In today’s competitive world, computer security is a high demand due to tremendous amount of network attacks. Various threats are affecting the network by gaining unauthorized access to the networks. The biological immune systems and particularly the Human Immune System (HIS) are an inspiration for defense that protects organisms against diverse threats. Biologically Inspired Algorithms (BIAs) addresses challenges faced by the current network. Such networks will require more scalability, adaptive and robust designs to address the dynamic changes and potential failures caused by large scale networks. A variety of biological algorithms demonstrate characteristics desirable for a good network design such as the Negative Selection Algorithm, Clonal Selection Algorithm and the Danger theory. This paper presents an AIS based intrusion detection mechanism in which negative selection algorithm is used for the generation of detectors which are the anti- bodies who mainly play the role of detecting the intruders. This paper starts with an (1) Introduction; (2) Background study of the Human Immune System ;(3) Negative Selective Algorithm in generating detectors; (4) Related work ; (5) Proposed approach and algorithm ; and (6) A Comparison table of performance amongst our experimental results and the existing results. We consider, Artificial Immune System (AIS) techniques an appealing approach for designing IDS which provides distributed detection through its lymphocytes.
Volume 11 | 04-Special Issue
Pages: 2564-2572