Analysis of Human Immune System Inspired Intrusion Detection System
Artificial Immune Systems (AIS) are algorithms inspired by the human immune system. The human immune system is a robust, decentralized, error tolerant and adaptive system. Such properties are highly desirable for the development of novel computer systems. Unlike some other bio-inspired techniques, such as genetic algorithms and neural networks, the field of AIS encompasses a spectrum of algorithms to implement different functions. In this paper, the authors investigate CLONALG for network intrusion classification. The CLONal Selection ALGorithm (CLONALG) is inspired by the clonal selection theory of acquired immunity, which has shown success on broad range of engineering problem domains.