Detecting Packet Dropping Attacks Using Emergent Self-Organizing Maps in Mobile Ad Hoc Networks

Paper in proceeding, 2006

The evolution of wireless network technologies and the recent advances in mobile computing hardware have made possible the introduction of various applications in mobile ad hoc networks. Not only is the infrastructure of these networks inherently vulnerable but they have increased requirements regarding their security as well. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient regarding security, we need a second line of defense, Intrusion Detection. The focus of this paper is on anomaly detection techniques in order to exploit their main advantage of being able to detect unknown attacks. First, we briefly describe intrusion detection systems and then we suggest a distributed schema applicable to mobile ad hoc networks. This anomaly detection mechanism is based on a neural network and is evaluated for packet dropping attacks using features selected from the MAC layer. The performance of the proposed architecture is evaluated under different traffic conditions and mobility patterns.