A Peel of Onion. Paul Syverson U.S. Naval Research Laboratory.
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1 A Peel of Onion Paul Syverson U.S. Naval Research Laboratory
2 Our motivation here is not to provide anonymous communication, but to separate identification from routing. Proxies for anonymous routing. Reed, Syverson, and Goldschlag. ACSAC 1996
3 A Motivational Use Case Example Navy Petty Officer Alice is temporarily in Repressia
4
5 A Motivational Use Case Example Safe back in her room at the Repressia Grand Hotel, PO Alice wants to read and/or post to sealiftcommand.com
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7 A Motivational Use Case Example Navy PO Alice in her hotel
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9 Connecting when overseas Navy PO Alice in her hotel Contacted: sealiftcommand.com 05/06/2014, 9PM, 20 min, encrypted
10 Connecting when overseas Navy PO Alice in her hotel Contacted: sealiftcommand.com 05/06/2014, 9PM, 20 min, encrypted Rm: 416 Ckout on: 05/08/2014
11 Security of operations concern as well as personnel security concern Navy PO Alice in her hotel Contacted: nrl.navy.mil 05/06/2014, 9PM, 20 min, encrypted Rm: 416 Ckout on: 05/08/2014
12 Some more government uses Open source intelligence gathering Sensitive communications with untrusted/ untrusting parties Encouraging open communications with citizens Location protected servers for defense in depth Protecting the public infrastructure Interacting with network sensors
13 Ordinary citizen Alice Protecting her behavior from: Cyberstalking abusive ex-spouse Behavior tracking and DNS shenanigans from her ISP Misunderstanding from her employer when she investigates disease info for an ailing friend Harassment for blogging her views Malicious parties watching her log into Club Penguin (and watching her mom logged into twitter from work) Spear phishers watching her log into her bank
14
15 It's not only about dissidents in faraway lands
16 Ordinary citizen Alice Protecting her behavior from: Cyberstalking abusive ex-spouse Behavior tracking and DNS shenanigans from her ISP Misunderstanding from her employer when she investigates disease info for an ailing friend Harassment for blogging her views Malicious parties watching her log into Club Penguin (and watching her mom logged into twitter from work) Spear phishers watching her log into her bank
17 Ordinary citizen Alice Protecting her behavior from: Cyberstalking abusive ex-spouse Behavior tracking and DNS shenanigans from her ISP Misunderstanding from her employer when she investigates disease info for an ailing friend Harassment for blogging her views Malicious parties watching her log into Club Penguin (and watching her mom logged into twitter from work) Spear phishers watching her log into her bank
18 Officer Alice Setting up a sting operation: as a collaborator as a service provider Monitoring criminal activity online Encouraging anonymous tips
19 Researcher/Reporter/Rights Worker Alice Gathering information while protecting sources Accessing information that is locally censored or monitored Reporting information that is locally censored or monitored
20 Corporation Alice Investigating competitors public sites Avoiding leaking strategy or nonpublic information Protecting customers spearphishing attacks or selective service disruption privacy sensitivity
21 Aside: some other benefits of an anonymity system Besides protecting affiliation, etc. can provide poor man s VPN. Access to the internet despite Network port policy disconnects DNS failure
22 You can't be anonymous by yourself: private solutions are ineffective... Citizen Alice Alice's small anonymity net... One of the 25 users on AliceNet. Officer Alice Municipal anonymity net Investigated suspect Looks like a cop. AliceCorp AliceCorp anonymity net Competitor/ malware host It's somebody at AliceCorp!
23 ... so, anonymity loves company! Citizen Alice...??? Officer Alice Shared anonymity net Investigated suspect??? AliceCorp Competitor???
24 The simplest designs use a single relay to hide connections. Alice1 Bob1 Alice2 Bob1, Y Relay Z Bob2 Alice3 Bob3
25 But an attacker who sees Alice can see who she's talking to. Alice1 Bob1 Alice2 Bob1, Y Relay Z Bob2 Alice3 Bob3
26 Add encryption to stop attackers who eavesdrop on Alice. Alice1 Bob1 Alice2 E(Bob1, Y ) Relay Z Bob2 Alice3 Bob3 (e.g.: some commercial proxy providers, Anonymizer)
27 But a single relay is a single point of failure. Alice1 Bob1 Alice2 E(Bob1, Y ) Evil or Compromised Relay Z Bob2 Alice3 Bob3
28 But a single relay is a single point of bypass. Alice1 Bob1 Alice2 E(Bob1, Y ) Irrelevant Relay Z Bob2 Alice3 Bob3 Timing analysis bridges all connections through relay An attractive fat target
29 Low-latency systems are vulnerable to end-to-end correlation attacks. Low-latency: Alice1 sends: Bob2 gets: " Alice2 sends: Bob1 gets: Time High-latency: Alice1 sends: Alice2 sends: " Bob1 gets:... Bob2 gets:... match! match! These attacks work in practice. The obvious defenses are expensive (like high-latency), useless, or both.
30 But a single relay is a single point of bypass. Alice1 Bob1 Alice2 E(Bob1, Y ) Irrelevant Relay Z Bob2 Alice3 Bob3 Timing analysis bridges all connections through relay An attractive fat target
31 So, add multiple relays so that no single one can betray Alice. Alice R1 R5 Bob R4 R2 R3
32 A corrupt first hop can tell that Alice is talking, but not to whom. Alice R5 Bob R4 R2 R3
33 A corrupt last hop can tell someone is talking to Bob, but not who. Alice R1 Bob R4 R2 R3
34 Onion Routing: Circuit construction Alice R1 R5 Bob R4 R2 R3
35 Onion Routing: Circuit construction Alice R1 R5 Bob R4 R2 R3
36 Onion Routing: Circuit construction Alice R1 R5 Bob R4 R2 R3
37 Onion Routing: Connection creation Alice R1 R5 Bob R4 R2 R3
38 Onion Routing: Data Exchange Alice R1 R5 Bob R4 R2 R3
39 Onion Routing: Data Exchange Alice R1 R5 Bobs R4 R2 R3
40 Onion Routers (Relays/Nodes): Clique topology R1 R5 R4 R2 R3
41 Onion Routers (Relays/Nodes): Overlay network R1 R5 R4 R2 R3
42 That's onion routing in a nutshell
43 Mix networks vs. Onion routing networks Low-latency: Alice1 sends: Bob2 gets: " The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again. Alice2 sends: Bob1 gets: Time High-latency: Alice1 sends: Alice2 sends: " Bob1 gets:... Bob2 gets:... match! match! These attacks work in practice. The obvious defenses are expensive (like high-latency), useless, or both.
44
45 What onion routing is NOT: Mixes Entirely different threat model mixes are based on an adversary not being able to correlate inputs and outputs he sees onion routing is based on an adversary not being able to see both inputs and outputs to correlate mix networks more secure against global passive adversary mix networks can be less secure vs. local active adversary Entirely different communications paradigm: Circuit based encryption vs. per message onion routing supports bidirectional communication onion routing supports low-latency communication Can be combined to make mixing onion routers, but not typically done or desired
46 What onion routing is Uses expensive crypto (public-key) to lay a cryptographic circuit over which data is passed Typically uses free-route circuit building to make location of circuit endpoints unpredictable
47 Why call it onion routing? Answer: Because of the original key distribution data structure Alice Bob R1 R3 R4 R2 R5
48 Why is it called onion routing? K A,R5 " K A,R2 R5 Alice R1 K A,R1 R2 R5 Bob R4 R3 R2 Onion: Just layers of public-key crypto Nothing in the center, just another layer
49 Mixi networks have a message in the middle of a public-key onion. 49
50 Why is it called onion routing? K A,R5 " K A,R2 R5 Alice R1 K A,R1 R2 R5 Bob R4 R3 R2 Onion: Just layers of public-key crypto Nothing in the center, just another layer
51 Circuit setup K A,R5 " K A,R2 R5 K A,R1 R2 NRL v0 and v1 onion routing and also ZKS Freedom network used onions to build circuits Lacked Forward Secrecy Required storing record of onions against replay Tor (NRL v2) uses one layer onion skins ephemeral Diffie-Hellman yields forward secrecy No need to record processed onions against replay From suggestion out of Zack Brown s Cebolla
52 Aside: Why is it called Tor and what does Tor mean? Frequent question to Roger c : Oh you re working on onion routing... which one? Roger: THE onion routing. The original onion routing project from NRL. Rachel: That s a good acronym. Roger: And it s a good recursive acronym. Plus, as a word, it has a good meaning in German (door/gate/portal) and Turkish (finemeshed net)
53 Aside: Why is it called Tor and what does Tor mean? We foolishly called the first Tor paper Tor: the second generation onion router But this was very confusing Tor stands for The onion routing or Tor s onion routing. It does not stand for the onion router The paper is about the whole system, not just the onion routers Tor is not the second generation
54 Aside: Why is it called Tor and what does Tor mean?
55 Aside: Why is it called Tor and what does Tor mean? Tor: A (class of) onion routing design created at NRL starting c Tor: A U.S. 501(c)3 nonprofit organization formed in Tor: A client software program that connects your computer to the Tor network. Tor: A volunteer network comprised of c nodes serving c. 4 GiB/s data for c. 1M users (see metrics.torproject.org ) Any amorphous combination of the above or other users
56 Onion routing origins: Generation 0 Fixed-length five-node circuits Integrated configuration Static topology Loose-source routing Partial active adversary Rendezvous servers and reply onions
57 Onion routing, the next generation Running a client separated from running an OR Variable length circuits (up to 11 hops per onion---or tunnel for more) Application independent proxies (SOCKS) plus redirector Entry policies and exit policies Dynamic network state, flat distribution of state info Multiplexing of multiple application connections in single onion routing circuit Mixing of cells from different circuits Padding and bandwidth limiting
58 Third-generation onion routing (Tor) Onion skins, not onions: Diffie-Hellman based circuit building Fixed-length three-hop circuits Rendezvous circuits and hidden servers Directory servers, caching (evolved w/in Tor) Most application specific proxies no longer needed (still need e.g. for DNS) Congestion control End-to-end integrity checking No mixing and no padding
59 Circuit setup K A,R5 " K A,R2 R5 K A,R1 R2 NRL v0 and v1 onion routing and also ZKS Freedom network used onions to build circuits Lacked Forward Secrecy Required storing record of onions against replay Tor (NRL v2) uses one layer onion skins ephemeral Diffie-Hellman yields forward secrecy No need to record processed onions against replay From suggestion out of Zack Brown s Cebolla
60 Tor Circuit Setup (Create) Client chooses first node, establishes session key over TLS connection " Client Initiator, Hash( ) Onion Router TLS connection
61 Tor Circuit Setup (Create) Client chooses first node, establishes session key over TLS connection " Client Initiator, Hash( ) Onion Router
62 Tor Circuit Setup (Extend) Client chooses first node, establishes session key over TLS connection " OR2, Client Initiator, Hash( ) OR1, Hash( ) OR2
63 Tor Circuit Setup (Begin) and Data Flow Slight simplification of actual protocol " Connect Client Initiator Reply OR2 OR1 Reply Web server
64 How do we know where to build a circuit? Network discovery. Flat flooding of network state: complex, tricky, scales in principal but? Tor has a directory system Originally a single directory signing information about network nodes. Then a multiple redundant directory with mirrors. Then a majority vote system. Then a consensus document system. Then separate things that need to be signed and updated frequently. Then...
65 Onion routing was invented to separate identification from routing What if onion-routing-network-user is the identification you want to avoid? Bridges are proxies into the Tor network that are not publicly listed. Tricky to get bridge info out to potential users without giving it to the network blockers. Flash Proxy plugin on volunteer s browser connects to both censored client and Tor relay Can also use obfuscated transport to hide Tor protocols from DPI.
66 What if adversary owns a botnet or has nation level resources? Consumer Alice, abuse/disease victim Alice, local law enforcement Alice, etc. probably OK Intelligence analyst Alice, DoD road warrior Alice, etc.?
67 Network diversity environment Government comms sometimes must use public internet Open source intelligence gathering Traveling employees communicating back home Interacting with untrusted/semitrusted parties Need a network with diversely run infrastructure Economic and usage feasibility implies a freeto-use network with infrastructure open to any contributors Cannot preclude adversaries running a significant portion of your network
68 First-Last Correlation Problem What? Adversary observes first and last routers. Traffic patterns link first and last routers. Why? Attack completely breaks anon regardless of number of users. Attack possible with moderate resources. 17MB/s compromises random 1% of current Tor users (100 or so home Internet accounts needed for attack) Padding, etc. too expensive and will never work anyway.
69 Key Idea: Trust Users may know how likely a router is to be under observation. Tor Routers with Possible Trust Factors Name Hostname Bandwidth Uptime Location Tor version OS moria nexico.ediscom.de 4 KB/s 67 days Germany Linux Republic xvm-107.mit.edu 121 KB/s 49 days USA Linux Unnamed staticip rev.dyxnet.com 58 KB/s 58 days Hong Kong Windows Server 2003 SP2 Source: 10/12/2011
70 Basic Adversary Model Routers R Users Destinations Adversary A
71 Basic Trust Model Routers R Users Destinations 0 1 Probability of Compromise: c Adversary A
72 Trust Model 1: Limited Adversary Routers R Users Destinations 0 1 Probability of Compromise: c Adversary A A R, A k
73 Trust Model 1: Limited Adversary Routers R Users Destinations 0 1 Probability of Compromise: c Adversary A A R, A k
74 Trust Model 2: Per-User Adversary User u Routers R Naïve users N Destinations 0 1 Probability of Compromise: c Adversary A N
75 The Man
76 Trust Model 2: Per-User Adversary User u Routers R Naïve users N Destinations 0 1 Probability of Compromise: c Adversary A N
77 Trust Model 2: Per-User Adversary User u Routers R Naïve users N Destinations 0 1 Probability of Compromise: c Adversary A u Adversary A N
78 Downhill Algorithm Key idea: Blend in with the naïve users. 1. Set path length l and trust levels λ 1,, λ l to optimize anonymity metric.
79 Downhill Algorithm Key idea: Blend in with the naïve users. 1. Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
80 Downhill Algorithm Key idea: Blend in with the naïve users. 1. Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
81 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
82 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
83 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
84 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
85 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i
86 Downhill Algorithm Key idea: Blend in with the naïve users Set path length l and trust levels λ 1,, λ l to optimize anonymity metric. 2. For 1 i l, Randomly select among routers with trust λ i 3. For each connection, Create circuit through selected routers to the destination.
87 Anonymity Analysis of Downhill Algorithm Metric: Posterior probability of actual source of a given connection. Expected anonymity Downhill Most trusted Random Lower bound medium trust low trust
88 Anonymity Analysis Metric: Posterior probability of actual source of a given connection. Expected anonymity Downhill Most trusted Random Lower bound medium trust low trust Scenario 1: User has some limited information. c=.01 c=.1 c=.9 5 routers 10 routers 1000 routers
89 Anonymity Analysis Metric: Posterior probability of actual source of a given connection. Expected anonymity Downhill Most trusted Random Lower bound medium trust low trust Scenario 2: User and friends run routers. Adversary is strong. c= routers c= routers c= routers
90 Tor: Actual path selection Alice R1 R5 Bobs R4 R2 R3
91 Tor: Actual path selection Alice R1 R5 Bobs R4 R2 R3
92 Tor: Actual path selection Alice R1 R5 Bobs R4 R2 R3
93 Tor: Actual path selection Relay choice is weighted by bandwidth & depends on uptime Alice R1 R5 Bobs R4 R2 R3
94 Users get routed (ACM CCS 13 NRL/Georgetown collaboration) 80% of all types of users may be deanonymized by moderate Tor-relay adversary within 6 months
95 First-Last Correlation Problem What? Adversary observes first and last routers. Traffic patterns link first and last routers.
96 Onion Routers (Relays/Nodes): Overlay network R1 R5 R4 R2 R3
97 Users get routed (ACM CCS 13 NRL/Georgetown collaboration) 80% of all types of users may be deanonymized by moderate Tor-relay adversary within 6 months Against a single-as adversary roughly 100% of users in some common locations are deanonymized within three months (or 95% in 3 months for a single IXP) 2-AS adversary reduces median time to the first client deanonymization by an order of magnitude: from over 3 months to only 1 day for typical web user from over 3 months to c. 1 month for a BitTorrent user
98 Using Trust is first approach to protect traffic even if adversary owns a large chunk of the network. Not yet (or much) mentioned/future work: Datagram transport Links Performance/congestion/throttling/incentives Hidden services Trust propagation Better security models
99 Questions?
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