The Pollution Attack in P2P Live Video Streaming: Measurement Results and Defenses

1. The Pollution Attack in P2P Live Video Streaming: Measurement Results and Defenses Prithula Dhungel Xiaojun Hei Keith W. Ross Nitesh Saxena Polytechnic University

2. The Pollution Attack • Attacker joins an ongoing video channel • Attacker advertises it has a large number of chunks • When neighbors request chunks, attacker sends bogus chunks • Receiver plays back bogus chunks • Each receiver may further forward the polluted chunks

3. Peer Peer request request Peer Polluter Peer Peer request Peer Peer 3

4. Contributions • Identified the pollution attack in P2P live video streaming applications • Verify via experimental results (in PPLive) that pollution attack can be devastating • Survey possible defenses against the attack

5. Pollution Experiment Figure: PPLive pollution experiment setup

6. Measurement Results (1) Figure: Number of peers viewing channel over experiment periods 6

7. Brooklyn Peer Figure: Clean and polluted chunks to/from Brooklyn peer

8. Hong Kong Peer Figure: Clean and polluted chunks to/from Hong Kong peer

9. Pollution Defense Mechanisms • Blacklisting • Traffic Encryption • Chunk Signing • Sign-All Approach • Signature-Amortization Approaches • Star Chaining • Merkle Tree • Sign-and-Correct Approach

10. Chunk Signing • Use PKI • Every video source has public-private key pair • Source uses private key to sign the chunks • Receiver uses public key of source to verify integrity of chunk

11. “Sign-All” (1) • Source • Source signs each chunk • Sends signature (“authentication information”) with corresponding chunk • Receiver • Verifies each chunk individually using authentication information and public key of source

12. “Sign-All” (2)  Chunk processing independence  Bandwidth overhead • For a stream of m chunks, m signatures For 372 kbps channel with chunk size of 4000 bytes, around 3%  Computation overhead - 1 (expensive) signature operation per chunk

13. “Block Signing” Chunks organized into blocks Each block contains n chunks After generating n chunks, hash concatenation of all hashes, and sign result Reduces computation But can’t verify individual chunks 13

14. “Star Chaining” • Chunks organized into blocks • Each block contains n chunks • After generating n chunks, calculate authentication information for each chunk • Signed hash of concatenation of all chunk hashes • Along with, all hashes of other n-1 chunks • Receiver, chunk by chunk: • Applies public key to get hash of hashes • Verifies by concatenating hash of current chunk with those of the n-1 chunks, and taking hash

15. “Star Chaining”  Computation overhead –> 1 signature per block  Loss–> If some chunks are lost in block, can still decode rest  Bandwidth overhead -> for block of n chunks, n-1 hashes + n signatures For channel of bitrate 372 kbps and chunk size of 4000 bytes, n = 32, about 16%

16. “Merkle Tree”  Computation overhead –> 1 signature per block  Loss–> If some chunks are lost in block, can still decode rest  Bandwidth overhead -> nlog2n hashes + n signatures (about 5%)

17. Conclusion • The pollution attack can be devastating • Defenses: • Signature Amortization (Merkle Tree) – less computational overhead and delay at receiver but more bandwidth overhead • Sign-and-Correct – less bandwidth requirement but higher processing delay and computational requirement • Based on requirements of the application, either of the two could be used

18. References [1] C. K.Wong and S. S. Lam. Digital signatures for flows and multicasts. IEEE/ACM Trans. Netw., 1999. [2] A. Lysyanskaya, R. Tamassia, and N. Triandopoulos. Multicast authentication in fully adversarial networks. In IEEE Symposium on Security and Privacy, 2004.

19. Thank You!