Pseudo Trust : Zero-Knowledge Based Authentication in Anonymous Peer-to-Peer Protocols

1. Pseudo Trust: Zero-Knowledge Based Authentication in Anonymous Peer-to-Peer Protocols Li Lu, Lei Hu State Key Lab of Information Security, Graduate School of Chinese Academy of Sciences Jinsong Han, Yunhao Liu, Lionel M. Ni Dept. of Computer Science and Engineering, Hong Kong University of Science and Technology Jinpeng Huai School of Computer Science, State Key Lab of Software Developing Environment, Beihang University

2. Authentication • To make one person trust another one. • Who is talking to whom must be as valid as whom he or she claimed. • Is he/she the valid person who is searching a public database? • Is he/she the valid person who provide you a movie without virus? • Is the collaborating company legal? • Is a cheater who send you an e-mail?

3. However… • Your machine may be accessed by a hacker. • You may receive fraudulent. advertisement via e-mail. • The goal of authentication: A host will communicate with a server while he can determine its identity.

4. Anonymity or Privacy • the right to be let alone: one of the rights most cherished by people. • Who is talking to whom should be confidential or private in the Internet. • Who is searching a public database? • Which movie are you downloading? • Which companies are collaborating? • Who are you talking to via e-mail?

5. However… • Your machine’s IP uniquely identifies you across web sites. • Nothing illegal about cross-referencing. • The goal of Internet anonymity: A host can communicate with a server while nobody can determine its identity www.ticket-agency.com www.insurance-advertisement.com

6. Previous approaches: Authentication • Authentication in P2P is used to help evaluating reputations of peers. To know Who want to download or searching from Whom. • Indeed, current P2P trust designs are identity-based, where one peer does not trust another before knowing its identity. • Not trying to protect the identity’s anonymity of peers.

7. Previous approaches: Anonymity • Anonymity is the state of being indistinguishable from other members of some group. Don’t know Who is Searching or DownloadingWhat from Whom. • Main goal is to hide initiator’s and responder’s real identities, such as IP address, post address, etc. • Not trying to authenticate the validity of peers.

8. IPC B B IPC IPD IPB IPC IPD IPD IPD D M M M D D C C C Anonymity Examples: Mix& Onion A B C D ABCD IPC Public keys IP IPD M

9. Anonymity Example: APFS Server Client However, APFS is just for file delivery, without identity authentication.

10. Tradeoff • Authentication is Identity-based • Leaking the real identity of peer, such as IP address, post address… • Anonymity is to hide the identity. • Vulnerable to many active attacks, especially impersonation and man-in-middle-attack.

11. Basic goal: A New Mutual Anonymity Authentication for P2P • Non ID-based authentication • No need to know real identity of peer before authentication. • Pseudonym-based authentication. • Invulnerable to many active attacks. • Impersonation • Man-in-Middle-Attack • Replay… • Lightweight: efficient pseudonym generation and authentication.

12. Query and Downloading in Unstructured P2P Systems • Flooding based query • Reversed path based response • Direct downloading Initiator Query Responder Response Downloading

13. Pseudonym generation We use cryptographic hash function to generate pseudonym PI: Where moduli , and are two big primes. These two primes are kept as peer’s secrets. Due to the one-way and collision-resistant properties of hash function, a malicious peer cannot impersonate other peer’s pseudonym.

14. Tail node Onion Path Flooding Our Design: Pseudo Trust Query Sending Responder R Query q Initiator I

15. Tail node Onion Path between R and Onion Path between I and Tail node TCP Link Response Responder R Response; prove your pseudonym. Query q Initiator I

16. Tail node Onion Path between R and Tail node TCP Link Mutual authentication Responder R Proof verification Challenge message Request verification Authentication request Proof generation Initiator I Onion Path between I and Similar procedure for Initiator authenticating responder Responder authenticates initiator.

17. Remarks on mutual authentication • The zero-knowledge identification protocol is used to implement pseudonym-base authentication. • Session key exchange is embedded in the mutual authentication. • After authentication, initiator and responder can use the session key to protect file confidentiality and integrity. For example, using symmetric-key encryption and massage authentication code.

18. Several important issues • Security • Anonymity degree • Impersonation • Man-in-Middle-attack • Overhead • Traffic overhead • Cryptographic overhead • Response time of queries

19. Security Analysis • Completely anonymity • Resistant to impersonation and replay. • Man-in-Middle attacker gets nothing from authentication • Resistant to inner attacks • Tail nodes are attackers. • Initiator or responder is attack.

20. Trace Driven Simulation • Physic network: Gnutella • Overlay network: DSS Clip2 trace • In a variety of network sizes ranging from hundreds to thousands. • For each simulation, we take the average result from 1,000 runs.

21. Response Time • The response time of APFS is approximately 3 times that of overt Gnutella, while PT is around 7 times that of overt Gnutella. • The time consumed in anonymous paths of PT constitutes a major part of the whole latency. • The time consumption of authentication is indeed trivial.

22. Traffic Overhead • The figure above plots the extra traffic cost brought about by authentication procedures. • Traffic stretch is defined as the traffic cost ratio between PT plus Gnutella, and Gnutella only

23. Prototype Implementation • We implemented a prototype in our labs at the Chinese Academy of Sciences, the campus of Beihang University and Hong Kong University of Science and Technology. • We test: • The extra computation overhead caused by PT. • Overall latency of pseudo identity authentication procedures in the Internet environment

24. Computational Overhead Proof generation Pseudonym certificate generation Verification

25. Time Consumption in Message Transmission CANtest MAN test WAN test

26. Thank you！ Li Lu, Lei Hu State Key Lab of Information Security, Graduate School of Chinese Academy of Sciences Jinsong Han, Yunhao Liu, Lionel M. Ni Dept. of Computer Science and Engineering, Hong Kong University of Science and Technology Jinpeng Huai School of Computer Science, State Key Lab of Software Developing Environment, Beihang University