Abstract
Setting up an IDS architecture on ad-hoc network is hard because it is not easy to find suitable locations to setup IDS’s. One way is to divide the network into a set of clusters and put IDS on each cluster head. However traditional clustering techniques for ad-hoc network have been developed for routing purpose, and they tend to produce duplicate nodes or fragmented clusters as a result of utilizing maximum connectivity for routing. Most of recent clustering algorithm for IDS are also based on them and show similar problems. In this paper, we suggest to divide the network first into zones which are supersets of clusters and to control the clustering process globally within each zone to produce more efficient clusters in terms of connectivity and load balance. The algorithm is explained in detail and shows about 32% less load concentration in cluster heads than traditional techniques.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zhang, Y., Lee, W.: Intrusion Detection in Wireless Ad-Hoc Networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networks (MobiCom), Boston, USA (2000)
Sterne, D., Balasubramanyam, P., Carman, D., Wilson, B., Talpade, R., Ko, C., Balupari, R., Tseng, C.-Y., Bowen, T., Levitt, K., Rowe, J.: A General Cooperative Intrusion Detection Architecture for MANETs. In: Proceedings of the third IEEE International Workshop on Information Assurance (IWIA), College Park, MD, USA (2005)
Kachirski, O., Guha, R.: Effective Intrusion Detection Using Multiple Sensors in Wireless Ad Hoc Networks. In: Proceedings of the 36th Hawaii International Conference on System Science (HICSS), Hawaii (2003)
Huang, Y., Lee, W.: A Cooperative Intrusion Detection System for Ad Hoc Networks. In: Proceedings of the ACM Workshop on Security in Ad Hoc and Sensor Networks (SASN), Fairfax, VA, USA (2003)
GloMoSim Simulator’s web site, http://pcl.cs.ucla.edu/projects/glomosim/
Brutch, P., Ko, C.: Challenges in Intrusion Detection for Wireless Ad-hoc Networks. In: 2003 Symposium on Applications and the Internet Workshops (SAINT), Orlando, Florida, USA (2003)
Marti, S., Giuli, T., Lai, K., Barker, M.: Mitigating Routing Misbehavior in Mobile Ad Hoc Networks. In: Proceedings of 6th International Conference on Mobile Computing and Networking (MobiCom), Boston, USA (2000)
Chatterjee, M., Das, S.K., Turgut, D.: WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks. Journal of Cluster Computing 5(2) (2002)
Zhou, L., Hass, L.J.: Securing ad hoc networks. IEEE Networks 13(6) (1999)
Li., Y., Wei, J.: Guidelines on Selecting Intrusion Detection Methods in MANET. In: The Proceedings of ISECON 2004, Newport (2004)
Bechler, M., Hof, H.-J., Kraft, D., Pählke, F., Wolf, L.: A Cluster-Based Security Architecture of Ad Hoc Networks. In: Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), Hong Kong, China (2004)
Toh, C.-K.: Ad Hoc Mobile Wireless Networks: Protocols and Systems. Prentice Hall PTR, Englewood Cliffs (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, IY., Kim, YS., Kim, KC. (2006). Zone-Based Clustering for Intrusion Detection Architecture in Ad-Hoc Networks. In: Kim, YT., Takano, M. (eds) Management of Convergence Networks and Services. APNOMS 2006. Lecture Notes in Computer Science, vol 4238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11876601_26
Download citation
DOI: https://doi.org/10.1007/11876601_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45776-3
Online ISBN: 978-3-540-46233-0
eBook Packages: Computer ScienceComputer Science (R0)