Can a good offense be a good defense? Vulnerability testing of anomaly detectors through an artificial arms race

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{KayacIk2010,

• author = "Hilmi Gunes Kayacik and A. Nur Zincir-Heywood and Malcolm I. Heywood",
• title = "Can a good offense be a good defense? Vulnerability testing of anomaly detectors through an artificial arms race",
• journal = "Applied Soft Computing",
• year = "2011",
• volume = "11",
• number = "7",
• month = oct,
• pages = "4366--4383",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2010.09.005",
• URL = "http://www.sciencedirect.com/science/article/B6W86-517J230-1/2/84e06f47c1845a8bc71256b74a86b16d",
• keywords = "genetic algorithms, genetic programming, Computer security, Intrusion detection, Evasion attacks, Arms race",
• size = "18 pages",
• abstract = "Intrusion detection systems, which aim to protect our IT infrastructure are not infallible. Attackers take advantage of detector vulnerabilities and weaknesses to evade detection, hence hindering the effectiveness of the detectors. To do so, attackers generate evasion attacks which can eliminate or minimise the detection while successfully achieving the attacker's goals. This work proposes an artificial arms race between an automated white-hat attacker and various anomaly detectors for the purpose of identifying detector weaknesses. The proposed arms race aims to automate the vulnerability testing of the anomaly detectors so that the security experts can be more proactive in eliminating detector vulnerabilities.",

}

Genetic Programming entries for Hilmi Gunes Kayacik Nur Zincir-Heywood Malcolm Heywood

Citations