Exploiting BitTorrent For Fun (But Not Profit)

1. Nikitas Liogkas, Robert Nelson, Eddie Kohler, Lixia Zhang University of California, Los Angeles Exploiting BitTorrent For Fun(But Not Profit)

2. Motivation • Robustness: system always provides useful service to all connected peers • depends on peers’ willingness to contribute • but uploading not in peers’ direct self interest • Fairness: those who do not contribute should not be able to receive good service • Can fairness violations reduce robustness?

3. Selfish peers • BitTorrent fairness model • rules for data exchange between peers • “tit-for-tat” for upload decisions • Selfishness: peers violate fairness while evading detection • abuse existing protocol mechanisms • is it effective (fairness violation)? • impact on honest peers (robustness reduction)?

4. Contributions • Designed and evaluated three selfish exploits • tools for measuring robustness • Despite selfishness, BitTorrent quite robust • at most 29% higher rates for the selfish peer • but no considerable degradation of service • How is this robustness achieved? • identify responsible protocol mechanisms • propose five guiding design principles

5. Presentation outline • BitTorrent operation • Implementation and methodology • Design and evaluation of exploits • Discussion • Conclusions • Future work

6. 2 4 3 1 tracker website seed/leecher new leecher BitTorrent – joining a torrent Peers divided into: • seeds:have the entire file • leechers: still downloading metadata file join peer list datarequest 1. obtain the metadata file 2. contact the tracker 3. obtain a peerlist (contains seeds & leechers) 4. contact peers from that list for data

7. leecher A seed leecher B leecher C BitTorrent – exchanging data I have ! ●Verify pieces using hashes ●Download sub-pieces in parallel ● Advertise received pieces to the entire peer list ● Look for the rarest pieces

8. leecher A seed leecher B leecher C leecher D BitTorrent - unchoking ● Periodically calculate data-receiving rates ● Upload to (unchoke) the fastest downloaders ● Optimistic unchoking ▪ periodically select a peer at random and upload to it▪ continuously look for the fastest partners

9. Presentation outline • BitTorrent operation • Implementation and methodology • Design and evaluation of exploits • Discussion • Conclusions • Future work

10. Implementation • implemented all three exploits in the Ctorrent client • ensured that our changes did not interfere with regular protocol operation • exploits do not exhaust all possibleselfish behavior… • but prove to be valuable tools for evaluating robustness

11. Experimental methodology • Private torrents • eight leechers & one seed on Planetlab • most torrents are small [Guo et al., IMC’05] • impose download and upload limits • leechers join according to Poisson • purpose: measure benefit to selfish (fairness), impact on honest (robustness) • Public torrents • two clients join the same torrent together • purpose: reveal impact in real settings

12. leecher A seed leecher B leecher C tracker Exploit 1 – Downloading only from seeds new listrequest peer list ● Download only from seeds; no need to upload ● Repeatedly query the tracker for peer lists ● Distinguish the seeds, and receive data from them ● Violates fairness model; also harmful to honest peers

13. 22% max 75%ile median 25%ile min Evaluation – Exploit 1in private torrents • Limit bandwidth of leechers 1 to 6. No limit on seed. • Modest fairness violation (22% better rate) when selfish is fast • Robustness does not suffer: most honest slower by <15% Download rates for all peers

14. Evaluation – Exploit 1with modified seed • Seed only unchokes one leecher at a time • Considerable fairness violation: selfish peer faster by 155% • Reduces robustness: honest peers slower by at least 32% Download rates for all peers 155%

15. Evaluation – Exploit 1in public torrents • Tested with small (< 20 peers) and large (> 150 peers) torrents • Selfish leecher gets consistently higher download rates (7-20%) • Does particularly well in torrents with many seeds • Greater incentive to cheat in popular torrents

16. leecher A leecher B leecher C leecher D Exploit 2 – Downloading only from the fastest peers I have ! ● Download only from fast peers, never waste time on slow ones ● Do not perform optimistic unchokes ● Observe frequency of piece advertisements to infer bandwidth of peers ● Especially harmful at the start of a peer’s lifetime

17. 29% Evaluation – Exploit 2in private torrents • Selfish peer interacts only with the two fastest leechers in its list • Modest fairness violation: selfish peer faster by 29% • Robustness does not suffer: impact on honest peers small Download rates for all peers

18. Evaluation – Exploit 2in public torrents • Exploit fails in public torrents • consistently lower download rates (1-30%) • Reasons • optimistic unchoking aids in discovering the best partners • short-term calculations beat our advertisement-based estimations • Mechanism for continuous adaptation is valuable

19. leecher A leecher B leecher C Exploit 3 – Advertisingfalse pieces 1 2 1 2 4 I have ! 3 garbage 1 2 3 ● Lie about the pieces you have ● Gradually advertise the rarest pieces ● Send garbage when you do not have a piece ▪ pollution is not primary objective

20. 22% Evaluation – Exploit 3in private torrents • Modest fairness violation: selfish peer faster by 22% • Robustness does not suffer; some of the honest peers even improve their rates! Download rates for all peers

21. Evaluation – Exploit 3in public torrents • Exploit fails in public torrents • modern implementations keep state about the origin of pieces • lying leechers easily detected • Remembering past interactions enables defending against false piece advertisements

22. Presentation outline • BitTorrent operation • Implementation and methodology • Design and evaluation of exploits • Discussion • Conclusions • Future work

23. Design principles • Parallel downloading • Memory of past interactions • Problem partitioning • Export minimal information • Keep the network connected

24. Principles #1 and #2 • Maintain parallel interactionswith multiple peers • example: limited impact of the download-only-from-seeds exploit • Maintain memoryof past interactions • example: failure of the false-advertisements exploit in public torrents • trade-off between robustness and performance

25. Principle #3 • Enforce problem partitioning [Shneidman et al., PODC’04] • “No peer should be able to influence another peer’s decision-making by declaring false information” • Not enforced by BitTorrent • Should decouple data needs (pieces) from the provided service (unchoking) • Could harm performance

26. Principles #4 and #5 • Export minimal information necessary • example: hide that you are a seed • super-seeding policy does just that • Keep the network connected • optimistic unchoking: random choice that aids robustness • value evident in the failure of the download-from-the fastest exploit in public torrents

27. Related work • Describes the basic BitTorrent mechanisms [Cohen, P2PECON’03] • Feasibility of selfish behavior in BitTorrent [Shneidman et al., PINS’04] • Theoretical analysis [Qiu et al., SIGCOMM’04] • Simulations [Bharambe et al., MSR-TR-2005] • Measurement studies [Izal et al., PAM’04, Pouwelse et al., Delft TR 2004 and IPTPS’05, Guo et al., IMC’05]

28. Conclusions • Presented three selfish exploits • BitTorrent quite robust, despite fairness violations • Identified protocol characteristics that enable robustness • Proposed five guiding design principles

29. Future work • Investigate combinations of exploits • Our exploits do not exhaust the complete space of selfish behavior • how to methodically design other (possibly more successful) exploits? • Selfish behavior in multi-torrent systems

30. Nikitas Liogkas, Robert Nelson, Eddie Kohler, Lixia Zhang Questions? Exploiting BitTorrent For Fun(But Not Profit)

31. Bonus slide – Exploit 1all-selfish scenario • Appears as if everyone benefits when everyone is being selfish • Artifact of the imposed bandwidth limits: seed serving similar clients • Degenerates into a client-server model Download rates for all peers