Abstract—Networks are protected using many firewalls and encryption software’s. But many of them are not sufficient and effective. Most intrusion detection systems for mobile ad hoc networks are focusing on either routing protocols or its efficiency, but it fails to address the security issues. Some of the nodes may be selfish, for example, by not forwarding the packets to the destination, thereby saving the battery power. Some others may act malicious by launching security attacks like denial of service or hack the information. The ultimate goal of the security solutions for wireless networks is to provide security services, such as authentication, confidentiality, integrity, anonymity, and availability, to mobile users. This paper incorporates agents and data mining techniques to prevent anomaly intrusion in mobile adhoc networks. Home agents present in each system collects the data from its own system and using data mining techniques to observed the local anomalies. The Mobile agents monitoring the neighboring nodes and collect the information from neighboring home agents to determine the correlation among the observed anomalous patterns before it will send the data. This system was able to stop all of the successful attacks in an adhoc networks and reduce the false alarm positives.
—Mobile agents, Intrusion detection system, Adhoc networks, Network Security.
R. Nakkeeran is with the Department of Computer Science and Engineering, Dr Pauls engineering College (Affiliated to Anna University, Chennai), Vanur Taluk, Villupuram -605 109, India. (Phone: +91 9787718933; +91 4142 329090)
S T. Aruldoss Albert is with the University Department of Electrical Engineering, Anna University Coimbatore, Coimbatore - 641 013, India.
R. Ezumalai is with the Department of Computer Science and Engineering, Dr Pauls engineering College (Affiliated to Anna University, Chennai)., Vanur Taluk, Villupuram -605 109, India. (Phone: +91 9345486422).
Cite: R. Nakkeeran, T. Aruldoss Albert and R. Ezumalai, "Agent Based Efficient Anomaly Intrusion Detection System in Adhoc networks," International Journal of Engineering and Technology
vol. 2, no. 1, pp. 52-56, 2010.