tor-design.tex 53 KB

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  34. \title{Tor: Design of a Second-Generation Onion Router}
  35. %\author{Roger Dingledine \\ The Free Haven Project \\ arma@freehaven.net \and
  36. %Nick Mathewson \\ The Free Haven Project \\ nickm@freehaven.net \and
  37. %Paul Syverson \\ Naval Research Lab \\ syverson@itd.nrl.navy.mil}
  38. \maketitle
  39. \thispagestyle{empty}
  40. \begin{abstract}
  41. We present Tor, a connection-based low-latency anonymous communication
  42. system. It is intended as a successor to Onion Routing
  43. and addresses many limitations in the original Onion Routing design.
  44. Tor works in a real-world Internet environment,
  45. requires little synchronization or coordination between nodes, and
  46. protects against known anonymity-breaking attacks as well
  47. as or better than other systems with similar design parameters.
  48. \end{abstract}
  49. %\begin{center}
  50. %\textbf{Keywords:} anonymity, peer-to-peer, remailer, nymserver, reply block
  51. %\end{center}
  52. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  53. \Section{Overview}
  54. \label{sec:intro}
  55. Onion Routing is a distributed overlay network designed to anonymize
  56. low-latency TCP-based applications such as web browsing, secure shell,
  57. and instant messaging. Clients choose a path through the network and
  58. build a \emph{virtual circuit}, in which each node in the path knows its
  59. predecessor and successor, but no others. Traffic flowing down the circuit
  60. is sent in fixed-size \emph{cells}, which are unwrapped by a symmetric key
  61. at each node and relayed downstream. The original Onion Routing
  62. project published several design and analysis papers
  63. \cite{or-jsac98,or-discex00,or-ih96,or-pet00}. While there was briefly
  64. a wide area Onion Routing network,
  65. % how long is briefly? a day, a month? -RD
  66. the only long-running and publicly accessible
  67. implementation was a fragile proof-of-concept that ran on a single
  68. machine. Many critical design and deployment issues were never implemented,
  69. and the design has not been updated in several years.
  70. Here we describe Tor, a protocol for asynchronous, loosely
  71. federated onion routers that provides the following improvements over
  72. the old Onion Routing design, and over other low-latency anonymity systems:
  73. \begin{tightlist}
  74. \item \textbf{Perfect forward secrecy:} The original Onion Routing
  75. design is vulnerable to a single hostile node recording traffic and later
  76. compromising successive nodes in the circuit and forcing them to
  77. decrypt it.
  78. Rather than using
  79. onions to lay the circuits, Tor uses an incremental or \emph{telescoping}
  80. path-building design, where the initiator negotiates session keys with
  81. each successive hop in the circuit. Onion replay detection is no longer
  82. necessary, and the process of building circuits is more reliable, since
  83. the initiator knows when a hop fails and can then try extending to a new node.
  84. \item \textbf{Separation of protocol cleaning from anonymity:}
  85. The original Onion Routing design required a separate ``application
  86. proxy'' for each
  87. supported application protocol, resulting in a lot of extra code --- most
  88. of which was never written, so most applications were not supported.
  89. Tor uses the unified and standard Socks
  90. \cite{socks4,socks5} proxy interface, allowing us to support most TCP-based
  91. programs without modification. This design change allows Tor to
  92. use the protocol-normalization features of privacy-enhancing
  93. application-level proxies such as Privoxy without having to
  94. incorporate those features itself.
  95. \item \textbf{Many TCP streams can share one circuit:} The original
  96. Onion Routing design built one circuit for each application-level
  97. request.
  98. Aside from the performance issues of doing multiple public key
  99. operations for every request, building a circuit for each request can
  100. endanger anonymity.
  101. The very first Onion Routing design \cite{or-ih96} protected against
  102. this to some extent by hiding network access behind an onion
  103. router/firewall that was also forwarding traffic from other nodes.
  104. However, even if this meant complete protection, many users can
  105. benefit from Onion Routing for which neither running one's own node
  106. nor such firewall configurations are adequately convenient to be
  107. feasible. Those users, especially if they engage in certain unusual
  108. communication behaviors, may be identifiable \cite{wright03}. To
  109. complicate the possibility of such attacks Tor multiplexes many
  110. stream down each circuit, but still rotates the circuit
  111. periodically to avoid too much linkability from requests on a single
  112. circuit.
  113. \item \textbf{No mixing, padding, or traffic shaping:}
  114. The original Onion Routing
  115. design called for full link padding both between onion routers and between
  116. onion proxies (that is, users) and onion routers \cite{or-jsac98}. The
  117. later analysis paper \cite{or-pet00} suggested \emph{traffic shaping}
  118. to provide similar protection but use less bandwidth, but did not go
  119. into detail. However, recent research \cite{econymics} and deployment
  120. experience \cite{freedom21-security} suggest that this level of resource
  121. use is not practical or economical; and even full link padding is still
  122. vulnerable to active attacks \cite{defensive-dropping}.
  123. %[An upcoming FC04 paper. I'll add a cite when it's out. -RD]
  124. \item \textbf{Leaky-pipe circuit topology:} Through in-band
  125. signalling within the
  126. circuit, Tor initiators can direct traffic to nodes partway down the
  127. circuit. This allows for long-range padding to frustrate traffic
  128. shape and volume attacks at the initiator \cite{defensive-dropping},
  129. but because circuits are used by more than one application, it also
  130. allows traffic to exit the circuit from the middle -- thus
  131. frustrating traffic shape and volume attacks based on observing exit
  132. points.
  133. %Or something like that. hm. Tone this down maybe? Or support it. -RD
  134. %How's that? -PS
  135. \item \textbf{Congestion control:} Earlier anonymity designs do not
  136. address traffic bottlenecks. Unfortunately, typical approaches to load
  137. balancing and flow control in overlay networks involve inter-node control
  138. communication and global views of traffic. Our decentralized ack-based
  139. congestion control maintains reasonable anonymity while allowing nodes
  140. at the edges of the network to detect congestion or flooding attacks
  141. and send less data until the congestion subsides.
  142. \item \textbf{Directory servers:} Rather than attempting to flood
  143. link-state information through the network, which can be unreliable and
  144. open to partitioning attacks or outright deception, Tor takes a simplified
  145. view towards distributing link-state information. Certain more trusted
  146. onion routers also serve as directory servers; they provide signed
  147. \emph{directories} describing all routers they know about, and which
  148. are currently up. Users periodically download these directories via HTTP.
  149. \item \textbf{End-to-end integrity checking:} Without integrity checking
  150. on traffic going through the network, any onion router on the path
  151. can change the contents of cells as they pass by, e.g. to redirect a
  152. connection on the fly so it connects to a different webserver, or to
  153. tag encrypted traffic and look for the tagged traffic at the network
  154. edges \cite{minion-design}.
  155. \item \textbf{Robustness to failed nodes:} A failed node in a traditional
  156. mix network means lost messages, but thanks to Tor's step-by-step
  157. circuit building, users can notice failed
  158. nodes while building circuits and route around them. Additionally,
  159. liveness information from directories allows users to avoid
  160. unreliable node in the first place.
  161. %We further provide a
  162. %simple mechanism that allows connections to be established despite recent
  163. %node failure or slightly dated information from a directory server. Tor
  164. %permits onion routers to have \emph{router twins} --- nodes that share
  165. %the same private decryption key. Note that because connections now have
  166. %perfect forward secrecy, an onion router still cannot read the traffic
  167. %on a connection established through its twin even while that connection
  168. %is active. Also, which nodes are twins can change dynamically depending
  169. %on current circumstances, and twins may or may not be under the same
  170. %administrative authority.
  171. %
  172. %[Commented out; Router twins provide no real increase in robustness
  173. %to failed nodes. If a non-twinned node goes down, the
  174. %circuit-builder notices this and routes around it. Circuit-building
  175. %is offline, so there shouldn't even be a latency hit. -NM]
  176. \item \textbf{Variable exit policies:} Tor provides a consistent
  177. mechanism for
  178. each node to specify and advertise a policy describing the hosts and
  179. ports to which it will connect. These exit policies
  180. are critical in a volunteer-based distributed infrastructure, because
  181. each operator is comfortable with allowing different types of traffic
  182. to exit the Tor network from his node.
  183. \item \textbf{Implementable in user-space}.
  184. \item \textbf{Rendezvous points and location-protected servers:} Tor
  185. provides an integrated mechanism for responder-anonymity
  186. location-protected servers. [XXX say more.]
  187. [XXX Mention that reply onions are out because they're brittle don't give PFS.]
  188. \end{tightlist}
  189. [XXX carefully mention implementation, emphasizing that experience
  190. deploying isn't there yet, and not all features are implemented.
  191. Mention that it runs, is kinda alpha, kinda deployed, runs on win32.]
  192. We review previous work in Section \ref{sec:background}, describe
  193. our goals and assumptions in Section \ref{sec:assumptions},
  194. and then address the above list of improvements in Sections
  195. \ref{sec:design}-\ref{sec:maintaining-anonymity}. We then summarize
  196. how our design stands up to known attacks, and conclude with a list of
  197. open problems.
  198. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  199. \Section{Background and threat model}
  200. \label{sec:background}
  201. \SubSection{Related work}
  202. \label{sec:related-work}
  203. Modern anonymity designs date to Chaum's Mix-Net\cite{chaum-mix} design of
  204. 1981. Chaum proposed hiding sender-recipient connections by wrapping
  205. messages in several layers of public key cryptography, and relaying them
  206. through a path composed of Mix servers. Mix servers in turn decrypt, delay,
  207. and re-order messages, before relay them along the path towards their
  208. destinations.
  209. Subsequent relay-based anonymity designs have diverged in two
  210. principal directions. Some have attempted to maximize anonymity at
  211. the cost of introducing comparatively large and variable latencies,
  212. for example, Babel\cite{babel}, Mixmaster\cite{mixmaster-spec}, and
  213. Mixminion\cite{minion-design}. Because of this
  214. decision, such \emph{high-latency} networks are well-suited for anonymous
  215. email, but introduce too much lag for interactive tasks such as web browsing,
  216. internet chat, or SSH connections.
  217. Tor belongs to the second category: \emph{low-latency} designs that
  218. attempt to anonymize interactive network traffic. Because such
  219. traffic tends to involve a relatively large numbers of packets, it is
  220. difficult to prevent an attacker who can eavesdrop entry and exit
  221. points from correlating packets entering the anonymity network with
  222. packets leaving it. Although some work has been done to frustrate
  223. these attacks, most designs protect primarily against traffic analysis
  224. rather than traffic confirmation \cite{or-jsac98}. One can pad and
  225. limit communication to a constant rate or at least to control the
  226. variation in traffic shape. This can have prohibitive bandwidth costs
  227. and/or performance limitations. One can also use a cascade (fixed
  228. shared route) with a relatively fixed set of users. This assumes a
  229. significant degree of agreement and provides an easier target for an active
  230. attacker since the endpoints are generally known. However, a practical
  231. network with both of these features and thousands of active users has
  232. been run for many years (the Java Anon Proxy, aka Web MIXes,
  233. \cite{web-mix}).
  234. Another low latency design that was proposed independently and at
  235. about the same time as Onion Routing was PipeNet \cite{pipenet}.
  236. This provided anonymity protections that were stronger than Onion Routing's,
  237. but at the cost of allowing a single user to shut down the network simply
  238. by not sending. It was also never implemented or formally published.
  239. The simplest low-latency designs are single-hop proxies such as the
  240. Anonymizer \cite{anonymizer}, wherein a single trusted server removes
  241. identifying users' data before relaying it. These designs are easy to
  242. analyze, but require end-users to trust the anonymizing proxy.
  243. More complex are distributed-trust, channel-based anonymizing systems. In
  244. these designs, a user establishes one or more medium-term bidirectional
  245. end-to-end tunnels to exit servers, and uses those tunnels to deliver a
  246. number of low-latency packets to and from one or more destinations per
  247. tunnel. Establishing tunnels is comparatively expensive and typically
  248. requires public-key cryptography, whereas relaying packets along a tunnel is
  249. comparatively inexpensive. Because a tunnel crosses several servers, no
  250. single server can learn the user's communication partners.
  251. Systems such as earlier versions of Freedom and Onion Routing
  252. build the anonymous channel all at once (using an onion). Later
  253. designs of Freedom and Onion Routing as described herein build
  254. the channel in stages as does AnonNet
  255. \cite{anonnet}. Amongst other things, this makes perfect forward
  256. secrecy feasible.
  257. Some systems, such as Crowds \cite{crowds-tissec}, do not rely on the
  258. changing appearance of packets to hide the path; rather they employ
  259. mechanisms so that an intermediary cannot be sure when it is
  260. receiving from/sending to the ultimate initiator. There is no public-key
  261. encryption needed for Crowds, but the responder and all data are
  262. visible to all nodes on the path so that anonymity of connection
  263. initiator depends on filtering all identifying information from the
  264. data stream. Crowds is also designed only for HTTP traffic.
  265. Hordes \cite{hordes-jcs} is based on Crowds but also uses multicast
  266. responses to hide the initiator. Herbivore \cite{herbivore} and
  267. P5 \cite{p5} go even further requiring broadcast.
  268. They each use broadcast in very different ways, and tradeoffs are made to
  269. make broadcast more practical. Both Herbivore and P5 are designed primarily
  270. for communication between communicating peers, although Herbivore
  271. permits external connections by requesting a peer to serve as a proxy.
  272. Allowing easy connections to nonparticipating responders or recipients
  273. is a practical requirement for many users, e.g., to visit
  274. nonparticipating Web sites or to exchange mail with nonparticipating
  275. recipients.
  276. Distributed-trust anonymizing systems differ in how they prevent attackers
  277. from controlling too many servers and thus compromising too many user paths.
  278. Some protocols rely on a centrally maintained set of well-known anonymizing
  279. servers. Current Tor design falls into this category.
  280. Others (such as Tarzan and MorphMix) allow unknown users to run
  281. servers, while using a limited resource (DHT space for Tarzan; IP space for
  282. MorphMix) to prevent an attacker from owning too much of the network.
  283. Crowds uses a centralized ``blender'' to enforce Crowd membership
  284. policy. For small crowds it is suggested that familiarity with all
  285. members is adequate. For large diverse crowds, limiting accounts in
  286. control of any one party is more difficult:
  287. ``(e.g., the blender administrator sets up an account for a user only
  288. after receiving a written, notarized request from that user) and each
  289. account to one jondo, and by monitoring and limiting the number of
  290. jondos on any one net- work (using IP address), the attacker would be
  291. forced to launch jondos using many different identities and on many
  292. different networks to succeed'' \cite{crowds-tissec}.
  293. Tor is not primarily designed for censorship resistance but rather
  294. for anonymous communication. However, Tor's rendezvous points, which
  295. enable connections between mutually anonymous entities, also
  296. facilitate connections to hidden servers. These building blocks to
  297. censorship resistance and other capabilities are described in
  298. Section~\ref{sec:rendezvous}. Location-hidden servers are an
  299. essential component for anonymous publishing systems such as
  300. Publius\cite{publius}, Free Haven\cite{freehaven-berk}, and
  301. Tangler\cite{tangler}.
  302. [XXX I'm considering the subsection as ended here for now. I'm leaving the
  303. following notes in case we want to revisit any of them. -PS]
  304. Channel-based anonymizing systems also differ in their use of dummy traffic.
  305. [XXX]
  306. Finally, several systems provide low-latency anonymity without channel-based
  307. communication. Crowds and [XXX] provide anonymity for HTTP requests; [...]
  308. [XXX Mention error recovery?]
  309. STILL NOT MENTIONED:
  310. isdn-mixes\\
  311. real-time mixes\\
  312. rewebbers\\
  313. cebolla\\
  314. [XXX Close by mentioning where Tor fits.]
  315. \Section{Design goals and assumptions}
  316. \label{sec:assumptions}
  317. \subsection{Goals}
  318. % Are these really our goals? ;) -NM
  319. Like other low-latency anonymity designs, Tor seeks to frustrate
  320. attackers from linking communication partners, or from linking
  321. multiple communications to or from a single point. Within this
  322. main goal, however, several design considerations have directed
  323. Tor's evolution.
  324. First, we have tried to build a {\bf deployable} system. [XXX why?]
  325. This requirement precludes designs that are expensive to run (for
  326. example, by requiring more bandwidth than volunteers will easily
  327. provide); designs that place a heavy liability burden on operators
  328. (for example, by allowing attackers to implicate operators in illegal
  329. activities); and designs that are difficult or expensive to implement
  330. (for example, by requiring kernel patches to many operating systems,
  331. or ). [Only anon people need to run special software! Look at minion
  332. reviews]
  333. Second, the system must be {\bf usable}. A hard-to-use system has
  334. fewer users --- and because anonymity systems hide users among users, a
  335. system with fewer users provides less anonymity. Thus, usability is
  336. not only a convenience, but is a security requirement for anonymity
  337. systems.
  338. Third, the protocol must be {\bf extensible}, so that it can serve as
  339. a test-bed for future research in low-latency anonymity systems.
  340. (Note that while an extensible protocol benefits researchers, there is
  341. a danger that differing choices of extensions will render users
  342. distinguishable. Thus, implementations should not permit different
  343. protocol extensions to coexist in a single deployed network.)
  344. The protocol's design and security parameters must be {\bf
  345. conservative}. Additional features impose implementation and
  346. complexity costs. [XXX Say that we don't want to try to come up with
  347. speculative solutions to problems we don't KNOW how to solve? -NM]
  348. [XXX mention something about robustness? But we really aren't that
  349. robust. We just assume that tunneled protocols tolerate connection
  350. loss. -NM]
  351. \subsection{Non-goals}
  352. In favoring conservative, deployable designs, we have explicitly
  353. deferred a number of goals --- not because they are not desirable in
  354. anonymity systems --- but because solving them is either solved
  355. elsewhere, or an area of active research without a generally accepted
  356. solution.
  357. Unlike Tarzan or Morphmix, Tor does not attempt to scale to completely
  358. decentralized peer-to-peer environments with thousands of short-lived
  359. servers.
  360. Tor does not claim to provide a definitive solution to end-to-end
  361. timing or intersection attacks for users who do not run their own
  362. Onion Routers.
  363. % Does that mean we do claim to solve intersection attack for
  364. % the enclave-firewall model? -RD
  365. Tor does not provide \emph{protocol normalization} like the Anonymizer or
  366. Privoxy. In order to provide client indistinguishibility for
  367. complex and variable protocols such as HTTP, Tor must be layered with
  368. a filtering proxy such as Privoxy. Similarly, Tor does not currently
  369. integrate tunneling for non-stream-based protocols; this too must be
  370. provided by an external service.
  371. Tor is not steganographic: it doesn't try to conceal which users are
  372. sending or receiving communications.
  373. \SubSection{Adversary Model}
  374. \label{subsec:adversary-model}
  375. Like all practical low-latency systems, Tor is not secure against a
  376. global passive adversary, which is the most commonly assumed adversary
  377. for analysis of theoretical anonymous communication designs. The adversary
  378. we assume
  379. is weaker than global with respect to distribution, but it is not
  380. merely passive.
  381. We assume a threat model that expands on that from \cite{or-pet00}.
  382. The basic adversary components we consider are:
  383. \begin{description}
  384. \item[Observer:] can observe a connection (e.g., a sniffer on an
  385. Internet router), but cannot initiate connections. Observations may
  386. include timing and/or volume of packets as well as appearance of
  387. individual packets (including headers and content).
  388. \item[Disrupter:] can delay (indefinitely) or corrupt traffic on a
  389. link. Can change all those things that an observer can observe up to
  390. the limits of computational ability (e.g., cannot forge signatures
  391. unless a key is compromised).
  392. \item[Hostile initiator:] can initiate (or destroy) connections with
  393. specific routes as well as vary the timing and content of traffic
  394. on the connections it creates. A special case of the disrupter with
  395. additional abilities appropriate to its role in forming connections.
  396. \item[Hostile responder:] can vary the traffic on the connections made
  397. to it including refusing them entirely, intentionally modifying what
  398. it sends and at what rate, and selectively closing them. Also a
  399. special case of the disrupter.
  400. \item[Key breaker:] can break the key used to encrypt connection
  401. initiation requests sent to a Tor-node.
  402. % Er, there are no long-term private decryption keys. They have
  403. % long-term private signing keys, and medium-term onion (decryption)
  404. % keys. Plus short-term link keys. Should we lump them together or
  405. % separate them out? -RD
  406. %
  407. % Hmmm, I was talking about the keys used to encrypt the onion skin
  408. % that contains the public DH key from the initiator. Is that what you
  409. % mean by medium-term onion key? (``Onion key'' used to mean the
  410. % session keys distributed in the onion, back when there were onions.)
  411. % Also, why are link keys short-term? By link keys I assume you mean
  412. % keys that neighbor nodes use to superencrypt all the stuff they send
  413. % to each other on a link. Did you mean the session keys? I had been
  414. % calling session keys short-term and everything else long-term. I
  415. % know I was being sloppy. (I _have_ written papers formalizing
  416. % concepts of relative freshness.) But, there's some questions lurking
  417. % here. First up, I don't see why the onion-skin encryption key should
  418. % be any shorter term than the signature key in terms of threat
  419. % resistance. I understand that how we update onion-skin encryption
  420. % keys makes them depend on the signature keys. But, this is not the
  421. % basis on which we should be deciding about key rotation. Another
  422. % question is whether we want to bother with someone who breaks a
  423. % signature key as a particular adversary. He should be able to do
  424. % nearly the same as a compromised tor-node, although they're not the
  425. % same. I reworded above, I'm thinking we should leave other concerns
  426. % for later. -PS
  427. \item[Compromised Tor-node:] can arbitrarily manipulate the
  428. connections under its control, as well as creating new connections
  429. (that pass through itself).
  430. \end{description}
  431. All feasible adversaries can be composed out of these basic
  432. adversaries. This includes combinations such as one or more
  433. compromised Tor-nodes cooperating with disrupters of links on which
  434. those nodes are not adjacent, or such as combinations of hostile
  435. outsiders and link observers (who watch links between adjacent
  436. Tor-nodes). Note that one type of observer might be a Tor-node. This
  437. is sometimes called an honest-but-curious adversary. While an observer
  438. Tor-node will perform only correct protocol interactions, it might
  439. share information about connections and cannot be assumed to destroy
  440. session keys at end of a session. Note that a compromised Tor-node is
  441. stronger than any other adversary component in the sense that
  442. replacing a component of any adversary with a compromised Tor-node
  443. results in a stronger overall adversary (assuming that the compromised
  444. Tor-node retains the same signature keys and other private
  445. state-information as the component it replaces).
  446. In general we are more focused on traffic analysis attacks than
  447. traffic confirmation attacks. A user who runs a Tor proxy on his own
  448. machine, connects to some remote Tor-node and makes a connection to an
  449. open Internet site, such as a public web server, is vulnerable to
  450. traffic confirmation. That is, an active attacker who suspects that
  451. the particular client is communicating with the particular server will
  452. be able to confirm this if she can attack and observe both the
  453. connection between the Tor network and the client and that between the
  454. Tor network and the server. Even a purely passive attacker will be
  455. able to confirm if the timing and volume properties of the traffic on
  456. the connnection are unique enough. This is not to say that Tor offers
  457. no resistance to traffic confirmation; it does. We defer discussion
  458. of this point and of particular attacks until Section~\ref{sec:attacks},
  459. after we have described Tor in more detail. However, we note here some
  460. basic assumptions that affect the threat model.
  461. [XXX I think this next subsection should be cut, leaving its points
  462. for the attacks section. But I'm leaving it here for now. The above
  463. line refers to the immediately following SubSection.-PS]
  464. \SubSection{Known attacks against low-latency anonymity systems}
  465. \label{subsec:known-attacks}
  466. We discuss each of these attacks in more detail below, along with the
  467. aspects of the Tor design that provide defense. We provide a summary
  468. of the attacks and our defenses against them in Section~\ref{sec:attacks}.
  469. Passive attacks:
  470. simple observation,
  471. timing correlation,
  472. size correlation,
  473. option distinguishability,
  474. Active attacks:
  475. key compromise,
  476. iterated subpoena,
  477. run recipient,
  478. run a hostile node,
  479. compromise entire path,
  480. selectively DOS servers,
  481. introduce timing into messages,
  482. directory attacks,
  483. tagging attacks
  484. \SubSection{Assumptions}
  485. For purposes of this paper, we assume all directory servers are honest
  486. % No longer true, see subsec:dirservers below -RD
  487. and trusted. Perhaps more accurately, we assume that all users and
  488. nodes can perform their own periodic checks on information they have
  489. from directory servers and that all will always have access to at
  490. least one directory server that they trust and from which they obtain
  491. all directory information. Future work may include robustness
  492. techniques to cope with a minority dishonest servers.
  493. Somewhere between ten percent and twenty percent of nodes are assumed
  494. to be compromised. In some circumstances, e.g., if the Tor network is
  495. running on a hardened network where all operators have had
  496. background checks, the percent of compromised nodes might be much
  497. lower. It may be worthwhile to consider cases where many of the `bad'
  498. nodes are not fully compromised but simply (passive) observing
  499. adversaries or that some nodes have only had compromise of the keys
  500. that decrypt connection initiation requests. But, we assume for
  501. simplicity that `bad' nodes are compromised in the sense spelled out
  502. above. We assume that all adversary components, regardless of their
  503. capabilities are collaborating and are connected in an offline clique.
  504. We do not assume any hostile users, except in the context of
  505. % This sounds horrible. What do you mean we don't assume any hostile
  506. % users? Surely we can tolerate some? -RD
  507. rendezvous points. Nonetheless, we assume that users vary widely in
  508. both the duration and number of times they are connected to the Tor
  509. network. They can also be assumed to vary widely in the volume and
  510. shape of the traffic they send and receive.
  511. [XXX what else?]
  512. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  513. \Section{The Tor Design}
  514. \label{sec:design}
  515. high-level intro: overlay network of onion routers with long-term TLS
  516. connections. (Every OR connects to every other.) Users run local
  517. software (onion proxies) that establish path over network and
  518. construct virtual circuit. (USers know about all ORs from Directory.)
  519. OPs accept TCP streams and multiplex them across virtual circuit. OR
  520. on the other side of the cirucuit connects to the destinations of the
  521. TCP streams and continues to relay TCP sessions.
  522. Describe connection protocol. Link-to-link rate limiting. Link
  523. padding.
  524. Describe cells. Control versus Relay. Cell structure.
  525. Describe how circuits work and how relay cells get passed along,
  526. decrypted etc. This will include mentioning leaky-pipe circuit
  527. topology and end-to-end integrity checking. (Mention tagging.)
  528. Describe how circuits get built, extended, truncated.
  529. Describe how TCP connections get opened. (Mention DNS issues)
  530. Descibe closing TCP connections and 2-END handshake to mirror TCP
  531. close handshake.
  532. Describe how data is transmitted.
  533. Describe circuit-level and stream-level congestion control issues and
  534. solutions.
  535. Describe circuit-level and stream-level fairness issues; cite Marc's
  536. anonnet stuff.
  537. Describe DoS prevention.
  538. Mention twins, what the do, what they can't.
  539. How we should do sequencing and acking like TCP so that we can better
  540. tolerate lost data cells.
  541. [XXX mention that designers have to choose what you send across your
  542. circuit: wrapped IP packets, wrapped stream data, etc. [Disspell
  543. TCP-over-TCP misconception.]]
  544. [XXX Mention that OR-to-OR connections should be highly reliable. If
  545. they aren't, everything can stall.]
  546. \Section{Other design decisions}
  547. \SubSection{Exit policies and abuse}
  548. \label{subsec:exitpolicies}
  549. Exit abuse is a serious barrier to wide-scale Tor deployment --- we
  550. must block or limit attacks and other abuse that users can do through
  551. the Tor network.
  552. Each onion router's \emph{exit policy} describes to which external
  553. addresses and ports the router will permit stream connections. On one end
  554. of the spectrum are \emph{open exit} nodes that will connect anywhere;
  555. on the other end are \emph{middleman} nodes that only relay traffic to
  556. other Tor nodes, and \emph{private exit} nodes that only connect locally
  557. or to addresses internal to that node's organization. This private exit
  558. node configuration is more secure for clients --- the adversary cannot
  559. see plaintext traffic leaving the network (e.g. to a webserver), so he
  560. is less sure of Alice's destination. More generally, nodes can require
  561. a variety of forms of traffic authentication \cite{onion-discex00}.
  562. Tor offers more reliability than the high-latency fire-and-forget
  563. anonymous email networks, because the sender opens a TCP stream
  564. with the remote mail server and receives an explicit confirmation of
  565. acceptance. But ironically, the private exit node model works poorly for
  566. email, when Tor nodes are run on volunteer machines that also do other
  567. things, because it's quite hard to configure mail transport agents so
  568. normal users can send mail normally, but the Tor process can only deliver
  569. mail locally. Further, most organizations have specific hosts that will
  570. deliver mail on behalf of certain IP ranges; Tor operators must be aware
  571. of these hosts and consider putting them in the Tor exit policy.
  572. The abuse issues on closed (e.g. military) networks are very different
  573. from the abuse on open networks like the Internet. While these IP-based
  574. access controls are still commonplace on the Internet, on closed networks,
  575. nearly all participants will be honest, and end-to-end authentication
  576. can be assumed for anything important.
  577. Tor is harder than minion because tcp doesn't include an abuse
  578. address. you could reach inside the http stream and change the agent
  579. or something, but that's a very specific case and probably won't help
  580. much anyway.
  581. And volunteer nodes don't resolve to anonymizer.mit.edu so it never
  582. even occurs to people that it wasn't you.
  583. Preventing abuse of open exit nodes is an unsolved problem. Princeton's
  584. CoDeeN project \cite{darkside} gives us a glimpse of what we're in for.
  585. but their solutions, which mainly involve rate limiting and blacklisting
  586. nodes which do bad things, don't translate directly to Tor. Rate limiting
  587. still works great, but Tor intentionally separates sender from recipient,
  588. so it's hard to know which sender was the one who did the bad thing,
  589. without just making the whole network wide open.
  590. even limiting most nodes to allow http, ssh, and aim to exit and reject
  591. all other stuff is sketchy, because plenty of abuse can happen over
  592. port 80. but it's a very good start, because it blocks most things,
  593. and because people are more used to the concept of port 80 abuse not
  594. coming from the machine's owner.
  595. we could also run intrusion detection system (IDS) modules at each tor
  596. node, to dynamically monitor traffic streams for attack signatures. it
  597. can even react when it sees a signature by closing the stream. but IDS's
  598. don't actually work most of the time, and besides, how do you write a
  599. signature for "is sending a mean mail"?
  600. we should run a squid at each exit node, to provide comparable anonymity
  601. to private exit nodes for cache hits, to speed everything up, and to
  602. have a buffer for funny stuff coming out of port 80. we could similarly
  603. have other exit proxies for other protocols, like mail, to check
  604. delivered mail for being spam.
  605. A mixture of open and restricted exit nodes will allow the most
  606. flexibility for volunteers running servers. But while a large number
  607. of middleman nodes is useful to provide a large and robust network,
  608. a small number of exit nodes still simplifies traffic analysis because
  609. there are fewer nodes the adversary needs to monitor, and also puts a
  610. greater burden on the exit nodes.
  611. The JAP cascade model is really nice because they only need one node to
  612. take the heat per cascade. On the other hand, a hydra scheme could work
  613. better (it's still hard to watch all the clients).
  614. Discuss importance of public perception, and how abuse affects it.
  615. ``Usability is a security parameter''. ``Public Perception is also a
  616. security parameter.''
  617. Discuss smear attacks.
  618. \SubSection{Directory Servers}
  619. \label{subsec:dirservers}
  620. First-generation Onion Routing designs \cite{or-jsac98,freedom2-arch} did
  621. % is or-jsac98 the right cite here? what's our stock OR cite? -RD
  622. in-band network status updates: each router flooded a signed statement
  623. to its neighbors, which propagated it onward. But anonymizing networks
  624. have different security goals than typical link-state routing protocols.
  625. For example, we worry more about delays (accidental or intentional)
  626. which cause different parts of the network to have different pictures
  627. of link-state and topology. We also worry about attacks to deceive a
  628. client about the router membership list, topology, or current network
  629. state. Such \emph{partitioning attacks} on client knowledge help an
  630. adversary with limited resources to efficiently deploy those resources
  631. when attacking a target.
  632. Instead, Tor uses a small group of redundant directory servers to
  633. track network topology and node state such as current keys and exit
  634. policies. The directory servers are normal onion routers, but there are
  635. only a few of them and they are more trusted. They listen on a separate
  636. port as an HTTP server, both so participants can fetch current network
  637. state and router lists (a \emph{directory}), and so other onion routers
  638. can upload a signed summary of their keys, address, bandwidth, exit
  639. policy, etc (\emph{server descriptors}.
  640. [[mention that descriptors are signed with long-term keys; ORs publish
  641. regularly to dirservers; policies for generating directories; key
  642. rotation (link, onion, identity); Everybody already know directory
  643. keys; how to approve new nodes (advogato, sybil, captcha (RTT));
  644. policy for handling connections with unknown ORs; diff-based
  645. retrieval; diff-based consesus; separate liveness from descriptor
  646. list]]
  647. Of course, a variety of attacks remain. An adversary who controls a
  648. directory server can track certain clients by providing different
  649. information --- perhaps by listing only nodes under its control
  650. as working, or by informing only certain clients about a given
  651. node. Moreover, an adversary without control of a directory server can
  652. still exploit differences among client knowledge. If Eve knows that
  653. node $M$ is listed on server $D_1$ but not on $D_2$, she can use this
  654. knowledge to link traffic through $M$ to clients who have queried $D_1$.
  655. Thus these directory servers must be synchronized and redundant. The
  656. software is distributed with the signature public key of each directory
  657. server, and directories must be signed by a threshold of these keys.
  658. The directory servers in Tor are modeled after those in Mixminion
  659. \cite{minion-design}, but our situation is easier. Firstly, we make the
  660. simplifying assumption that all participants agree on who the directory
  661. servers are. Secondly, Mixminion needs to predict node behavior ---
  662. that is, build a reputation system for guessing future performance of
  663. nodes based on past performance, and then figure out a way to build
  664. a threshold consensus of these predictions. Tor just needs to get a
  665. threshold consensus of the current state of the network.
  666. The threshold consensus can be reached with standard Byzantine agreement
  667. techniques \cite{castro-liskov}.
  668. % Should I just stop the section here? Is the rest crap? -RD
  669. But this library, while more efficient than previous Byzantine agreement
  670. systems, is still complex and heavyweight for our purposes: we only need
  671. to compute a single algorithm, and we do not require strict in-order
  672. computation steps. The Tor directory servers build a consensus directory
  673. through a simple four-round broadcast protocol. First, each server signs
  674. and broadcasts its current opinion to the other directory servers; each
  675. server then rebroadcasts all the signed opinions it has received. At this
  676. point all directory servers check to see if anybody's cheating. If so,
  677. directory service stops, the humans are notified, and that directory
  678. server is permanently removed from the network. Assuming no cheating,
  679. each directory server then computes a local algorithm on the set of
  680. opinions, resulting in a uniform shared directory. Then the servers sign
  681. this directory and broadcast it; and finally all servers rebroadcast
  682. the directory and all the signatures.
  683. The rebroadcast steps ensure that a directory server is heard by either
  684. all of the other servers or none of them (some of the links between
  685. directory servers may be down). Broadcasts are feasible because there
  686. are so few directory servers (currently 3, but we expect to use as many
  687. as 9 as the network scales). The actual local algorithm for computing
  688. the shared directory is straightforward, and is described in the Tor
  689. specification \cite{tor-spec}.
  690. % we should, uh, add this to the spec. oh, and write it. -RD
  691. Using directory servers rather than flooding approaches provides
  692. simplicity and flexibility. For example, they don't complicate
  693. the analysis when we start experimenting with non-clique network
  694. topologies. And because the directories are signed, they can be cached at
  695. all the other onion routers (or even elsewhere). Thus directory servers
  696. are not a performance bottleneck when we have many users, and also they
  697. won't aid traffic analysis by forcing clients to periodically announce
  698. their existence to any central point.
  699. \Section{Rendezvous points: location privacy}
  700. \label{sec:rendezvous}
  701. Rendezvous points are a building block for \emph{location-hidden services}
  702. (aka responder anonymity) in the Tor network. Location-hidden
  703. services means Bob can offer a tcp service, such as a webserver,
  704. without revealing the IP of that service.
  705. We provide this censorship resistance for Bob by allowing him to
  706. advertise several onion routers (his \emph{Introduction Points}) as his
  707. public location. Alice, the client, chooses a node for her \emph{Meeting
  708. Point}. She connects to one of Bob's introduction points, informs him
  709. about her meeting point, and then waits for him to connect to the meeting
  710. point. This extra level of indirection means Bob's introduction points
  711. don't open themselves up to abuse by serving files directly, eg if Bob
  712. chooses a node in France to serve material distateful to the French. The
  713. extra level of indirection also allows Bob to respond to some requests
  714. and ignore others.
  715. We provide the necessary glue so that Alice can view webpages from Bob's
  716. location-hidden webserver with minimal invasive changes. Both Alice and
  717. Bob must run local onion proxies.
  718. The steps of a rendezvous:
  719. \begin{tightlist}
  720. \item Bob chooses some Introduction Points, and advertises them on a
  721. Distributed Hash Table (DHT).
  722. \item Bob establishes onion routing connections to each of his
  723. Introduction Points, and waits.
  724. \item Alice learns about Bob's service out of band (perhaps Bob told her,
  725. or she found it on a website). She looks up the details of Bob's
  726. service from the DHT.
  727. \item Alice chooses and establishes a Meeting Point (MP) for this
  728. transaction.
  729. \item Alice goes to one of Bob's Introduction Points, and gives it a blob
  730. (encrypted for Bob) which tells him about herself, the Meeting Point
  731. she chose, and the first half of an ephemeral key handshake. The
  732. Introduction Point sends the blob to Bob.
  733. \item Bob chooses whether to ignore the blob, or to onion route to MP.
  734. Let's assume the latter.
  735. \item MP plugs together Alice and Bob. Note that MP can't recognize Alice,
  736. Bob, or the data they transmit (they share a session key).
  737. \item Alice sends a Begin cell along the circuit. It arrives at Bob's
  738. onion proxy. Bob's onion proxy connects to Bob's webserver.
  739. \item Data goes back and forth as usual.
  740. \end{tightlist}
  741. When establishing an introduction point, Bob provides the onion router
  742. with a public ``introduction'' key. The hash of this public key
  743. identifies a unique service, and (since Bob is required to sign his
  744. messages) prevents anybody else from usurping Bob's introduction point
  745. in the future. Bob uses the same public key when establish the other
  746. introduction points for that service.
  747. The blob that Alice gives the introduction point includes a hash of Bob's
  748. public key to identify the service, an optional initial authentication
  749. token (the introduction point can do prescreening, eg to block replays),
  750. and (encrypted to Bob's public key) the location of the meeting point,
  751. a meeting cookie Bob should tell the meeting point so he gets connected to
  752. Alice, an optional authentication token so Bob can choose whether to respond,
  753. and the first half of a DH key exchange. When Bob connects to the meeting
  754. place and gets connected to Alice's pipe, his first cell contains the
  755. other half of the DH key exchange.
  756. % briefly talk about our notion of giving cookies to people proportional
  757. % to how important they are, for location-protected servers hardened
  758. % against DDoS threat? -RD
  759. \subsection{Integration with user applications}
  760. For each service Bob offers, he configures his local onion proxy to know
  761. the local IP and port of the server, a strategy for authorizating Alices,
  762. and a public key. We assume the existence of a robust decentralized
  763. efficient lookup system which allows authenticated updates, eg
  764. \cite{cfs:sosp01}. (Each onion router could run a node in this lookup
  765. system; also note that as a stopgap measure, we can just run a simple
  766. lookup system on the directory servers.) Bob publishes into the DHT
  767. (indexed by the hash of the public key) the public key, an expiration
  768. time (``not valid after''), and the current introduction points for that
  769. service. Note that Bob's webserver is completely oblivious to the fact
  770. that it's hidden behind the Tor network.
  771. As far as Alice's experience goes, we require that her client interface
  772. remain a SOCKS proxy, and we require that she shouldn't have to modify
  773. her applications. Thus we encode all of the necessary information into
  774. the hostname (more correctly, fully qualified domain name) that Alice
  775. uses, eg when clicking on a url in her browser. Location-hidden services
  776. use the special top level domain called `.onion': thus hostnames take the
  777. form x.y.onion where x encodes the hash of PK, and y is the authentication
  778. cookie. Alice's onion proxy examines hostnames and recognizes when they're
  779. destined for a hidden server. If so, it decodes the PK and starts the
  780. rendezvous as described in the table above.
  781. \subsection{Previous rendezvous work}
  782. Ian Goldberg developed a similar notion of rendezvous points for
  783. low-latency anonymity systems \cite{ian-thesis}. His ``service tag''
  784. is the same concept as our ``hash of service's public key''. We make it
  785. a hash of the public key so it can be self-authenticating, and so the
  786. client can recognize the same service with confidence later on. His
  787. design differs from ours in the following ways though. Firstly, Ian
  788. suggests that the client should manually hunt down a current location of
  789. the service via Gnutella; whereas our use of the DHT makes lookup faster,
  790. more robust, and transparent to the user. Secondly, the client and server
  791. can share ephemeral DH keys, so at no point in the path is the plaintext
  792. exposed. Thirdly, our design is much more practical for deployment in a
  793. volunteer network, in terms of getting volunteers to offer introduction
  794. and meeting point services. The introduction points do not output any
  795. bytes to the clients. And the meeting points don't know the client,
  796. the server, or the stuff being transmitted. The indirection scheme
  797. is also designed with authentication/authorization in mind -- if the
  798. client doesn't include the right cookie with its request for service,
  799. the server doesn't even acknowledge its existence.
  800. \Section{Analysis}
  801. How well do we resist chosen adversary?
  802. How well do we meet stated goals?
  803. Mention jurisdictional arbitrage.
  804. Pull attacks and defenses into analysis as a subsection
  805. \Section{Maintaining anonymity sets}
  806. \label{sec:maintaining-anonymity}
  807. [Put as much of this as a part of open issuses as is possible.]
  808. [what's an anonymity set?]
  809. packet counting attacks work great against initiators. need to do some
  810. level of obfuscation for that. standard link padding for passive link
  811. observers. long-range padding for people who own the first hop. are
  812. we just screwed against people who insert timing signatures into your
  813. traffic?
  814. Even regardless of link padding from Alice to the cloud, there will be
  815. times when Alice is simply not online. Link padding, at the edges or
  816. inside the cloud, does not help for this.
  817. how often should we pull down directories? how often send updated
  818. server descs?
  819. when we start up the client, should we build a circuit immediately,
  820. or should the default be to build a circuit only on demand? should we
  821. fetch a directory immediately?
  822. would we benefit from greater synchronization, to blend with the other
  823. users? would the reduced speed hurt us more?
  824. does the "you can't see when i'm starting or ending a stream because
  825. you can't tell what sort of relay cell it is" idea work, or is just
  826. a distraction?
  827. does running a server actually get you better protection, because traffic
  828. coming from your node could plausibly have come from elsewhere? how
  829. much mixing do you need before this is actually plausible, or is it
  830. immediately beneficial because many adversary can't see your node?
  831. do different exit policies at different exit nodes trash anonymity sets,
  832. or not mess with them much?
  833. do we get better protection against a realistic adversary by having as
  834. many nodes as possible, so he probably can't see the whole network,
  835. or by having a small number of nodes that mix traffic well? is a
  836. cascade topology a more realistic way to get defenses against traffic
  837. confirmation? does the hydra (many inputs, few outputs) topology work
  838. better? are we going to get a hydra anyway because most nodes will be
  839. middleman nodes?
  840. using a circuit many times is good because it's less cpu work.
  841. good because of predecessor attacks with path rebuilding.
  842. bad because predecessor attacks can be more likely to link you with a
  843. previous circuit since you're so verbose.
  844. bad because each thing you do on that circuit is linked to the other
  845. things you do on that circuit.
  846. how often to rotate?
  847. how to decide when to exit from middle?
  848. when to truncate and re-extend versus when to start new circuit?
  849. Because Tor runs over TCP, when one of the servers goes down it seems
  850. that all the circuits (and thus streams) going over that server must
  851. break. This reduces anonymity because everybody needs to reconnect
  852. right then (does it? how much?) and because exit connections all break
  853. at the same time, and it also reduces usability. It seems the problem
  854. is even worse in a p2p environment, because so far such systems don't
  855. really provide an incentive for nodes to stay connected when they're
  856. done browsing, so we would expect a much higher churn rate than for
  857. onion routing. Are there ways of allowing streams to survive the loss
  858. of a node in the path?
  859. discuss topologies. Cite George's non-freeroutes paper. Maybe this
  860. graf goes elsewhere.
  861. discuss attracting users; incentives; usability.
  862. Choosing paths and path lengths.
  863. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  864. \Section{Attacks and Defenses}
  865. \label{sec:attacks}
  866. Below we summarize a variety of attacks and how well our design withstands
  867. them.
  868. \begin{enumerate}
  869. \item \textbf{Passive attacks}
  870. \begin{itemize}
  871. \item \emph{Simple observation.}
  872. \item \emph{Timing correlation.}
  873. \item \emph{Size correlation.}
  874. \item \emph{Option distinguishability.}
  875. \end{itemize}
  876. \item \textbf{Active attacks}
  877. \begin{itemize}
  878. \item \emph{Key compromise.}
  879. \item \emph{Iterated subpoena.}
  880. \item \emph{Run recipient.}
  881. \item \emph{Run a hostile node.}
  882. \item \emph{Compromise entire path.}
  883. \item \emph{Selectively DoS servers.}
  884. \item \emph{Introduce timing into messages.}
  885. \item \emph{Tagging attacks.}
  886. the exit node can change the content you're getting to try to
  887. trick you. similarly, when it rejects you due to exit policy,
  888. it could give you a bad IP that sends you somewhere else.
  889. \end{itemize}
  890. \item \textbf{Directory attacks}
  891. \begin{itemize}
  892. \item foo
  893. \end{itemize}
  894. \end{enumerate}
  895. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  896. \Section{Future Directions and Open Problems}
  897. \label{sec:conclusion}
  898. % Mention that we need to do TCP over tor for reliability.
  899. Tor brings together many innovations into
  900. a unified deployable system. But there are still several attacks that
  901. work quite well, as well as a number of sustainability and run-time
  902. issues remaining to be ironed out. In particular:
  903. \begin{itemize}
  904. \item \emph{Scalability:} Since Tor's emphasis currently is on simplicity
  905. of design and deployment, the current design won't easily handle more
  906. than a few hundred servers, because of its clique topology. Restricted
  907. route topologies \cite{danezis-pets03} promise comparable anonymity
  908. with much better scaling properties, but we must solve problems like
  909. how to randomly form the network without introducing net attacks.
  910. % [cascades are a restricted route topology too. we must mention
  911. % earlier why we're not satisfied with the cascade approach.]-RD
  912. % [We do. At least
  913. \item \emph{Cover traffic:} Currently we avoid cover traffic because
  914. it introduces clear performance and bandwidth costs, but and its
  915. security properties are not well understood. With more research
  916. \cite{SS03,defensive-dropping}, the price/value ratio may change, both for
  917. link-level cover traffic and also long-range cover traffic. In particular,
  918. we expect restricted route topologies to reduce the cost of cover traffic
  919. because there are fewer links to cover.
  920. \item \emph{Better directory distribution:} Even with the threshold
  921. directory agreement algorithm described in \ref{subsec:dirservers},
  922. the directory servers are still trust bottlenecks. We must find more
  923. decentralized yet practical ways to distribute up-to-date snapshots of
  924. network status without introducing new attacks.
  925. \item \emph{Implementing location-hidden servers:} While Section
  926. \ref{sec:rendezvous} provides a design for rendezvous points and
  927. location-hidden servers, this feature has not yet been implemented.
  928. We will likely encounter additional issues, both in terms of usability
  929. and anonymity, that must be resolved.
  930. \item \emph{Wider-scale deployment:} The original goal of Tor was to
  931. gain experience in deploying an anonymizing overlay network, and learn
  932. from having actual users. We are now at the point where we can start
  933. deploying a wider network. We will see what happens!
  934. % ok, so that's hokey. fix it. -RD
  935. \end{itemize}
  936. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  937. %\Section{Acknowledgments}
  938. %% commented out for anonymous submission
  939. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  940. \bibliographystyle{latex8}
  941. \bibliography{tor-design}
  942. \end{document}
  943. % Style guide:
  944. % U.S. spelling
  945. % avoid contractions (it's, can't, etc.)
  946. % 'mix', 'mixes' (as noun)
  947. % 'mix-net'
  948. % 'mix', 'mixing' (as verb)
  949. % 'Mixminion Project'
  950. % 'Mixminion' (meaning the protocol suite or the network)
  951. % 'Mixmaster' (meaning the protocol suite or the network)
  952. % 'middleman' [Not with a hyphen; the hyphen has been optional
  953. % since Middle English.]
  954. % 'nymserver'
  955. % 'Cypherpunk', 'Cypherpunks', 'Cypherpunk remailer'
  956. % 'Onion Routing design', 'onion router' [note capitalization]
  957. %
  958. % 'Whenever you are tempted to write 'Very', write 'Damn' instead, so
  959. % your editor will take it out for you.' -- Misquoted from Mark Twain