Abstract
The security of the networking infrastructure (e.g., routers and switches) in large scale enterprise or Internet service provider (ISP) networks is mainly achieved through mechanisms such as access control lists (ACLs) at the edge of the network and deployment of centralized AAA (authentication, authorization and accounting) systems governing all access to network devices. However, a misconfigured edge router or a compromised user account may put the entire network at risk. In this paper, we propose enhancing existing security measures with an intrusion detection system overseeing all network management activities. We analyze device access logs collected via the AAA system, particularly TACACS+, in a global tier-1 ISP network and extract features that can be used to distinguish normal operational activities from rogue/anomalous ones. Based on our analyses, we develop a real-time intrusion detection system that constructs normal behavior models with respect to device access patterns and the configuration and control activities of individual accounts from their long-term historical logs and alerts in real-time when usage deviates from the models. Our evaluation shows that this system effectively identifies potential intrusions and misuses with an acceptable level of overall alarm rate.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
Anderson, J.P.: Computer security threat monitoring and surveillance. Technical Report James P Anderson Co Fort Washington Pa, p. 56 (1980)
Carrel, D., Grant, L.: The TACACS+ protocol (January 1997)
Dreger, H., Feldmann, A., Mai, M., Paxson, V., Sommer, R.: Dynamic application-layer protocol analysis for network intrusion detection. In: Proceedings of the 15th conference on USENIX Security Symposium, vol. 15. USENIX Association, Berkeley (2006)
Iglesias, J.A., Ledezma, A., Sanchis, A.: Creating User Profiles from a Command-Line Interface: A Statistical Approach. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 90–101. Springer, Heidelberg (2009)
Krishnamurthy, B., Sen, S., Zhang, Y., Chen, Y.: Sketch-based change detection: methods, evaluation, and applications. In: Proceedings of the 3rd ACM SIGCOMM Conference on Internet Measurement, IMC 2003, pp. 234–247. ACM, New York (2003)
Li, Z., Xia, G., Gao, H., Tang, Y., Chen, Y., Liu, B., Jiang, J., Lv, Y.: Netshield: massive semantics-based vulnerability signature matching for high-speed networks. In: Proceedings of the ACM SIGCOMM 2010 Conference on SIGCOMM, SIGCOMM 2010, pp. 279–290. ACM, New York (2010)
Lunt, T.F., Jagannathan, R., Lee, R., Listgarten, S., Edwards, D.L., Neumann, P.G., Javitz, H.S., Valdes, A., Lunt, T.F., Jagannathan, R., Lee, R., Listgarten, S., Edwards, D.L., Neumann, P.G., Javitz, H.S., Valdes, A.: Ides: The enhanced prototype - a real-time intrusion-detection expert system. Tech. rep., SRI International, 333 Ravenswood Avenue, Menlo Park (1988)
Maggi, F., Matteucci, M., Zanero, S.: Detecting intrusions through system call sequence and argument analysis. IEEE Transactions on Dependable and Secure Computing 7, 381–395 (2010)
Maronna, R., Martin, R., Yohai, V.: Robust statistics: theory and methods. Wiley series in probability and statistics. J. Wiley (2006)
Maxion, R.: Masquerade detection using enriched command lines. In: Proc. of 2003 International Conference on Dependable Systems and Networks, pp. 5–14 (June 2003)
Paxson, V.: Bro: a system for detecting network intruders in real-time. Comput. Netw. 31, 2435–2463 (1999)
Rigney, C., Willens, S., Rubens, A., Simpson, W.: Remote authentication dial in user service, radius (2000)
Robertson, W., Maggi, F., Kruegel, C., Vigna, G.: Effective Anomaly Detection with Scarce Training Data. In: Proceedings of the Network and Distributed System Security Symposium (NDSS), San Diego, CA (February 2010)
Roesch, M.: Snort - lightweight intrusion detection for networks. In: Proceedings of the 13th USENIX Conference on System Administration, LISA 1999, pp. 229–238. USENIX Association, Berkeley (1999)
Salem, M.B., Stolfo, S.J.: A comparison of one-class bag-of-words user behavior modeling techniques for masquerade detection. Security and Communication Networks (2011)
Song, Y., Keromytis, A.D., Stolfo, S.J.: Spectrogram: A mixture-of-markov-chains model for anomaly detection in web traffic. In: NDSS. The Internet Society (2009)
Stefan, A.: Intrusion detection systems: A survey and taxonomy. Technical Report 99(Technical report 99-15), 1–15 (2000)
Suo, X., Zhu, Y., Owen, G.S.: Graphical passwords: A survey. In: Proceedings of the 21st Annual Computer Security Applications Conference, pp. 463–472. IEEE Computer Society, Washington, DC (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chu, J., Ge, Z., Huber, R., Ji, P., Yates, J., Yu, YC. (2012). ALERT-ID: Analyze Logs of the Network Element in Real Time for Intrusion Detection. In: Balzarotti, D., Stolfo, S.J., Cova, M. (eds) Research in Attacks, Intrusions, and Defenses. RAID 2012. Lecture Notes in Computer Science, vol 7462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33338-5_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-33338-5_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33337-8
Online ISBN: 978-3-642-33338-5
eBook Packages: Computer ScienceComputer Science (R0)