Abstract
Wireless sensor network (WSN) is vulnerable to a wide range of attacks due to its natural environment and inherent unreliable transmission. To protect its security, intrusion detection systems (IDSs) have been widely deployed in such a wireless environment. In addition, trust-based mechanism is a promising method in detecting insider attacks (e.g., malicious nodes) in a WSN. In this paper, we thus attempt to develop a trust-based intrusion detection mechanism by means of Bayesian model and evaluate it in the aspect of detecting malicious nodes in a WSN. This Bayesian model enables a hierarchical wireless sensor network to establish a map of trust values among different sensor nodes. The hierarchical structure can reduce network traffic caused by node-to-node communications. To evaluate the performance of the trust-based mechanism, we analyze the impact of a fixed and a dynamic trust threshold on identifying malicious nodes respectively and further conduct an evaluation in a wireless sensor environment. The experimental results indicate that the Bayesian model is encouraging in detecting malicious sensor nodes, and that the trust threshold in a wireless sensor network is more dynamic than that in a wired network.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Axelsson, S.: The Base-rate Fallacy and the Difficulty of Intrusion Detection. ACM Transactions on Information and System Security 3(3), 186–205 (2000)
Bao, F., Chen, I.-R., Chang, M., Cho, J.-H.: Trust-Based Intrusion Detection in Wireless Sensor Networks. In: Proceedings of the 2011 IEEE International Conference on Communications (ICC), pp. 1–6 (2011)
Bao, F., Chen, I.-R., Chang, M., Cho, J.-H.: Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection. IEEE Transactions on Network and Service Management 9(2), 169–183 (2012)
Beckwith, R., Teibel, D., Bowen, P.: Report from the Field: Results from an Agricultural Wireless Sensor Network. In: Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks, pp. 471–478 (2004)
Chen, X., Makki, K., Yen, K., Pissinou, N.: Sensor Network Security: A Survey. IEEE Communication Surveys & Tutorials 11(2), 52–73 (2009)
Chen, H., Wu, H., Hu, J., Gao, C.: Event-based Trust Framework Model in Wireless Sensor Networks. In: Proceedings of the 2008 International Conference on Networking, Architecture, and Storage (NAS), pp. 359–364 (2008)
Cheung, S.-Y., Varaiya, P.: Traffic Surveillance by Wireless Sensor Networks: Final Report. California PATH Research Report, UCB-ITS-PRR-2007-4. Institue of Transportation Studies, University of California, Berkeley (2007), http://www.its.berkeley.edu/publications/UCB/2007/PRR/UCB-ITS-PRR-2007-4.pdf
Cho, J.-H., Swami, A., Chen, I.-R.: A Survey on Trust Management for Mobile Ad Hoc Networks. IEEE Communications Surveys & Tutorials 13(4), 562–583 (2011)
Daabaj, K., Dixon, M., Koziniec, T., Lee, K.: Trusted Routing for Resource-Constrained Wireless Sensor Networks. In: Proceedings of the 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC), pp. 666–671 (2010)
Ganeriwal, S., Balzano, L.K., Srivastava, M.B.: Reputation-based Framework for High Integrity Sensor Networks. ACM Transitions on Sensor Network 4(3), 1–37 (2008)
Gonzalez, J.M., Anwar, M., Joshi, J.B.D.: A Trust-based Approach against IP-Spoofing Attacks. In: Proceedings of the 9th International Conference on Privacy, Security and Trust (PST 2011), pp. 63–70 (2011)
Ghosh, A.K., Wanken, J., Charron, F.: Detecting Anomalous and Unknown Intrusions Against Programs. In: Proceedings of the 1998 Annual Computer Security Applications Conference (ACSAC), pp. 259–267 (1998)
Grilo, A., Piotrowski, K., Langendoerfer, P., Casaca, A.: A Wireless Sensor Network Architecture for Homeland Security Application. In: Ruiz, P.M., Garcia-Luna-Aceves, J.J. (eds.) ADHOC-NOW 2009. LNCS, vol. 5793, pp. 397–402. Springer, Heidelberg (2009)
Guo, J., Marshall, A., Zhou, B.: A New Trust Management Framework for Detecting Malicious and Selfish Behaviour for Mobile Ad Hoc Networks. In: Proceedings of the 10th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 142–149 (2011)
Gupta, G., Younis, M.: Performance Evaluation of Load-Balanced Clustering of Wireless Sensor Networks. In: Proceedings of the 10th International Conference on Telecommunications (ICT), pp. 1577–1583 (2003)
Hutchison, K.: Wireless Intrusion Detection Systems. SANS GSEC Whitepaper, 1–18 (2005), http://www.sans.org/reading_room/whitepapers/wireless/wireless-intrusion-detection-systems_1543
Liu, K., Abu-Ghazaleh, N., Kang, K.-D.: Location Verification and Trust Management for Resilient Geographic Routing. Journal of Parallel and Distributed Computing 67(2), 215–228 (2007)
Meng, Y., Kwok, L.-F., Li, W.: Towards Designing Packet Filter with a Trust-Based Approach Using Bayesian Inference in Network Intrusion Detection. In: Keromytis, A.D., Di Pietro, R. (eds.) SecureComm 2012. LNICST, vol. 106, pp. 203–221. Springer, Heidelberg (2013)
Mishra, A., Nadkarni, K., Patcha, A.: Intrusion Detection in Wireless Ad-Hoc Networks. IEEE Wireless Communications 11(1), 48–60 (2004)
Porras, P.A., Kemmerer, R.A.: Penetration State Transition Analysis: A Rule-based Intrusion Detection Approach. In: Proceedings of the 8th Annual Computer Security Applications Conference (ACSAC), pp. 220–229 (1992)
Probst, M.J., Kasera, S.K.: Statistical Trust Establishment in Wireless Sensor Networks. In: Proceedings of the 2007 International Conference on Parallel and Distributed Systems (ICPADS), pp. 1–8 (2007)
Wang, F., Huang, C., Zhang, J., Rong, C.: IDMTM: A Novel Intrusion Detection Mechanism based on Trust Model for Ad-Hoc Networks. In: Proceedings of the 22nd IEEE International Conference on Advanced Information Networking and Applications (AINA), pp. 978–984 (2008)
Shaikh, R.A., Jameel, H., d’Auriol, B.J., Lee, H., Lee, S., Song, Y.J.: Group-based Trust Management Scheme for Clustered Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems 20(11), 1698–1712 (2009)
Sommer, R., Paxson, V.: Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. In: Proceedings of the 2010 IEEE Symposium on Security and Privacy, pp. 305–316 (2010)
Sun, Y., Luo, H., Das, S.K.: A Trust-Based Framework for Fault-Tolerant Data Aggregation in Wireless Multimedia Sensor Networks. IEEE Transactions on Dependable and Secure Computing 9(6), 785–797 (2012)
Sun, Y., Yu, W., Han, Z., Liu, K.: Information Theoretic Framework of Trust Modeling and Evaluation for Ad Hoc Networks. IEEE Journal on Selected Areas in Communications 24(2), 305–317 (2006)
Younis, O., Fahmy, S.: HEED: A Hybrid Energy Efficient, Distributed Clustering Approach for Ad Hoc Sensor Network. IEEE Transaction on Mobile Computing 3(3), 366–379 (2004)
Zahariadis, T., Trakadas, P., Leligou, H.C., Maniatis, S., Karkazis, P.: A Novel Trust-Aware Geographical Routing Scheme for Wireless Sensor Networks. Wireless Personal Communications, 1–22 (2012)
Zhang, J., Shankaran, R., Orgun, M.A., Varadharajan, V., Sattar, A.: A Dynamic Trust Establishment and Management Framework for Wireless Sensor Networks. In: Proceedings of the 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC), pp. 484–491 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Meng, Y., Li, W., Kwok, Lf. (2013). Evaluation of Detecting Malicious Nodes Using Bayesian Model in Wireless Intrusion Detection. In: Lopez, J., Huang, X., Sandhu, R. (eds) Network and System Security. NSS 2013. Lecture Notes in Computer Science, vol 7873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38631-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-38631-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38630-5
Online ISBN: 978-3-642-38631-2
eBook Packages: Computer ScienceComputer Science (R0)