P2P Filesharing Population Tracking Based on Network Flow Data

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P2P Filesharing Population Tracking Based on Network Flow Data Arno Wagner, Thomas Dübendorfer, Lukas Hämmerle, Bernhard Plattner Contact: arno@wagner.name Communication Systems Laboratory Swiss Federal Institute of Technology Zurich (ETH Zurich)

Outline 1. Motivation 2. Setting 3. The PeerTracker 4. Validation by Polling 5. Comments on Legal Aspects 6. Conclusion Arno Wagner, ETH Zurich, ICISP 2006 p.1

Contributors Philipp Jardas, P2P Filesharing Systems: Real World NetFlow Traffic Characterization, Barchelor Thesis, ETH Zürich, 2004 Lukas Hämmerle, P2P Population Tracking and Traffic Characterization of Current P2P file-sharing Systems, Master Thesis, ETH Zürich, 2004 Roger Kaspar, P2P File-sharing Traffic Identification Method Validation and Verification, Semester Thesis, ETH Zürich, 2005 PDFs available from http://www.tik.ee.ethz.ch/~ddosvax/sada/ Arno Wagner, ETH Zurich, ICISP 2006 p.2

Motivation P2P traffic forms a large and dynamic part of the overall network traffic Identification of P2P traffic allows P2P anomaly detection Identification of P2P traffic allows better analysis of other traffic Arno Wagner, ETH Zurich, ICISP 2006 p.3

The DDoSVax Project http://www.tik.ee.ethz.ch/~ddosvax/ Collaboration between SWITCH (www.switch.ch, AS559) and ETH Zurich (www.ethz.ch) Aim (long-term): Near real-time analysis and countermeasures for DDoS-Attacks and Internet Worms Start: Begin of 2003 Funded by SWITCH and the Swiss National Science Foundation Arno Wagner, ETH Zurich, ICISP 2006 p.4

DDoSVax Data Source: SWITCH The Swiss Academic And Research Network.ch Registrar Links most Swiss Universities and CERN Carried around 5% of all Swiss Internet traffic in 2003 Around 60.000.000 flows/hour Around 300GB traffic/hour Flow archive (unsampled) since May 2003 Arno Wagner, ETH Zurich, ICISP 2006 p.5

What is a Flow? In the DDoSVax-Project: CISCO NetFlow v5. Basically unidirectional aggregated header information: Source and destination IP Protocol Source and destination port (TCP and UDP) Packet and byte count Start and end time stamp, 1ms accuracy Some routing information No payload information whatsoever Arno Wagner, ETH Zurich, ICISP 2006 p.6

P2P Networks Considered Signalling connection File transfer connection BitTorrent Azureus... BitTorrent Kademlia emule Client Server/ Supernode/ Tracker edonkey FastTrack/iMesh mldonkey Gnutella Overnet KaZaA imesh Grokster... LimeWire Bearshare Shareaza... Overnet edonkey2000... Arno Wagner, ETH Zurich, ICISP 2006 p.7

PeerTracker Algorithm Idea: Traverse P2P network from seeds Seeds: Seeds are peers using default ports (TCP and UDP) Keep a pool of peers for each network Add hosts that communicate with the pool Remove hosts that are idle Arno Wagner, ETH Zurich, ICISP 2006 p.8

Default Port Usage P2P System Default port usage (TCP) BitTorrent 70.0 % FastTrack 8.3 % Gnutella 58.6 % edonkey 55.6 % Overnet 83.9 % Kademlia 66.6 % From 8 day PeerTracker measurement end of 2004 Arno Wagner, ETH Zurich, ICISP 2006 p.9

PeerTracker: Hosts State Diagram Arno Wagner, ETH Zurich, ICISP 2006 p.10

Some PeerTracker Details Peers in the SWITCH network form core External hosts only identified if they contact core Different ageing for core and external hosts Dead core peers are still contacted from external peers Arno Wagner, ETH Zurich, ICISP 2006 p.11

Validation The PeerTracker does not look at Payloads Large error possible Validation Approach: Run PeerTracker Poll found peers immediately Compare polling and tracker results Arno Wagner, ETH Zurich, ICISP 2006 p.12

Peer Polling Methods P2P System Polling method FastTrack Request: GET /.files HTTP/1.0 Response: HTTP 1.0 403 Forbidden <number 1> <number 2> or HTTP/1.0 404 Not Found/nX-Kazaa-<username> Gnutella Request: GNUTELLA CONNECT/<version> Response: Gnutella <status> edonkey, Request: Binary: 0xE3 <length> 0x01 0x10 <MD4 hash> <ID> <port> Kademlia, Response: Binary: 0xE3... Overnet emule Same as edonkey, but replace initial byte with 0xC5. BitTorrent Unsolved. Seems to need knowledge of a shared file on the target peer. Arno Wagner, ETH Zurich, ICISP 2006 p.13

Polling Results P2P System TCP Connect P2P-client found edonkey, Kademlia, 50% 41% Overnet Gnutella 53% 30% FastTrack 51% 41% Total 51% 38% Table 1: Positive polling answers Arno Wagner, ETH Zurich, ICISP 2006 p.14

Polling Remarks Delay to polling < 10 Minutes About 50% unreachable via TCP and port seen by PeerTracker likely behind NAT Other errors: Peer variation (esp. Gnutella), classification into wrong network, tracker error BitTorrent not really pollable Arno Wagner, ETH Zurich, ICISP 2006 p.15

Legal Aspects (Warning: I am no legal expert) Flow data likely not subject to privacy laws (unless attempts to identify people are made) PeerTracker does not identify content shared output unproblematic, no action needs to be taken Identification of heavy hitters unproblematic, since payloads (shared contents) not identified Polling is unproblematic, since similar to running a peer (some users get nervous though...) Arno Wagner, ETH Zurich, ICISP 2006 p.16

PeerTracker for Law Enforcement Situation for CH! Massive private file-sharing is done Law enforcement is not really interested in copyright infringement Illegal contents (child pornography and the like) can be done far better with modified P2P clients Not really suitable Arno Wagner, ETH Zurich, ICISP 2006 p.17

Conclusion, Remarks Peer identification feasible with flow data Nodes with little traffic problematic BitTorrent problematic P2P filesharing still evolves PeerTracker code is available under GPL In productive use at ETH Zurich since 2005 Arno Wagner, ETH Zurich, ICISP 2006 p.18

Thank You! Arno Wagner, ETH Zurich, ICISP 2006 p.19