The full text of this article


A hybrid data mining anomaly detection technique in ad hoc networks
by Yu Liu, Yang Li, Hong Man, Wei Jiang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 2, No. 1, 2007


Abstract: Ad hoc network security mainly relies on defence mechanisms at each mobile node due to lack of infrastructure. For this reason, various intrusion detection techniques have been proposed for ad hoc networks. Developing Intrusion Detection Systems (IDS) for individual nodes in ad hoc network is challenging for a number of reasons, including resource constraints at each node and the difficulties to locate attack source for prompt response. In this paper, we propose a hybrid data mining anomaly detection technique for node-based IDS. Specifically, we incorporate two data mining techniques, that is, association-rule mining and cross-feature mining, to characterise normal behaviours of mobile nodes and detect anomalies by finding deviance from the norm. The advantage of our hybrid approach is that association-rule mining and cross-feature mining usually complement each other in time scale and sensitivity to different attack types. We investigate features of interest from both the medium access (MAC) layer and the network layer. Our intention of using the MAC layer features is to localise the attack source within one-hop perimeter. To preserve the precious energy of mobile nodes, we propose two compact feature sets, that is, direct feature set and statistical feature set, that target on short-term and long-term profiling of normal node behaviours, respectively. Considering the characteristic of audit data collected upon different feature sets, we apply association-rule mining to the short-term profiling and cross-feature mining to the long-term profiling. We validate our work through ns-2 simulation experiments. Experimental results show the effectiveness of our method.

Online publication date: Mon, 28-May-2007


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email