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Xinwen Fu Anonymous Communication & Computer Forensics 91.580.203 Computer & Network Forensics
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CS@UML 2 Outline Background Onion routing Attacks against anonymity Tor
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CS@UML 3 Motivation I know what’s going on!!! Protect the identity of participants in a distributed application, such as E-voting, E-shopping, E-cash, and military applications Eavesdropping
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CS@UML 4 Commercial routers not under government control Unencrypted data is completely open Encrypted data still exposes communicating parties Current Network Status Sender Address Receiver Address IP Packet Header Structure
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CS@UML 5 Public networks are vulnerable to traffic analysis attack. In a public network: Packet headers identify recipients Packet routes can be tracked Volume and timing signatures are exposed Encryption does not hide identity information of a sender and receiver. Sender Public Network Receiver Traffic Analysis Attack
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CS@UML 6 Traffic Analysis reveals identities. Who is talking to whom may be confidential or private: Who is searching a public database? What web-sites are you surfing? Which agencies or companies are collaborating? Where are your e-mail correspondents? What supplies/quantities are you ordering from whom ? Knowing traffic properties can help an adversary decide where to spend resources for decryption, penetration,... Traffic Analysis Attack (cont.)
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CS@UML 7 Goals of Anonymity: Receiver Untraceability Senders are observable – i.e. the attacker knows that A sent a message to someone Receivers are not observable – i.e. the attacker does not know if B received a message Alice Bob Example: radio Evil
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CS@UML 8 Goals of Anonymity: Sender Untraceability Senders unobservable…. Example: Wireless routers using NAT Alice Bob Evil
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CS@UML 9 Goals of Anonymity: Sender/Receiver Unlinkability Senders and Receivers are observable, but not clear who is talking to whom Alice Bob Evil
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CS@UML 10 Outline Background Onion routing Attacks against anonymity Tor
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CS@UML 11 Anonymous Communication Systems A number of Anonymous Communication Systems have been realized. Several well-known systems are: Anonymizer (anonymizer.com) Onion-Routing (NRL) Crowds (Reiter and Rubin) Anonymous Remailer (MIT LCS) Tor (MIT and EFF) Freedom (Zero-Knowledge Systems) Hordes (Shields and Levine) PipeNet (Dai) SafeWeb (Symantec)
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CS@UML 12 Channels appear to come from proxy, not true originator May also filter traffic for identifying information Examples: Penet Remailer (shut down), The Anonymizer, SafeWeb (Symantec) anonymizing proxy Basic Approach: Anonymizing Proxy
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CS@UML 13 User connects to the proxy first and types the URL in a web form Channels appear to come from proxy, not true originator The proxy may also filter traffic to remove identifying information It offers encrypted link to the proxy (SSL or SSH) anonymizing proxy: anonymizer.com Anonymizer for Web Browsing
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CS@UML 14 ISP knows user connection times/volumes: Can easily eavesdrop on outgoing proxy connections and learn all Proxy knows everything about connections So, both are fully trusted (single points of failure) Internet Phone System Responders ISP Encrypted link: user to proxy Proxy Problems of Anonymizer
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CS@UML 15 Underlying Idea for Mixmaster remailer, Onion Routing, ZKS Freedom, Web Mixes Basic description: A network of mix nodes Special Onion-like encryption: Cell (message/packet) wrapped in multiple layers of public-key encryption by sender, one for each node in a route Decrypted layer tells mix next node in route Reordering: Mixes hold different cells for a time and reorder before forwarding to respective destinations Rerouting: use a few proxies Chaum Mixes (David Chaum)
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CS@UML 16 Anonymity Network Sender Receiver A B Onion Routing Based on Mix Networks Sender selects a route through the mix network An intermediate mix only knows where the packet comes from, and what is the next stop of the packet Traditional Spy Network S to A B to R A to B
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CS@UML 17 Review of Public Key Cryptography PrivateKey Bob (PublicKey Bob (Message))=Message PublicKey Bob (PrivateKey Bob (Message))=Message e B (message) d B (e B (message))=message (e B, d B ) (e A, d A ) Bob Alice
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CS@UML 18 Onion-Like Encryption Sender S to R Receiver B A √ M B R S to A A to B M R M B to R
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CS@UML 19 Why Buffering and Reordering Packets? Disrupt the timing correlation between packets into and out of a mix mix
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CS@UML 20 Crowds User machines are the network "Blender" announces crowd members to all members “Jondo" at machine flips weighted coin If Heads forwards to random crowd member If Tails connects to end Web address All Jondos on path know path key All connections from a source use same path for lifetime of that crowd Sender Web server Blender
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CS@UML 21 Crowds Virtues Good on sender protections No single point of failure Peer-to-peer design means minimal long-term network services More lightweight crypto than mix-based systems
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CS@UML 22 Crowds Limitations All users must run Perl code Requires users to have longrunning high-speed Internet connections Entirely new network graph needed for new or reconnecting Crowd member Connection anonymity dependent on data anonymity Anonymity protection limited to Crowd size Rather weak on responder protections Lacks perfect forward anonymity The intermediate nodes knows the receiver
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CS@UML 23 Outline Background Onion routing Attacks against anonymity Tor
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CS@UML 24 Sender B S to A A to B Receiver B to C C to R C A Adversary HQ S to A & A to B B to C & C to R The adversary knows that Sender communicates with Receiver Attacks against Mix Networks x x Connectivity Analysis Attacks
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CS@UML 25 Outline Background Onion routing Attacks against anonymity Tor
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CS@UML 26 Tor: A Practical Anonymous Protocol Some combination of Chaum’s Mix and Crowds Encrypt data packets by symmetric keys Implement forward and backward anonymity Has P2P functions Easy to use Open source
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CS@UML 27 First Sight A web server knows your ip: http://www.proxyway.com/www/check-ip- address/whatis-my-ip-address.html http://www.proxyway.com/www/check-ip- address/whatis-my-ip-address.html Tor to hide your ip Tor downloading webpage http://tor.eff.org/download.html.en http://tor.eff.org/download.html.en Manual for Windows setup http://tor.eff.org/docs/tor-doc-win32.html.en http://tor.eff.org/docs/tor-doc-win32.html.en
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CS@UML 28
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CS@UML 29 IE
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CS@UML 30 Tor Components Interne t WWWServer Vidalia Privoxy tor
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CS@UML 31 Tor Network Onion router list: C:\Documents and Settings\fu\Application Data\Tor\cached-status Client Application Server Tor Network Directory Server Legend: Client or Server or Onion Router Onion Router Directory Server
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CS@UML 32 References D. Chaum, (1981), Untraceable electronic mail, return addresses, and digital pseudonyms, Communications of the ACM, Vol. 24, No. 2, February, pp. 84--88.Untraceable electronic mail, return addresses, and digital pseudonyms Andrei Serjantov, Roger Dingledine and Paul Syverson, From a Trickle to a Flood: Active Attacks on Several Mix Types, In Proceedings of the Information Hiding Workshop, 2002From a Trickle to a Flood: Active Attacks on Several Mix Types Andreas Pfitzmann et al., Anonymity, Unobservability, and Pseudonymity – A Proposal for Terminology, 2000,Anonymity, Unobservability, and Pseudonymity – A Proposal for Terminology Xinwen Fu, welcome to Xinwen Fu’s homepage, http://www.homepages.dsu.edu/fux/, 2007 http://www.homepages.dsu.edu/fux/ Cisco Systems, Inc., Catalyst 2950 and Catalyst 2955 Switch Software Configuration Guide, 12.1(19)EA1, 2007Catalyst 2950 and Catalyst 2955 Switch Software Configuration Guide, 12.1(19)EA1 Cisco Systems, Inc., Catalyst 2900 Series Configuration Guide and Command Ref, 2007Catalyst 2900 Series Configuration Guide and Command Ref
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