Blasco Alís, JorgeOrfila Díaz-Pabon, AgustínRibagorda Garnacho, Arturo2010-11-122010-11-122010-022010 International Conference on Availability, Reliability and Security (ARES '10), pp. 327-332978-1-4244-5879-0https://hdl.handle.net/10016/9574Proceeding of: International Conference on Availability, Reliability, and Security, 2010. ARES '10, 15-18 February 2010, Krakow, PolandOne of the central areas in network intrusion detection is how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper we explore the use of Genetic Programming (GP) for such a purpose. Although GP has already been studied for this task, the inner features of network intrusion detection have been systematically ignored. To avoid the blind use of GP shown in previous research, we guide the search by means of a fitness function based on recent advances on IDS evaluation. For the experimental work we use a well-known dataset (i.e. KDD- 99) that has become a standard to compare research although its drawbacks. Results clearly show that an intelligent use of GP achieves systems that are comparable (and even better in realistic conditions) to top state-of-the-art proposals in terms of effectiveness, improving them in efficiency and simplicity.text/plainapplication/pdfeng© IEEEEffectivenessEfficiencyGPIntrusion detectionconference paperInformática10.1109/ARES.2010.53open access3273322010 International Conference on Availability, Reliability and Security (ARES '10)