Evaluating Artificial Immune System Algorithms for Intrusion Detection

Over the years multiple algorithms have been published in the field of artificial immune systems. In this paper we evaluate the effectiveness of different immune inspired algorithms when used in intrusion detection. The focus of the work is the usage of publicly available implementations and current data sets to increase repeatability and relevance to real world applications. Our results indicate a good fit of the immune theory to the problem of intrusion detection, with further research being needed.