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IFIP Annual Conference on Data and Applications Security and Privacy

DBSec 2006: Data and Applications Security XX pp 119–132Cite as

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Interactive Analysis of Attack Graphs Using Relational Queries

Interactive Analysis of Attack Graphs Using Relational Queries

  • Lingyu Wang18,
  • Chao Yao18,
  • Anoop Singhal19 &
  • …
  • Sushil Jajodia18 
  • Conference paper
  • 672 Accesses

  • 14 Citations

Part of the Lecture Notes in Computer Science book series (LNISA,volume 4127)

Abstract

Attack graph is important in defending against well-orchestrated network intrusions. However, the current analysis of attack graphs requires an algorithm to be developed and implemented, causing a delay in the availability of analysis. Such a delay is usually unacceptable because the needs for analyzing attack graphs may change rapidly in defending against network intrusions. An administrator may want to revise an analysis upon observing its outcome. Such an interactive analysis, similar to that in decision support systems, is difficult if at all possible with current approaches based on proprietary algorithms. This paper removes the above limitation and enables interactive analysis of attack graphs. We devise a relational model for representing necessary inputs including network configuration and domain knowledge. We generate the attack graph from those inputs as relational views. We then show that typical analyses of the attack graph can be realized as relational queries against the views. Our approach eliminates the needs for developing a proprietary algorithm for each different analysis, because an analysis is now simply a relational query. The interactive analysis of attack graphs is now possible, because relational queries can be dynamically constructed and revised at run time. Moreover, the mature optimization techniques in relational databases can also improve the performance of the analysis.

Keywords

  • Domain Knowledge
  • Intrusion Detection
  • Interactive Analysis
  • Goal Condition
  • Computer Security

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This material is based upon work supported by National Institute of Standards and Technology Computer Security Division; by Homeland Security Advanced Research Projects Agency under the contract FA8750-05-C-0212 administered by the Air Force Research Laboratory/Rome; by Army Research Office under grants DAAD19-03-1-0257 and W911NF-05-1-0374, by Federal Aviation Administration under the contract DTFAWA-04-P-00278/0001, and by the National Science Foundation under grants IIS-0242237 and IIS-0430402. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsoring organizations.

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References

  1. Ammann, P., Wijesekera, D., Kaushik, S.: Scalable, graph-based network vulnerability analysis. In: Proceedings of the 9th ACM Conference on Computer and Communications Security (CCS 2002), pp. 217–224 (2002)

    Google Scholar 

  2. Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to Algorithms. MIT Press, Cambridge (1990)

    MATH  Google Scholar 

  3. Cuppens, F., Miege, A.: Alert correlation in a cooperative intrusion detection framework. In: Proceedings of the 2002 IEEE Symposium on Security and Privacy (S&P 2002), pp. 187–200 (2002)

    Google Scholar 

  4. Dacier, M.: Towards quantitative evaluation of computer security. Ph.D. Thesis, Institut National Polytechnique de Toulouse (1994)

    Google Scholar 

  5. Deraison, R.: Nessus scanner (1999), available at: http://www.nessus.org

  6. Farmer, D., Spafford, E.H.: The COPS security checker system. In: USENIX Summer, pp. 165–170 (1990)

    Google Scholar 

  7. Gray, J., Bosworth, A., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., Pirahesh, H.: Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Mining and Knowledge Discovery 1(1), 29–53 (1997)

    CrossRef  Google Scholar 

  8. Jajodia, S., Noel, S., O’Berry, B.: Topological analysis of network attack vulnerability. In: Kumar, V., Srivastava, J., Lazarevic, A. (eds.) Managing Cyber Threats: Issues, Approaches and Challenges. Kluwer Academic Publishers, Dordrecht (2003)

    Google Scholar 

  9. Jha, S., Sheyner, O., Wing, J.M.: Two formal analysis of attack graph. In: Proceedings of the 15th Computer Security Foundation Workshop (CSFW 2002) (2002)

    Google Scholar 

  10. Ning, P., Cui, Y., Reeves, D.S.: Constructing attack scenarios through correlation of intrusion alerts. In: Proceedings of the 9th ACM Conference on Computer and Communications Security (CCS 2002), pp. 245–254 (2002)

    Google Scholar 

  11. Noel, S., Jajodia, S.: Correlating intrusion events and building attack scenarios through attack graph distance. In: Proceedings of the 20th Annual Computer Security Applications Conference (ACSAC 2004) (2004)

    Google Scholar 

  12. Noel, S., Jajodia, S., O’Berry, B., Jacobs, M.: Efficient minimum-cost network hardening via exploit dependency grpahs. In: Proceedings of the 19th Annual Computer Security Applications Conference (ACSAC 2003) (2003)

    Google Scholar 

  13. Ortalo, R., Deswarte, Y., Kaaniche, M.: Experimenting with quantitative evaluation tools for monitoring operational security. IEEE Trans. Software Eng. 25(5), 633–650 (1999)

    CrossRef  Google Scholar 

  14. Phillips, C., Swiler, L.: A graph-based system for network-vulnerability analysis. In: Proceedings of the New Security Paradigms Workshop (NSPW 1998) (1998)

    Google Scholar 

  15. Ramakrishnan, C.R., Sekar, R.: Model-based analysis of configuration vulnerabilities. Journal of Computer Security 10(1/2), 189–209 (2002)

    CrossRef  Google Scholar 

  16. Ritchey, R., Ammann, P.: Using model checking to analyze network vulnerabilities. In: Proceedings of the 2000 IEEE Symposium on Research on Security and Privacy (S&P 2000), pp. 156–165 (2000)

    Google Scholar 

  17. Ritchey, R., O’Berry, B., Noel, S.: Representing TCP/IP connectivity for topological analysis of network security. In: Proceedings of the 18th Annual Computer Security Applications Conference (ACSAC 2002), p. 25 (2002)

    Google Scholar 

  18. Sheyner, O., Haines, J., Jha, S., Lippmann, R., Wing, J.M.: Automated generation and analysis of attack graphs. In: Proceedings of the 2002 IEEE Symposium on Security and Privacy (S&P 2002), pp. 273–284 (2002)

    Google Scholar 

  19. Swiler, L., Phillips, C., Ellis, D., Chakerian, S.: Computer attack graph generation tool. In: Proceedings of the DARPA Information Survivability Conference & Exposition II (DISCEX 2001) (2001)

    Google Scholar 

  20. Wang, L., Liu, A., Jajodia, S.: An efficient and unified approach to correlating, hypothesizing, and predicting intrusion alerts. In: di Vimercati, S.d.C., Syverson, P.F., Gollmann, D. (eds.) ESORICS 2005. LNCS, vol. 3679, pp. 247–266. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  21. Zerkle, D., Levitt, K.: Netkuang - a multi-host configuration vulnerability checker. In: Proceedings of the 6th USENIX Unix Security Symposium (USENIX 1996) (1996)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Center for Secure Information Systems, George Mason University, Fairfax, VA, 22030-4444, USA

    Lingyu Wang, Chao Yao & Sushil Jajodia

  2. Computer Security Division, NIST, Gaithersburg, MD, 20899, USA

    Anoop Singhal

Authors
  1. Lingyu Wang
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  2. Chao Yao
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  3. Anoop Singhal
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  4. Sushil Jajodia
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Editor information

Editors and Affiliations

  1. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Italy

    Ernesto Damiani

  2. The Logistics Institute, Northeastern University, Shenyang, China

    Peng Liu

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© 2006 IFIP International Federation for Information Processing

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Cite this paper

Wang, L., Yao, C., Singhal, A., Jajodia, S. (2006). Interactive Analysis of Attack Graphs Using Relational Queries. In: Damiani, E., Liu, P. (eds) Data and Applications Security XX. DBSec 2006. Lecture Notes in Computer Science, vol 4127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11805588_9

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  • DOI: https://doi.org/10.1007/11805588_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36796-3

  • Online ISBN: 978-3-540-36799-4

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