CSCE 715 Ankur Jain 11/16/2010

Introduction Design Goals Framework SDT Protocol Achievements of Goals Overhead of SDT Conclusion

Peer-to-Peer systems Distributed application architecture Partitions task between peers equivalently. E.g. – Skype, Cloud Computing, P2PTV and many more. Fundamental Challenge Trust relationship between peers. Several research studies. To build trust and reputation between peers.

Reliability Computing true trust value. Presence of malicious user. Anonymity Non Identification of peers Accountability Identification of malicious peers. Previous research focused on reliability.

Overall Goal Extend P2P trust management systems To provide Witness Anonymity To provide anonymity to person reporting malicious behavior. To preserve privacy of peers. To hide trust topology from malicious parties.

Identity Anonymity Backward Anonymity Traceability Non-slanderability. Additional Goals Efficiency Decentralization.

System Model No Trusted Third Party. 2 types of user Offline Group Manager (OGM) User # of adversaries less than threshold t. Adversary Model 2 types of adversaries Malicious user Selfish user Will collude together to maximize the attack.

Network Model Mixnet based anonymous system Consist of series of servers called MIXes. Associated with public keys. Receives encrypted messages. Decrypts, batches, permutes, forwards messages. Strips off sender’s name and identifying information. Mechanism for monitoring claims sent Irrespective of claims being generated or forwarded.

SDT – Secure Deep Throat Provide anonymity and accountability together. Include tracing mechanism to identify user. 4 step procedure Setup Registration Claim Broadcasting Public Tracing Modes of Operation Active: Real Time requirements. Passive: Not strict Real Time requirements.

OGM generates public and secret keys. Identification list (LIST) initially empty. Define tag bases Used in claim broadcasting To create anonymous claims. Only one per type of misbehavior per user.

User contacts OGM. User selects identity. Check its availability. User obtains a member public/secret key pair. OGM adds a new entry to LIST. OGM select s items from LIST and sends it to user. User sends confirmation for key pair and LIST items received.

User maintain two databases. Maintains claim sent by herself. Maintains claim received from other user. On detecting malicious behavior Checks database for previous entries for same type of behavior. If not found generates new claim using tag base. Broadcast through anonymous communication system. Also stores claim in database.

On receiving claim Checks whether entry for that claim is present or not. If yes, then drops the claim. If not check its validity and stores the claim. Also forwards it in the system. Initializing Public Tracing User finds t claims. Checks distinctness of all t claims. Generates a message including t claims and broadcast it to network

Check for entries in databases. If found broadcast two entries as proof to disclose the identity of malicious user. If no entries found broadcast message NO-ONE. After receiving NO-ONE message other repeat the steps in their local LIST.

Used when real time requirement is not critical. Achieve better efficiency. Changes in claims broadcasting Claims regarding malicious behavior not sent immediately. Sent these claims only when queried about the behavior of user. Public tracing will performed on all claims to prevent multiple claims from an adversary.

Peer forwards claim with a probability. Instead of flooding entire network. Lower the probability, lower is the number of peers storing the claim. Lower is the probability that one peer stores every t distinct claims. Require more number of witnesses in this case. Also non zero probability that adversary may escape disclosure.

Identity Anonymity May be broken using Traffic Analysis or Protocol Analysis Traffic Analysis is prevented by Mixnet based communication system. Protocol Analysis is also hard to perform No public key in claim broadcasted All parameter are calculated using discrete algorithm so very robust against brute force attack.

Backward Anonymity Adversaries can compromise multiple peers. Claim does not provide information regarding identity. No way to differentiate the user on basis of claims. Also ensured when OGM and adversaries are in contact User’s secret key is only known to user. No way to extract secret key from OGM.

Traceability Good peers need to find a valid record of adversary from LIST. LIST items are distributed among different peers. Probability of all copies controlled by adversary group is very small.

Non-Slanderability Max number of claims sent by adversaries against a user Total number of adversaries which is less than t. Adversaries cannot collect enough claims to remove good user from the system.

Distributed storage of LIST OGM maintains LIST offline. LIST is stored in distributed form. Peers do not have knowledge of LIST items with other peers. Helps in detecting a adversary even if adversary is controlling the majority of LIST.

Communication Costs Major cost is forwarding claims. Implemented using elliptic curve or hyper elliptic curve over a finite field. Claim size not more than 409 bytes. LIST distribution another cost. Smaller the LIST, higher probability of message broadcast while tracing.

Storage Requirements For cryptographic keys, LIST and local databases. Storing personal keys and public key of OGM. Only small part of the entire LIST. Very small database requirement in passive mode. A probabilistic forwarding approach may reduce database space in active mode.

SDT provide witness anonymity to users reporting malicious behavior. Two modes of operation: Active and Passive. Overhead is acceptable in peer-to-peer systems.