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Constructing attack scenarios through correlation of intrusion alerts

Published:18 November 2002Publication History

ABSTRACT

Traditional intrusion detection systems (IDSs) focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. In situations where there are intensive intrusions, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. This paper presents a practical technique to address this issue. The proposed approach constructs attack scenarios by correlating alerts on the basis of prerequisites and consequences of intrusions. Intuitively, the prerequisite of an intrusion is the necessary condition for the intrusion to be successful, while the consequence of an intrusion is the possible outcome of the intrusion. Based on the prerequisites and consequences of different types of attacks, the proposed approach correlates alerts by (partially) matching the consequence of some previous alerts and the prerequisite of some later ones. The contribution of this paper includes a formal framework for alert correlation, the implementation of an off-line alert correlator based on the framework, and the evaluation of our method with the 2000 DARPA intrusion detection scenario specific datasets. Our experience and experimental results have demonstrated the potential of the proposed method and its advantage over alternative methods.

References

  1. J. P. Anderson. Computer security threat monitoring and surveillance. Technical report, James P. Anderson Co., Fort Washington, PA, 1980.]]Google ScholarGoogle Scholar
  2. AT & T Research Labs. GraphViz - open source graph layout and drawing software. http://www.research.att.com/sw/tools/graphviz/.]]Google ScholarGoogle Scholar
  3. R. Bace. Intrusion Detection. Macmillan Technology Publishing, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. F. Cuppens and A. Miege. Alert correlation in a cooperative intrusion detection framework. In Proc. of the 2002 IEEE Symposium on Security and Privacy, May 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. F. Cuppens and R. Ortalo. LAMBDA: A language to model a database for detection of attacks. In Proc. of Recent Advances in Intrusion Detection (RAID 2000), pages 197--216, September 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. O. Dain and R. Cunningham. Fusing a heterogeneous alert stream into scenarios. In Proc. of the 2001 ACM Workshop on Data Mining for Security Applications, pages 1--13, Nov. 2001.]]Google ScholarGoogle Scholar
  7. H. Debar and A. Wespi. Aggregation and correlation of intrusion-detection alerts. In Recent Advances in Intrusion Detection, LNCS 2212, pages 85--103, 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. ISS, Inc. RealSecure intrusion detection system. http://www.iss.net.]]Google ScholarGoogle Scholar
  9. S. Jha, O. Sheyner, and J. Wing. Two formal analyses of attack graphs. In Proc. of the 15th Computer Security Foundation Workshop, June 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. MIT Lincoln Lab. 2000 DARPA intrusion detection scenario specific datasets. http://www.ll.mit.edu/IST/ideval/data/2000/2000_data_index.html, 2000.]]Google ScholarGoogle Scholar
  11. P. Ning, Y. Cui, and D. S. Reeves. Analyzing intensive intrusion alerts via correlation. In Proc. of the 5th Int'l Symposium on Recent Advances in Intrusion Detection (RAID 2002), October 2002.]]Google ScholarGoogle ScholarCross RefCross Ref
  12. P. Ning, Y. Cui, and D. S. Reeves. Constructing attack scenarios through correlation of intrusion alerts (full version). Technical Report TR-2002-13, North Carolina State University, Department of Computer Science, August 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. P. Ning and D. Xu. Adapting query optimization techniques for efficient intrusion alert correlation. Technical Report TR-2002-14, North Carolina State University, Department of Computer Science, September 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. R. Ritchey and P. Ammann. Using model checking to analyze network vulnerabilities. In Proc. of IEEE Symposium on Security and Privacy, pages 156--165, May 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. O. Sheyner, J. Haines, S. Jha, R. Lippmann, and J. Wing. Automated generation and analysis of attack graphs. In Proc. of IEEE Symposium on Security and Privacy, May 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. Staniford, J. Hoagland, and J. McAlerney. Practical automated detection of stealthy portscans. To appear in Journal of Computer Security, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. S. Templeton and K. Levit. A requires/provides model for computer attacks. In Proc. of New Security Paradigms Workshop, pages 31--38. September 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. Valdes and K. Skinner. Probabilistic alert correlation. In Proc. of the 4th Int'l Symposium on Recent Advances in Intrusion Detection (RAID 2001), pages 54--68, 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          CCS '02: Proceedings of the 9th ACM conference on Computer and communications security
          November 2002
          284 pages
          ISBN:1581136129
          DOI:10.1145/586110

          Copyright © 2002 ACM

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          Publication History

          • Published: 18 November 2002

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