Soft Computing Models for Network Intrusion Detection Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @TechReport{abraham:2004:0405046,
-
author = "Ajith Abraham and Ravi Jain",
-
title = "Soft Computing Models for Network Intrusion Detection
Systems",
-
institution = "OSU",
-
year = "2004",
-
month = "13 " # may # " 2004",
-
note = "Journal-ref: Soft Computing in Knowledge Discovery:
Methods and Applications, Saman Halgamuge and Lipo Wang
(Eds.), Studies in Fuzziness and Soft Computing,
Springer Verlag Germany, Chapter 16, 20 pages, 2004",
-
keywords = "genetic algorithms, genetic programming, Cryptography
and Security",
-
URL = "http://www.softcomputing.net/saman2.pdf",
-
URL = "http://arxiv.org/abs/cs/0405046",
-
abstract = "Security of computers and the networks that connect
them is increasingly becoming of great significance.
Computer security is defined as the protection of
computing systems against threats to confidentiality,
integrity, and availability. There are two types of
intruders: external intruders, who are unauthorised
users of the machines they attack, and internal
intruders, who have permission to access the system
with some restrictions. This chapter presents a soft
computing approach to detect intrusions in a network.
Among the several soft computing paradigms, we
investigated fuzzy rule-based classifiers, decision
trees, support vector machines, linear genetic
programming and an ensemble method to model fast and
efficient intrusion detection systems. Empirical
results clearly show that soft computing approach could
play a major role for intrusion detection.",
-
notes = "ACM-class: K.6.5 cs.CR/0405046",
-
size = "20 pages",
- }
Genetic Programming entries for
Ajith Abraham
Ravi Jain
Citations