A grammatical evolution approach to intrusion detection on mobile ad hoc networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Sen:2009:WiSec,
-
author = "Sevil Sen and John Andrew Clark",
-
title = "A grammatical evolution approach to intrusion
detection on mobile ad hoc networks",
-
booktitle = "WiSec '09: Proceedings of the second ACM conference on
Wireless network security",
-
year = "2009",
-
pages = "95--102",
-
address = "Zurich, Switzerland",
-
publisher_address = "New York, NY, USA",
-
month = mar # " 16-19",
-
publisher = "ACM",
-
language = "english",
-
organisation = "SIGSAC: ACM Special Interest Group on Security, Audit,
and Control. ACM: Association for Computing Machinery",
-
keywords = "genetic algorithms, genetic programming, grammatical
evolution, Design, Experimentation, Performance,
Security, artificial intelligence, intrusion detection,
mobile ad hoc networks, security",
-
isbn13 = "978-1-60558-460-7",
-
DOI = "doi:10.1145/1514274.1514289",
-
abstract = "In recent years mobile ad hoc networks (MANETs) have
become a very popular research topic. By providing
communication in the absence of a fixed infrastructure
they are very attractive for many applications such as
tactical and disaster recovery operations and virtual
conferences. On the other hand, this flexibility
introduces new security risks. Moreover, different
characteristics of MANETs make conventional security
systems ineffective and inefficient for this new
environment. Intrusion detection, which is an
indispensable part of a security system, presents also
a particular challenge due to the dynamic nature of
MANETs, the lack of central points, and their highly
constrained nodes. In this paper, we propose to
investigate the use of an artificial intelligence based
learning technique to explore this difficult design
space. The grammatical evolution technique inspired by
natural evolution is explored to detect known attacks
on MANETs such as DoS attacks and route disruption
attacks. Intrusion detection programs are evolved for
each attack and distributed to each node on the
network. The performance of these programs is evaluated
on different types of networks with different mobility
and traffic patterns to show their effects on intrusion
detection ability.",
-
notes = "Also known as \cite{1514289}",
- }
Genetic Programming entries for
Sevil Sen
John A Clark
Citations