Evaluation of classification algorithms for intrusion detection in MANETs
Journal article, 2012

Mobile Ad hoc Networks (MANETs) are wireless networks without fixed infrastructure based on the cooperation of independent mobile nodes. The proliferation of these networks and their use in critical scenarios (like battlefield communications or vehicular networks) require new security mechanisms and policies to guarantee the integrity, confidentiality and availability of the data transmitted. Intrusion Detection Systems used in wired networks are inappropriate in this kind of networks since different vulnerabilities may appear due to resource constraints of the participating nodes and the nature of the communication. This article presents a comparison of the effectiveness of six different classifiers to detect malicious activities in MANETs. Results show that Genetic Programming and Support Vector Machines may help considerably in detecting malicious activities in MANETs. © 2012 Elsevier B.V. All rights reserved.

Intrusion detection


Genetic Programming

Classification algorithms

Support Vector Machines


S. Pastrana

Aikaterini Mitrokotsa

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

A. Orfila

P. Peris-Lopez

Knowledge-Based Systems

0950-7051 (ISSN)

Vol. 36 217-225

Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems

Information Science

Computer Science

Computer Systems



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