Abstract
Mobile ad-hoc wireless networks (MANET) are a significant area of research with many applications. MANETs are more vulnerable to malicious attack. Authentication and encryption techniques can be used as the first line of defense for reducing the possibilities of attacks. Alternatively, these approaches have several demerits and designed for a set of well known attacks. This paper proposes a cross layer intrusion detection architecture to discover the malicious nodes and different types of DoS attacks by exploiting the information available across different layers of protocol stack in order to improve the accuracy of detection. This approach uses a fixed width clustering algorithm for efficient detection of the anomalies in the MANET traffic and also for detecting newer attacks generated . In the association process, the Adaptive Association Rule mining algorithm is utilized. This helps to overcome the more time taken for performing the association process.
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