Improving Network Intrusion Detection by Means of Domain-Aware Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Blasco:2010:ARES,

• author = "Jorge Blasco and Agustin Orfila and Arturo Ribagorda",
• title = "Improving Network Intrusion Detection by Means of Domain-Aware Genetic Programming",
• booktitle = "International Conference on Availability, Reliability, and Security, ARES '10",
• year = "2010",
• month = feb,
• pages = "327--332",
• abstract = "One 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.",
• keywords = "genetic algorithms, genetic programming, domain-aware genetic programming, fitness function, intrusive traffic, network intrusion detection, normal traffic, security of data",
• DOI = "doi:10.1109/ARES.2010.53",
• notes = "Also known as \cite{5438073}",

}

Genetic Programming entries for Jorge Blasco Alis Agustin Orfila Diaz-Pabon D Arturo Ribagorda Garnacho

Citations