An Intrusion-Detection Model Based on Fuzzy Class-Association-Rule Mining Using Genetic Network Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Mabu:2011:ieeeSMC,
-
author = "Shingo Mabu and Ci Chen and Nannan Lu and
Kaoru Shimada and Kotaro Hirasawa",
-
title = "An Intrusion-Detection Model Based on Fuzzy
Class-Association-Rule Mining Using Genetic Network
Programming",
-
journal = "IEEE Transactions on Systems, Man, and Cybernetics,
Part C: Applications and Reviews",
-
year = "2011",
-
month = jan,
-
volume = "41",
-
number = "1",
-
pages = "130--139",
-
abstract = "As the Internet services spread all over the world,
many kinds and a large number of security threats are
increasing. Therefore, intrusion detection systems,
which can effectively detect intrusion accesses, have
attracted attention. This paper describes a novel fuzzy
class-association-rule mining method based on genetic
network programming (GNP) for detecting network
intrusions. GNP is an evolutionary optimisation
technique, which uses directed graph structures instead
of strings in genetic algorithm or trees in genetic
programming, which leads to enhancing the
representation ability with compact programs derived
from the reusability of nodes in a graph structure. By
combining fuzzy set theory with GNP, the proposed
method can deal with the mixed database that contains
both discrete and continuous attributes and also
extract many important class-association rules that
contribute to enhancing detection ability. Therefore,
the proposed method can be flexibly applied to both
misuse and anomaly detection in
network-intrusion-detection problems. Experimental
results with KDD99Cup and DARPA98 databases from MIT
Lincoln Laboratory show that the proposed method
provides competitively high detection rates compared
with other machine-learning techniques and GNP with
crisp data mining.",
-
keywords = "genetic algorithms, genetic programming, directed
graph structures, fuzzy class-association-rule mining,
fuzzy set theory, genetic network programming,
intrusion-detection model, data mining, directed
graphs, fuzzy set theory, security of data",
-
DOI = "doi:10.1109/TSMCC.2010.2050685",
-
ISSN = "1094-6977",
-
notes = "Also known as \cite{5499108}",
- }
Genetic Programming entries for
Shingo Mabu
Ci Chen
Nannan Lu
Kaoru Shimada
Kotaro Hirasawa
Citations