Genetic algorithm and artificial immune systems: A combinational approach for network intrusion detection

Network Intrusion Detection is the most happening field of the network security research. It is a new kind of defense technology of the network security, used as a countermeasure to preserve data integrity and system availability during an intrusion. An ideal IDS system should be capable of evolving itself to identify not only known attacks but also unknown attacks. Algorithms based on Genetic Engineering and Immune Systems are known to evolve and learn from small examples. In this paper it is proposed to investigate the efficacy of genetic search methods for feature selection and Immune system to classify threats and non threats.