This paper studies a simplified form of LISYS, an artificial immune system for network intrusion detection. The paper describes results based on a new, more controlled data set than that used for earlier studies. The paper also looks at which parameters appear most important for minimizing false positives, as well as the trade-o#s and relationships among parameter settings.

this paper we outline the biological principles we believe to be most relevant to understanding and designing the computational networks of the future. Among the principles of living systems we see as most important to the development of robust software systems are: Modularity, autonomy, redundancy, adaptability, distribution, diversity, and use of disposable components. These are not exhaustive, simply the ones that we have found most useful in our own research. We then describe a prototype network intrusion-detection system, known as LISYS, which illustrates many of these principles. Finally, we present experimental data on LISYS' performance in a live network environment