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1 SANS Technology Institute - Candidate for Master of Science Degree 1 The Afterglow Effect and Peer 2 Peer Networks Jay Radcliffe June 2010 GIAC: GSEC.

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Presentation on theme: "1 SANS Technology Institute - Candidate for Master of Science Degree 1 The Afterglow Effect and Peer 2 Peer Networks Jay Radcliffe June 2010 GIAC: GSEC."— Presentation transcript:

1 1 SANS Technology Institute - Candidate for Master of Science Degree 1 The Afterglow Effect and Peer 2 Peer Networks Jay Radcliffe June 2010 GIAC: GSEC Gold, GCIH Gold, GCIA Gold, GCFA, GLEG, GLIT, GSPA, GLDR, GPEN, GWAPT

2 SANS Technology Institute - Candidate for Master of Science Degree 2 Objective How statistical analysis can be used to view network connections? What type of connection patterns can be found in peer to peer afterglow traffic? Can any type of pattern or markers be identified that could indicate malicious post-termination connections?

3 SANS Technology Institute - Candidate for Master of Science Degree 3 What is P2P Networking? Peer to Peer networking is a distributed architecture designed to make file sharing more efficient. Bit Torrent is a P2P methodology using trackers to track who is participating in the sharing of a single torrent which may contain one or more files.

4 SANS Technology Institute - Candidate for Master of Science Degree 4 P2P Afterglow An “Afterglow” connection is one that occurs after the client has terminated the P2P session. The tracker will remove the IP address from the list of participating clients after a certain period of time, usually less then 20 minutes

5 SANS Technology Institute - Candidate for Master of Science Degree 5 Test Setup Client sits behind a firewall with a monitoring box running snort Snort rules setup to record new TCP connections (SYN only) and UDP connections on the specified unique port number

6 SANS Technology Institute - Candidate for Master of Science Degree 6 Test Conditions Initiate a Bit Torrent P2P session using a Fedora Installation DVD ISO image. Terminate torrent session after twelve hours. Continue monitoring for 14 hours after termination tracking afterglow connections

7 SANS Technology Institute - Candidate for Master of Science Degree 7 Test Data Results Connections will be tallied in 10 minute increments (00:00-00:10: 20 connections)

8 SANS Technology Institute - Candidate for Master of Science Degree 8 Results (Quantitative) Data had non-standard distribution. This skews typical statistical analysis. All three test runs had wide variance in standard deviation and skew. Trial #1Trial #2Trial #3 N 170312526 Mean (SD) 1.54 (3.41) 9.99 (17.05) 15.31 (60.66) Skew 3.385.5154.92 Kurtosis 13.720.28176.60

9 SANS Technology Institute - Candidate for Master of Science Degree 9 Results (Qualitative)

10 SANS Technology Institute - Candidate for Master of Science Degree 10 Results (Source Country) Using Whois/ARIN data to lookup the source countries of the afterglow connections Trial #1Trial #2Trial #3 USA26.77%USA29.73%USA20.36% Brazil24.80%China7.68%Brazil6.41% Poland7.87%France4.87%Russia5.81% Thailand7.87% Great Britain4.55%Canada5.23% Russia7.48% Netherlan ds4.29%China4.47%

11 SANS Technology Institute - Candidate for Master of Science Degree 11 Unique Anomaly

12 SANS Technology Institute - Candidate for Master of Science Degree 12 Unique Anomaly Theories on why there are spikes every two hours: –Unique client code (Timeout/retry, cached client list) –Dropped or Filtered Traffic –Malicious Retry to verify disconnection

13 SANS Technology Institute - Candidate for Master of Science Degree 13 Study Limitations Limited number of Trial runs Identical “safe” torrent files Wide variance in data connection rates

14 SANS Technology Institute - Candidate for Master of Science Degree 14 Directions for the Future Ideas for follow-up research –Client identification (Certain P2P clients might have a fingerprint or signature) –Packet Analysis (Flags or structure in Afterglow connections to identify malicious or non-typical connections) –Traffic Analysis (Do other protocols/attacks exhibit similar patterns like 2 hour retry with 5 attempts) –Torrent Variance (Movies, music, etc.)

15 SANS Technology Institute - Candidate for Master of Science Degree 15 Summary Certain qualitative statistical analysis can be used to look at network traffic for anomalies and patterns. Quantitative analysis is more difficult. Unexplained connection patterns exist in P2P afterglow connections.


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