title: An artificial bioindicator system for network intrusion detection.
abstract: An artificial bioindicator system is developed in order to solve a network intrusion detection problem. The system, inspired by an ecological approach to biological immune systems, evolves a population of agents that learn to survive in their environment. An adaptation process allows the transformation of the agent population into a bioindicator that is capable of reacting to system anomalies. Two characteristics stand out in our proposal. On the one hand, it is able to discover new, previously unseen attacks, and on the other hand, contrary to most of the existing systems for network intrusion detection, it does not need any previous training. We experimentally compare our proposal with three state-of-the-art algorithms and show that it outperforms the competing approaches on widely used benchmark data.
authors.affiliation: University of the Basque Country UPV/EHUIKERBASQUE.
authors.forename: Christian
authors.initials: C
authors.lastname: Blum
authors.affiliation: University of the Basque Country UPV/EHU.
authors.forename: José A
authors.initials: JA
authors.lastname: Lozano
authors.affiliation: University of the Basque Country UPV/EHUUniversidad Santo Tomás.
authors.forename: Pedro Pinacho
authors.initials: PP
authors.lastname: Davidson
keywords: Bioindicators; ecological approach to biological immune system; network intrusion detection; population of agents