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Intrusion Detection System for Applications Using Linux Containers

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Security and Trust Management (STM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9331))

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Abstract

Linux containers are gaining increasing traction in both individual and industrial use, and as these containers get integrated into mission-critical systems, real-time detection of malicious cyber attacks becomes a critical operational requirement. This paper introduces a real-time host-based intrusion detection system that can be used to passively detect malfeasance against applications within Linux containers running in a standalone or in a cloud multi-tenancy environment. The demonstrated intrusion detection system uses bags of system calls monitored from the host kernel for learning the behavior of an application running within a Linux container and determining anomalous container behavior. Performance of the approach using a database application was measured and results are discussed.

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References

  1. Alarifi, S., Wolthusen, S.: Detecting anomalies in IaaS environments through virtual machine host system call analysis. In: International Conference for Internet Technology and Secured Transactions, pp. 211–218. IEEE (2012)

    Google Scholar 

  2. Alarifi, S., Wolthusen, S.: Anomaly detection for ephemeral cloud IaaS virtual machines. In: Lopez, J., Huang, X., Sandhu, R. (eds.) NSS 2013. LNCS, vol. 7873, pp. 321–335. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  3. Chen, Y., Ghorbanzadeh, M., Ma, K., Clancy, C., McGwier, R.: A hidden markov model detection of malicious android applications at runtime. In: 2014 23rd Wireless and Optical Communication Conference (WOCC), pp. 1–6, May 2014

    Google Scholar 

  4. Cho, S.B., Park, H.J.: Efficient anomaly detection by modeling privilege flows using hidden markov model. Comput. Secur. 22(1), 45–55 (2003)

    Article  Google Scholar 

  5. Cohen, W.W.: Fast effective rule induction. In: Proceedings of the Twelfth International Conference on Machine Learning, Lake Tahoe, California (1995)

    Google Scholar 

  6. Damele, B., Stampar, M.: sqlmap: Automatic SQL injection and database takeover tool (2015). http://sqlmap.org

  7. Forrest, S., Hofmeyr, S., Somayaji, A., Longstaff, T.: A sense of self for unix processes. In: Proceedings of the 1996 IEEE Symposium on Security and Privacy, pp. 120–128, May 1996

    Google Scholar 

  8. Fuller, D., Honavar, V.: Learning classifiers for misuse and anomaly detection using a bag of system calls representation. In: Proceedings of the Sixth Annual IEEE Systems, Man and Cybernetics (SMC) Information Assurance Workshop, pp. 118–125. IEEE (2005)

    Google Scholar 

  9. Helsley, M.: LXC: Linux container tools. IBM developerWorks Technical Library (2009)

    Google Scholar 

  10. Hoang, X.D., Hu, J., Bertok, P.: A multi-layer model for anomaly intrusion detection using program sequences of system calls. In: Proceedings of the 11th IEEE International Conference on Networks, pp. 531–536 (2003)

    Google Scholar 

  11. Hofmeyr, S., Forrest, S., Somayaji, A.: Intrusion detection using sequences of system calls. J. Comput. Secur. 6(3), 151–180 (1998)

    Article  Google Scholar 

  12. Lee, W., Stolfo, S.J.: Data mining approaches for intrusion detection. In: Usenix Security (1998)

    Google Scholar 

  13. Merkel, D.: Docker: lightweight linux containers for consistent development and deployment. Linux J. 2014(239), 2 (2014)

    Google Scholar 

  14. Murtaza, S.S., Khreich, W., Hamou-Lhadj, A., Couture, M.: A host-based anomaly detection approach by representing system calls as states of kernel modules. In: 2013 IEEE 24th International Symposium onSoftware Reliability Engineering (ISSRE), pp. 431–440. IEEE (2013)

    Google Scholar 

  15. Mutz, D., Valeur, F., Vigna, G., Kruegel, C.: Anomalous system call detection. ACM Trans. Inf. Syst. Secur. (TISSEC) 9(1), 61–93 (2006)

    Article  Google Scholar 

  16. Oracle Corporation: mysqlslap - Load Emulation Client (2015). http://dev.mysql.com/doc/refman/5.6/en/mysqlslap.html

  17. Petazzoni, J.: Containers & Docker: How Secure Are They? (2013). http://blog.docker.com/2013/08/containers-docker-how-secure-are-they

  18. Wang, W., Guan, X.H., Zhang, X.L.: Modeling program behaviors by hidden markov models for intrusion detection. In: Proceedings of 2004 International Conference on Machine Learning and Cybernetics, vol. 5, pp. 2830–2835. IEEE (2004)

    Google Scholar 

  19. Warrender, C., Forrest, S., Pearlmutter, B.: Detecting intrusions using system calls: alternative data models. In: Proceedings of the 1999 IEEE Symposium on Security and Privacy, pp. 133–145 (1999)

    Google Scholar 

  20. Yeung, D.Y., Ding, Y.: Host-based intrusion detection using dynamic and static behavioral models. Pattern Recogn. 36(1), 229–243 (2003)

    Article  MATH  Google Scholar 

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Acknowledgment

This work was funded by Northrop Grumman Corporation via a partnership agreement through S2ERC; an NSF Industry/University Cooperative Research Center. We would like to express our appreciation to Donald Steiner and Joshua Shapiro for their support and collaboration efforts in this work

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Correspondence to Amr S. Abed .

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Abed, A.S., Clancy, C., Levy, D.S. (2015). Intrusion Detection System for Applications Using Linux Containers. In: Foresti, S. (eds) Security and Trust Management. STM 2015. Lecture Notes in Computer Science(), vol 9331. Springer, Cham. https://doi.org/10.1007/978-3-319-24858-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-24858-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24857-8

  • Online ISBN: 978-3-319-24858-5

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