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Dialog-based payload aggregation for intrusion detection

Published:04 October 2010Publication History

ABSTRACT

Network-based Intrusion Detection Systems (IDSs) such as Snort or Bro that have to analyze the packet payload for all the received data show severe performance problems if used in high-speed networks. Recent research results improve pattern matchers based on efficient algorithms or using specialized hardware. We approach the problem in a completely different way by considerably reducing the amount of data to be analyzed with only marginal impact on the detection quality. Dialog-based Payload Aggregation (DPA) uses TCP sequence numbers to decide which parts of the payload need to be analyzed by the IDS. Whenever a connection starts, or if the direction of the data transmission between peers changes, we forward the next N bytes of traffic to an attached IDS. All data transferred after the window is discarded. Our analysis using live network traffic and multiple Snort rulesets shows that most of the pattern matches occur at the beginning of connections or directly after direction changes in the data streams. According to our experimental results, our method reduces the data rate to be processed to around 1% in a typical network while retaining more than 98% of all detected events. Assuming a linear relationship between the data rate and processing time of an IDS, this results in a speedup of two magnitudes in the best case.

References

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  2. }}S. Kornexl, V. Paxson, H. Dreger, R. Sommer, and A. Feldmann. Building a Time Machine for Efficient Recording and Retrieval of High-Volume Network Traffic. In ACM IMC 2005, pages 267--272, Berkeley, CA, October 2005. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
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    • Published in

      cover image ACM Conferences
      CCS '10: Proceedings of the 17th ACM conference on Computer and communications security
      October 2010
      782 pages
      ISBN:9781450302456
      DOI:10.1145/1866307

      Copyright © 2010 Copyright is held by the author/owner(s)

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 4 October 2010

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      CCS '10 Paper Acceptance Rate55of325submissions,17%Overall Acceptance Rate1,261of6,999submissions,18%

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