Intrusion detection by integrating boosting genetic fuzzy classifier and data mining criteria for rule pre-screening-Reference-Cited by-同舟云学术

Intrusion detection by integrating boosting genetic fuzzy classifier and data mining criteria for rule pre-screening

Published:2007-01 Issue:1 Volume:30 Page:99-113
ISSN:1084-8045
Container-title:Journal of Network and Computer Applications
language:en
Short-container-title:Journal of Network and Computer Applications

Author:

Özyer Tansel,Alhajj Reda,Barker Ken

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Reference30 articles.

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2. Allen J, Christie A, Fithen W, McHugh J, Pickel J, Stoner E. State of the practice of intrusion detection technologies. CMU/SEI-99-TR-028 Carnegie Mellon Software (http://www.sei.cmu.edu/pub/documents/99.reports/pdf/99tr028.pdf). Engineering Institute, 1999.

3. Balasubramaniyan JS, Fernandezm JOG, Isacoff D, Spafford E, Zamboni D. An architecture for intrusion detection using autonomous agents. In: Proceedings of the annual computer security applications conference, 1998. p. 13–24.

4. Bridges S, MS, Vaughn RB. Fuzzy data mining and genetic algorithms applied to intrusion detection. In: Proceedings of the national information systems security conference, 2000.

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