465. practical to run a mid-latency option over the Tor network for those
  466. users either willing to experiment or in need of more a priori
  467. anonymity in the network. This will allow us to experiment with both
  468. the anonymity provided and the interest on the part of users.
  469. Adding a mid-latency option should not require significant fundamental
  470. change to the Tor client or server design; circuits can be labeled as
  471. low or mid latency on servers as they are set up. Low-latency traffic
  472. would be processed as now. Packets on circuits that are mid-latency
  473. would be sent in uniform size chunks at synchronized intervals. To
  474. some extent the chunking is already done because traffic moves through
  475. the network in uniform size cells, but this would occur at a courser
  476. granularity. If servers forward these chunks in roughly synchronous
  477. fashion, it will increase the similarity of data stream timing
  478. signatures. By experimenting with the granularity of data chunks and
  479. of synchronization we can attempt once again to optimize for both
  480. usability and anonymity. Unlike in \cite{sync-batch}, it may be
  481. impractical to synchronize on network batches by dropping chunks from
  482. a batch that arrive late at a given node---unless Tor moves away from
  483. stream processing to a more loss-tolerant processing of traffic (cf.\
  484. section~\ref{subsec:stream-vs-packet}). In other words, there would
  485. probably be no direct attempt to synchronize on batches of data
  486. entering the Tor network at the same time. Rather, it is the link
  487. level batching that will add noise to the traffic patterns exiting the
  488. network. Similarly, if end-to-end traffic confirmation is the
  489. concern, there is little point in mixing. It might also be feasible to
  490. pad chunks to uniform size as is done now for cells; if this is link
  491. padding rather than end-to-end, then it will take less overhead,
  492. especially in bursty environments. This is another way in which it
  493. would be fairly practical to set up a mid-latency option within the
  494. existing Tor network. Other padding regimens might supplement the
  495. mid-latency option; however, we should continue the caution with which
  496. we have always approached padding lest the overhead cost us either
  497. performance or volunteers.
  498. The distinction between traffic confirmation and traffic analysis is
  499. not as practically cut and dried as we might wish. In \cite{} it was
  500. shown that if latencies to and/or data volumes of various popular
  501. responder destinations are catalogued, it may not be necessary to
  502. observe both ends of a stream to confirm a source-destination link.
  503. These are likely to entail high variability and massive storage since
  504. routes through the network to each site will be random even if they
  505. have relatively unique latency or volume characteristics. So these do
  506. not seem an immediate practical threat. Further along similar lines, in
  507. \cite{attack-tor-oak05}, it was shown that an outside attacker can
  508. trace a stream through the Tor network while a stream is still active
  509. simply by observing the latency of his own traffic sent through
  510. various Tor nodes. These attacks are especially significant since they
  511. counter previous results that running one's own onion router protects
  512. better than using the network from the outside. The attacks do not
  513. show the client address, only the first server within the Tor network,
  514. making helper nodes all the more worthy of exploration for enclave
  515. protection. Setting up a mid-latency subnet as described above would
  516. be another significant step to evaluating resistance to such attacks.
  517. The attacks in \cite{attack-tor-oak05} are also dependent on
  518. cooperation of the responding application or the ability to modify or
  519. monitor the responder stream, in order of decreasing attack
  520. effectiveness. So, another way to counter these attacks in some cases
  521. would be to employ caching of responses. This is infeasible for
  522. application data that is not relatively static and from frequently
  523. visited sites; however, it might be useful for DNS lookups. This is
  524. also likely to be trading one practical threat for another. To be
  525. useful, such caches would need to be distributed to any likely exit
  526. nodes of recurred requests for the same data. Aside from the logistic
  527. difficulties and overhead of distribution, they constitute a collected
  528. record of destinations and/or data visited by Tor users. While
  529. limited to network insiders, given the need for wide distribution
  530. they could serve as useful data to an attacker deciding which locations
  531. to target for confirmation.
  532. [nick will work on this]
  533. \subsection{Application support: socks doesn't solve all our problems}
  534. socks4a isn't everywhere. the dns problem. etc.
  535. nick will work on this.
  536. \subsection{Measuring performance and capacity}
  537. How to measure performance without letting people selectively deny service
  538. by distinguishing pings. Heck, just how to measure performance at all. In
  539. practice people have funny firewalls that don't match up to their exit
  540. policies and Tor doesn't deal.
  541. Network investigation: Is all this bandwidth publishing thing a good idea?
  542. How can we collect stats better? Note weasel's smokeping, at
  543. http://seppia.noreply.org/cgi-bin/smokeping.cgi?target=Tor
  544. which probably gives george and steven enough info to break tor?
  545. [nick will work on this section, unless arma gets there first]
  546. \subsection{Anonymity benefits for running a server}
  547. Does running a server help you or harm you? George's Oakland attack.
  548. Plausible deniability -- without even running your traffic through Tor!
  549. But nobody knows about Tor, and the legal situation is fuzzy, so this
  550. isn't very true really.
  551. We have to pick the path length so adversary can't distinguish client from
  552. server (how many hops is good?).
  553. in practice, plausible deniability is hypothetical and doesn't seem very
  554. convincing. if ISPs find the activity antisocial, they don't care *why*
  555. your computer is doing that behavior.
  556. [arma will write this section]
  557. \subsection{Helper nodes}
  558. When does fixing your entry or exit node help you?
  559. Helper nodes in the literature don't deal with churn, and
  560. especially active attacks to induce churn.
  561. Do general DoS attacks have anonymity implications? See e.g. Adam
  562. Back's IH paper, but I think there's more to be pointed out here.
  563. Game theory for helper nodes: if Alice offers a hidden service on a
  564. server (enclave model), and nobody ever uses helper nodes, then against
  565. George+Steven's attack she's totally nailed. If only Alice uses a helper
  566. node, then she's still identified as the source of the data. If everybody
  567. uses a helper node (including Alice), then the attack identifies the
  568. helper node and also Alice, and knows which one is which. If everybody
  569. uses a helper node (but not Alice), then the attacker figures the real
  570. source was a client that is using Alice as a helper node. [How's my
  571. logic here?]
  572. point to routing-zones section re: helper nodes to defend against
  573. big stuff.
  574. [nick will write this section]
  575. \subsection{Location-hidden services}
  576. [arma will write this section]
  577. Survivable services are new in practice, yes? Hidden services seem
  578. less hidden than we'd like, since they stay in one place and get used
  579. a lot. They're the epitome of the need for helper nodes. This means
  580. that using Tor as a building block for Free Haven is going to be really
  581. hard. Also, they're brittle in terms of intersection and observation
  582. attacks. Would be nice to have hot-swap services, but hard to design.
  583. people are using hidden services as a poor man's vpn and firewall-buster.
  584. rather than playing with dyndns and trying to pierce holes in their
  585. firewall (say, so they can ssh in from the outside), they run a hidden
  586. service on the inside and then rendezvous with that hidden service
  587. externally.
  588. in practice, sites like bloggers without borders (www.b19s.org) are
  589. running tor servers but more important are advertising a hidden-service
  590. address on their front page. doing this can provide increased robustness
  591. if they used the dual-IP approach we describe in tor-design, but in
  592. practice they do it to a) increase visibility of the tor project and their
  593. support for privacy, and b) to offer a way for their users, using vanilla
  594. software, to get end-to-end encryption and end-to-end authentication to
  595. their website.
  596. \subsection{Trust and discovery}
  597. [arma will edit this and expand/retract it]
  598. The published Tor design adopted a deliberately simplistic design for
  599. authorizing new nodes and informing clients about servers and their status.
  600. In the early Tor designs, all ORs periodically uploaded a signed description
  601. of their locations, keys, and capabilities to each of several well-known {\it
  602. directory servers}. These directory servers constructed a signed summary
  603. of all known ORs (a ``directory''), and a signed statement of which ORs they
  604. believed to be operational at any given time (a ``network status''). Clients
  605. periodically downloaded a directory in order to learn the latest ORs and
  606. keys, and more frequently downloaded a network status to learn which ORs are
  607. likely to be running. ORs also operate as directory caches, in order to
  608. lighten the bandwidth on the authoritative directory servers.
  609. In order to prevent Sybil attacks (wherein an adversary signs up many
  610. purportedly independent servers in order to increase her chances of observing
  611. a stream as it enters and leaves the network), the early Tor directory design
  612. required the operators of the authoritative directory servers to manually
  613. approve new ORs. Unapproved ORs were included in the directory, but clients
  614. did not use them at the start or end of their circuits. In practice,
  615. directory administrators performed little actual verification, and tended to
  616. approve any OR whose operator could compose a coherent email. This procedure
  617. may have prevented trivial automated Sybil attacks, but would do little
  618. against a clever attacker.
  619. There are a number of flaws in this system that need to be addressed as we
  620. move forward. They include:
  621. \begin{tightlist}
  622. \item Each directory server represents an independent point of failure; if
  623. any one were compromised, it could immediately compromise all of its users
  624. by recommending only compromised ORs.
  625. \item The more servers appear join the network, the more unreasonable it
  626. becomes to expect clients to know about them all. Directories
  627. become unfeasibly large, and downloading the list of servers becomes
  628. burdonsome.
  629. \item The validation scheme may do as much harm as it does good. It is not
  630. only incapable of preventing clever attackers from mounting Sybil attacks,
  631. but may deter server operators from joining the network. (For instance, if
  632. they expect the validation process to be difficult, or if they do not share
  633. any languages in common with the directory server operators.)
  634. \end{tightlist}
  635. We could try to move the system in several directions, depending on our
  636. choice of threat model and requirements. If we did not need to increase
  637. network capacity in order to support more users, there would be no reason not
  638. to adopt even stricter validation requirements, and reduce the number of
  639. servers in the network to a trusted minimum. But since we want Tor to work
  640. for as many users as it can, we need XXXXX
  641. In order to address the first two issues, it seems wise to move to a system
  642. including a number of semi-trusted directory servers, no one of which can
  643. compromise a user on its own. Ultimately, of course, we cannot escape the
  644. problem of a first introducer: since most users will run Tor in whatever
  645. configuration the software ships with, the Tor distribution itself will
  646. remain a potential single point of failure so long as it includes the seed
  647. keys for directory servers, a list of directory servers, or any other means
  648. to learn which servers are on the network. But omitting this information
  649. from the Tor distribution would only delegate the trust problem to the
  650. individual users, most of whom are presumably less informed about how to make
  651. trust decisions than the Tor developers.
  652. %Network discovery, sybil, node admission, scaling. It seems that the code
  653. %will ship with something and that's our trust root. We could try to get
  654. %people to build a web of trust, but no. Where we go from here depends
  655. %on what threats we have in mind. Really decentralized if your threat is
  656. %RIAA; less so if threat is to application data or individuals or...
  657. \section{Crossroads: Scaling}
  658. %\label{sec:crossroads-scaling}
  659. %P2P + anonymity issues:
  660. Tor is running today with hundreds of servers and tens of thousands of
  661. users, but it will certainly not scale to millions.
  662. Scaling Tor involves three main challenges. First is safe server
  663. discovery, both bootstrapping -- how a Tor client can robustly find an
  664. initial server list -- and ongoing -- how a Tor client can learn about
  665. a fair sample of honest servers and not let the adversary control his
  666. circuits (see Section x). Second is detecting and handling the speed
  667. and reliability of the variety of servers we must use if we want to
  668. accept many servers (see Section y).
  669. Since the speed and reliability of a circuit is limited by its worst link,
  670. we must learn to track and predict performance. Finally, in order to get
  671. a large set of servers in the first place, we must address incentives
  672. for users to carry traffic for others (see Section incentives).
  673. \subsection{Incentives by Design}
  674. [nick will try to make this section shorter and more to the point.]
  675. [most of the technical incentive schemes in the literature introduce
  676. anonymity issues which we don't understand yet, and we seem to be doing
  677. ok without them]
  678. There are three behaviors we need to encourage for each server: relaying
  679. traffic; providing good throughput and reliability while doing it;
  680. and allowing traffic to exit the network from that server.
  681. We encourage these behaviors through \emph{indirect} incentives, that
  682. is, designing the system and educating users in such a way that users
  683. with certain goals will choose to relay traffic. In practice, the
  684. main incentive for running a Tor server is social benefit: volunteers
  685. altruistically donate their bandwidth and time. We also keep public
  686. rankings of the throughput and reliability of servers, much like
  687. seti@home. We further explain to users that they can get \emph{better
  688. security} by operating a server, because they get plausible deniability
  689. (indeed, they may not need to route their own traffic through Tor at all
  690. -- blending directly with other traffic exiting Tor may be sufficient
  691. protection for them), and because they can use their own Tor server
  692. as entry or exit point and be confident it's not run by the adversary.
  693. Finally, we can improve the usability and feature set of the software:
  694. rate limiting support and easy packaging decrease the hassle of
  695. maintaining a server, and our configurable exit policies allow each
  696. operator to advertise a policy describing the hosts and ports to which
  697. he feels comfortable connecting.
  698. Beyond these, however, there is also a need for \emph{direct} incentives:
  699. providing payment or other resources in return for high-quality service.
  700. Paying actual money is problematic: decentralized e-cash systems are
  701. not yet practical, and a centralized collection system not only reduces
  702. robustness, but also has failed in the past (the history of commercial
  703. anonymizing networks is littered with failed attempts). A more promising
  704. option is to use a tit-for-tat incentive scheme: provide better service
  705. to nodes that have provided good service to you.
  706. Unfortunately, such an approach introduces new anonymity problems.
  707. Does the incentive system enable the adversary to attract more traffic by
  708. performing well? Typically a user who chooses evenly from all options is
  709. most resistant to an adversary targetting him, but that approach prevents
  710. us from handling heterogeneous servers \cite{casc-rep}.
  711. When a server (call him Steve) performs well for Alice, does Steve gain
  712. reputation with the entire system, or just with Alice? If the entire
  713. system, how does Alice tell everybody about her experience in a way that
  714. prevents her from lying about it yet still protects her identity? If
  715. Steve's behavior only affects Alice's behavior, does this allow Steve to
  716. selectively perform only for Alice, and then break her anonymity later
  717. when somebody (presumably Alice) routes through his node?
  718. These are difficult and open questions, yet choosing not to scale means
  719. leaving most users to a less secure network or no anonymizing network
  720. at all. We will start with a simplified approach to the tit-for-tat
  721. incentive scheme based on two rules: (1) each node should measure the
  722. service it receives from adjacent nodes, and provide service relative to
  723. the received service, but (2) when a node is making decisions that affect
  724. its own security (e.g. when building a circuit for its own application
  725. connections), it should choose evenly from a sufficiently large set of
  726. nodes that meet some minimum service threshold. This approach allows us
  727. to discourage bad service without opening Alice up as much to attacks.
  728. %XXX rewrite the above so it sounds less like a grant proposal and
  729. %more like a "if somebody were to try to solve this, maybe this is a
  730. %good first step".
  731. %We should implement the above incentive scheme in the
  732. %deployed Tor network, in conjunction with our plans to add the necessary
  733. %associated scalability mechanisms. We will do experiments (simulated
  734. %and/or real) to determine how much the incentive system improves
  735. %efficiency over baseline, and also to determine how far we are from
  736. %optimal efficiency (what we could get if we ignored the anonymity goals).
  737. \subsection{Peer-to-peer / practical issues}
  738. [leave this section for now, and make sure things here are covered
  739. elsewhere. then remove it.]
  740. Making use of servers with little bandwidth. How to handle hammering by
  741. certain applications.
  742. Handling servers that are far away from the rest of the network, e.g. on
  743. the continents that aren't North America and Europe. High latency,
  744. often high packet loss.
  745. Running Tor servers behind NATs, behind great-firewalls-of-China, etc.
  746. Restricted routes. How to propagate to everybody the topology? BGP
  747. style doesn't work because we don't want just *one* path. Point to
  748. Geoff's stuff.
  749. \subsection{Location diversity and ISP-class adversaries}
  750. Anonymity networks have long relied on diversity of node location for
  751. protection against attacks---typically an adversary who can observe a
  752. larger fraction of the network can launch a more effective attack. One
  753. way to achieve dispersal involves growing the network so a given adversary
  754. sees less. Alternately, we can arrange the topology so traffic can enter
  755. or exit at many places (for example, by using a free-route network
  756. like Tor rather than a cascade network like JAP). Lastly, we can use
  757. distributed trust to spread each transaction over multiple jurisdictions.
  758. But how do we decide whether two nodes are in related locations?
  759. Feamster and Dingledine defined a \emph{location diversity} metric
  760. in \cite{routing-zones}, and began investigating a variant of location
  761. diversity based on the fact that the Internet is divided into thousands of
  762. independently operated networks called {\em autonomous systems} (ASes).
  763. The key insight from this paper is that while we typically think of a
  764. connection as going directly from the Tor client to her first Tor node,
  765. actually it traverses many different ASes on each hop. An adversary at
  766. any of these ASes can monitor or influence traffic. Specifically, given
  767. plausible initiators and recipients and path random path selection,
  768. some ASes in the simulation were able to observe 10\% to 30\% of the
  769. transactions (that is, learn both the origin and the destination) on
  770. the deployed Tor network (33 nodes as of June 2004).
  771. The paper concludes that for best protection against the AS-level
  772. adversary, nodes should be in ASes that have the most links to other ASes:
  773. Tier-1 ISPs such as AT\&T and Abovenet. Further, a given transaction
  774. is safest when it starts or ends in a Tier-1 ISP. Therefore, assuming
  775. initiator and responder are both in the U.S., it actually \emph{hurts}
  776. our location diversity to add far-flung nodes in continents like Asia
  777. or South America.
  778. Many open questions remain. First, it will be an immense engineering
  779. challenge to get an entire BGP routing table to each Tor client, or at
  780. least summarize it sufficiently. Without a local copy, clients won't be
  781. able to safely predict what ASes will be traversed on the various paths
  782. through the Tor network to the final destination. Tarzan~\cite{tarzan}
  783. and MorphMix~\cite{morphmix} suggest that we compare IP prefixes to
  784. determine location diversity; but the above paper showed that in practice
  785. many of the Mixmaster nodes that share a single AS have entirely different
  786. IP prefixes. When the network has scaled to thousands of nodes, does IP
  787. prefix comparison become a more useful approximation?
  788. %
  789. Second, can take advantage of caching certain content at the exit nodes, to
  790. limit the number of requests that need to leave the network at all.
  791. what about taking advantage of caches like akamai's or googles? what
  792. about treating them as adversaries?
  793. %
  794. Third, if we follow the paper's recommendations and tailor path selection
  795. to avoid choosing endpoints in similar locations, how much are we hurting
  796. anonymity against larger real-world adversaries who can take advantage
  797. of knowing our algorithm?
  798. %
  799. Lastly, can we use this knowledge to figure out which gaps in our network
  800. would most improve our robustness to this class of attack, and go recruit
  801. new servers with those ASes in mind?
  802. Tor's security relies in large part on the dispersal properties of its
  803. network. We need to be more aware of the anonymity properties of various
  804. approaches we can make better design decisions in the future.
  805. \subsection{The China problem}
  806. Citizens in a variety of countries, such as most recently China and
  807. Iran, are periodically blocked from accessing various sites outside
  808. their country. These users try to find any tools available to allow
  809. them to get-around these firewalls. Some anonymity networks, such as
  810. Six-Four~\cite{six-four}, are designed specifically with this goal in
  811. mind; others like the Anonymizer~\cite{anonymizer} are paid by sponsors
  812. such as Voice of America to set up a network to encourage `Internet
  813. freedom'~\cite{voice-of-america-anonymizer}. Even though Tor wasn't
  814. designed with ubiquitous access to the network in mind, thousands of
  815. users across the world are trying to use it for exactly this purpose.
  816. % Academic and NGO organizations, peacefire, \cite{berkman}, etc
  817. Anti-censorship networks hoping to bridge country-level blocks face
  818. a variety of challenges. One of these is that they need to find enough
  819. exit nodes---servers on the `free' side that are willing to relay
  820. arbitrary traffic from users to their final destinations. Anonymizing
  821. networks including Tor are well-suited to this task, since we have
  822. already gathered a set of exit nodes that are willing to tolerate some
  823. political heat.
  824. The other main challenge is to distribute a list of reachable relays
  825. to the users inside the country, and give them software to use them,
  826. without letting the authorities also enumerate this list and block each
  827. relay. Anonymizer solves this by buying lots of seemingly-unrelated IP
  828. addresses (or having them donated), abandoning old addresses as they are
  829. `used up', and telling a few users about the new ones. Distributed
  830. anonymizing networks again have an advantage here, in that we already
  831. have tens of thousands of separate IP addresses whose users might
  832. volunteer to provide this service since they've already installed and use
  833. the software for their own privacy~\cite{koepsell-wpes2004}. Because
  834. the Tor protocol separates routing from network discovery (see Section
  835. \ref{do-we-discuss-this?}), volunteers could configure their Tor clients
  836. to generate server descriptors and send them to a special directory
  837. server that gives them out to dissidents who need to get around blocks.
  838. Of course, this still doesn't prevent the adversary
  839. from enumerating all the volunteer relays and blocking them preemptively.
  840. Perhaps a tiered-trust system could be built where a few individuals are
  841. given relays' locations, and they recommend other individuals by telling them
  842. those addresses, thus providing a built-in incentive to avoid letting the
  843. adversary intercept them. Max-flow trust algorithms~\cite{advogato}
  844. might help to bound the number of IP addresses leaked to the adversary. Groups
  845. like the W3C are looking into using Tor as a component in an overall system to
  846. help address censorship; we wish them luck.
  847. %\cite{infranet}
  848. \subsection{Non-clique topologies}
  849. [nick will try to shrink this section]
  850. Because of its threat model that is substantially weaker than high
  851. latency mixnets, Tor is actually in a potentially better position to
  852. scale at least initially. From the perspective of a mix network, one
  853. of the worst things that can happen is partitioning. The more
  854. potential senders of messages entering the network the better the
  855. anonymity. Roughly, if a network is, e.g., split in half, then your
  856. anonymity is cut in half. Attacks become half as hard (if they're
  857. linear in network size), etc. In some sense this is still true for
  858. Tor: if you want to know who Alice is talking to, you can watch her
  859. for one end of a circuit. For a half size network, you then only have
  860. to brute force examine half as many nodes to find the other end. But
  861. Tor is not meant to cope with someone directly attacking many dozens
  862. of nodes in a few minutes. It was meant to cope with traffic
  863. confirmation attacks. And, these are independent of the size of the
  864. network. So, a simple possibility when the scale of a Tor network
  865. exceeds some size is to simply split it. Care could be taken in
  866. allocating which nodes go to which network along the lines of
  867. \cite{casc-rep} to insure that collaborating hostile nodes are not
  868. able to gain any advantage in network splitting that they do not
  869. already have in joining a network.
  870. The attacks in \cite{attack-tor-oak05} show that certain types of
  871. brute force attacks are in fact feasible; however they make the
  872. above point stronger not weaker. The attacks do not appear to be
  873. significantly more difficult to mount against a network that is
  874. twice the size. Also, they only identify the Tor nodes used in a
  875. circuit, not the client. Finally note that even if the network is split,
  876. a client does not need to use just one of the two resulting networks.
  877. Alice could use either of them, and it would not be difficult to make
  878. the Tor client able to access several such network on a per circuit
  879. basis. More analysis is needed; we simply note here that splitting
  880. a Tor network is an easy way to achieve moderate scalability and that
  881. it does not necessarily have the same implications as splitting a mixnet.
  882. Alternatively, we can try to scale a single network. Some issues for
  883. scaling include how many neighbors can nodes support and how many
  884. users (and how much application traffic capacity) can the network
  885. handle for each new node that comes into the network. This depends on
  886. many things, most notably the traffic capacity of the new nodes. We
  887. can observe, however, that adding a tor node of any feasible bandwidth
  888. will increase the traffic capacity of the network. This means that, as
  889. a first step to scaling, we can focus on the interconnectivity of the
  890. nodes, followed by directories, discovery, etc.
  891. By reducing the connectivity of the network we increase the total
  892. number of nodes that the network can contain. Anonymity implications
  893. of restricted routes for mix networks have already been explored by
  894. Danezis~\cite{danezis-pets03}. That paper explicitly considered only
  895. traffic analysis resistance provided by a mix network and sidestepped
  896. questions of traffic confirmation resistance. But, Tor is designed
  897. only to resist traffic confirmation. For this and other reasons, we
  898. cannot simply adopt his mixnet results to onion routing networks. If
  899. an attacker gains minimal increase in the likelyhood of compromising
  900. the endpoints of a Tor circuit through a sparse network (vs.\ a clique
  901. on the same node set), then the restriction will have had minimal
  902. impact on the anonymity provided by that network.
  903. The approach Danezis describes is based on expander graphs, i.e.,
  904. graphs in which any subgraph of nodes is likely to have lots of nodes
  905. as neighbors. For Tor, we may not need to have an expander per se, it
  906. may be enough to have a single subnet that is highly connected. As an
  907. example, assume fifty nodes of relatively high traffic capacity. This
  908. \emph{center} forms are a clique. Assume each center node can each
  909. handle 200 connections to other nodes (including the other ones in the
  910. center). Assume every noncenter node connects to three nodes in the
  911. center and anyone out of the center that they want to. Then the
  912. network easily scales to c. 2500 nodes with commensurate increase in
  913. bandwidth. There are many open questions: how directory information
  914. is distributed (presumably information about the center nodes could
  915. be given to any new nodes with their codebase), whether center nodes
  916. will need to function as a `backbone', etc. As above the point is
  917. that this would create problems for the expected anonymity for a mixnet,
  918. but for an onion routing network where anonymity derives largely from
  919. the edges, it may be feasible.
  920. Another point is that we already have a non-clique topology.
  921. Individuals can set up and run Tor nodes without informing the
  922. directory servers. This will allow, e.g., dissident groups to run a
  923. local Tor network of such nodes that connects to the public Tor
  924. network. This network is hidden behind the Tor network and its
  925. only visible connection to Tor at those points where it connects.
  926. As far as the public network is concerned or anyone observing it,
  927. they are running clients.
  928. \section{The Future}
  929. \label{sec:conclusion}
  930. we should put random thoughts here until there are enough for a
  931. conclusion.
  932. will our sustainability approach work? we'll see.
  933. "These are difficult and open questions, yet choosing not to solve them
  934. means leaving most users to a less secure network or no anonymizing
  935. network at all."
  936. \bibliographystyle{plain} \bibliography{tor-design}
  937. \appendix
  938. \begin{figure}[t]
  939. %\unitlength=1in
  940. \centering
  941. %\begin{picture}(6.0,2.0)
  942. %\put(3,1){\makebox(0,0)[c]{\epsfig{figure=graphnodes,width=6in}}}
  943. %\end{picture}
  944. \mbox{\epsfig{figure=graphnodes,width=5in}}
  945. \caption{Number of servers over time. Lowest line is number of exit
  946. nodes that allow connections to port 80. Middle line is total number of
  947. verified (registered) servers. The line above that represents servers
  948. that are not yet registered.}
  949. \label{fig:graphnodes}
  950. \end{figure}
  951. \begin{figure}[t]
  952. \centering
  953. \mbox{\epsfig{figure=graphtraffic,width=5in}}
  954. \caption{The sum of traffic reported by each server over time. The bottom
  955. pair show average throughput, and the top pair represent the largest 15
  956. minute burst in each 4 hour period.}
  957. \label{fig:graphtraffic}
  958. \end{figure}
  959. \end{document}