Evolving Intrusion Detection Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.7964

@InCollection{abraham:2006:GSP,

• author = "Ajith Abraham and Crina Grosan",
• title = "Evolving Intrusion Detection Systems",
• year = "2006",
• booktitle = "Genetic Systems Programming: Theory and Experiences",
• pages = "57--79",
• volume = "13",
• series = "Studies in Computational Intelligence",
• editor = "Nadia Nedjah and Ajith Abraham and Luiza {de Macedo Mourelle}",
• publisher = "Springer",
• address = "Germany",
• email = "ajith.abraham@ieee.org",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-29849-5",
• URL = "http://falklands.globat.com/~softcomputing.net/ids-chapter.pdf",
• DOI = "doi:10.1007/3-540-32498-4_3",
• abstract = "An Intrusion Detection System (IDS) is a program that analyses what happens or has happened during an execution and tries to find indications that the computer has been misused. An IDS does not eliminate the use of preventive mechanism but it works as the last defensive mechanism in securing the system. We evaluate the performances of two Genetic Programming techniques for IDS namely Linear Genetic Programming (LGP) and Multi-Expression Programming (MEP). Results are then compared with some machine learning techniques like Support Vector Machines (SVM) and Decision Trees (DT). Empirical results clearly show that GP techniques could play an important role in designing real time intrusion detection systems.",
• notes = "http://www.springer.com/sgw/cda/frontpage/0,11855,5-146-22-92733168-0,00.html",

}

Genetic Programming entries for Ajith Abraham Crina Grosan

Citations