skip to main content
10.1145/2382196.2382306acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
poster

Network-based intrusion detection systems go active!

Authors Info & Claims
Published:16 October 2012Publication History

ABSTRACT

In this work we investigate a new approach for detecting network-wide attacks that aim to degrade the network's Quality of Service (QoS). To this end, a new network-based intrusion detection system (NIDS) is proposed. In contrast to the passive approach which most contemporary NIDS follow and which relies solely on production traffic monitoring, the propose NIDS takes the active approach where special crafted probes are sent according to a known probability distribution in order to monitor the network for anomalous behavior. The proposed approach takes away much of the variability of network traffic that makes it so difficult to classify, and therefore can detect subtle attacks which would not be detected passively. Furthermore, the active probing approach allows the NIDS to be effectively trained using only examples of the network's normal states, hence enabling an effective detection of zero-day attacks. Preliminary results on a real-life ISP network topology demonstrate the advantages of the proposed NIDS.

References

  1. Barford, P., Duffield, N., Ron, A., and Sommers, J. Network performance anomaly detection and localization. In INFOCOM 2009, IEEE (april 2009), pp. 1377--1385.Google ScholarGoogle ScholarCross RefCross Ref
  2. Bejerano, Y., and Rastogi, R. In INFOCOM 2009, IEEE.Google ScholarGoogle Scholar
  3. Kowalski, J. P., and Warfield, B. Modelling traffic demand between nodes in a telecommunications network. In in ATNAC (1995).Google ScholarGoogle Scholar
  4. Leland, W., Taqqu, M., Willinger, W., and Wilson, D. On the self-similar nature of ethernet traffic (extended version). Networking, IEEE/ACM Transactions on 2, 1 (feb 1994), 1 --15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Moy, J. OSPF version 2. IETF RFC 2328, Apr. 1998.Google ScholarGoogle Scholar
  6. Schölkopf, B., Platt, J. C., Shawe-taylor, J., Smola, A. J., and Williamson, R. C. Estimating the support of a high-dimensional distribution, 1999.Google ScholarGoogle Scholar
  7. Sommer, R., and Paxson, V. Outside the closed world: On using machine learning for network intrusion detection. In Security and Privacy (SP), 2010 IEEE Symposium on (may 2010), pp. 305--316. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Spring, N. T., Mahajan, R., and Wetherall, D. Measuring isp topologies with rocketfuel. In SIGCOMM (2002), pp. 133--145. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Varga, A., and Hornig, R. An overview of the omnet++ simulation environment. In SimuTools (2008), p. 60. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Witten, I. H., and Frank, E. Data Mining: Practical machine learning tools and techniques, 2nd edition ed. Morgan Kaufmann, San Francisco, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Network-based intrusion detection systems go active!

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CCS '12: Proceedings of the 2012 ACM conference on Computer and communications security
      October 2012
      1088 pages
      ISBN:9781450316514
      DOI:10.1145/2382196

      Copyright © 2012 Authors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 16 October 2012

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • poster

      Acceptance Rates

      Overall Acceptance Rate1,261of6,999submissions,18%

      Upcoming Conference

      CCS '24
      ACM SIGSAC Conference on Computer and Communications Security
      October 14 - 18, 2024
      Salt Lake City , UT , USA

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader