Network intrusion detection using fuzzy class association rule mining based on genetic network programming

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

@InProceedings{chen:2009:SMC,

• author = "Ci Chen and Shingo Mabu and Chuan Yue and Kaoru Shimada and Kotaro Hirasawa",
• title = "Network intrusion detection using fuzzy class association rule mining based on genetic network programming",
• booktitle = "IEEE International Conference on Systems, Man and Cybernetics, SMC 2009",
• year = "2009",
• pages = "60--67",
• address = "San Antonio, Texas, USA",
• month = oct,
• keywords = "genetic algorithms, genetic programming, Internet, anomaly detection, computer systems, directed graph structure, evolutionary optimization, fuzzy class association rule mining, fuzzy set theory, genetic network programming, machine learning, network intrusion detection, Internet, data mining, security of data",
• DOI = "doi:10.1109/ICSMC.2009.5346328",
• ISSN = "1062-922X",
• abstract = "Computer systems are exposed to an increasing number and type of security threats due to the expanding of Internet in recent years. How to detect network intrusions effectively becomes an important techniques. This paper presents a novel fuzzy class association rule mining method based on Genetic Network Programming (GNP) for detecting network intrusions. GNP is an evolutionary optimization techniques, which uses directed graph structures as genes instead of strings (Genetic Algorithm) or trees (Genetic Programming), leading to creating compact programs and implicitly memorizing past action sequences. By combining fuzzy set theory with GNP, the proposed method can deal with the mixed database which contains both discrete and continuous attributes. And it can be flexibly applied to both misuse and anomaly detection in Network Intrusion Detection Problem. Experimental results with KDD99Cup and DAPRA98 databases from MIT Lincoln Laboratory show that the proposed method provides a competitively high detection rate compared with other machine learning techniques.",
• notes = "Also known as \cite{5346328}",

}

Genetic Programming entries for Ci Chen Shingo Mabu Chuan Yue Kaoru Shimada Kotaro Hirasawa

Citations