Intrusion Detection in Wireless Mesh Networks Using a Hybrid Approach

Wireless mesh network are very vulnerable to attacks by malicious users due to, mainly, the cooperation among their nodes. The methods for detection of attacks are grouped into two categories: analysis of anomalies and signatures. The former detects possible new attacks, which have not been previous...

Full description

Saved in:
Bibliographic Details
Main Authors: Ferreira, E.W.T., de Oliveira, R., Carrijo, G.A., Bhargava, B.
Format: Conference Proceeding
Language:English
Subjects:
Ad hoc networks
Computer science
Conferences
Distributed computing
Intrusion detection
Intrusion Detection System (IDS)
Neural networks
Security
Signal processing algorithms
Telecommunication traffic
Testing
Wavelet
Wireless Mesh Network
Wireless mesh networks
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Wireless mesh network are very vulnerable to attacks by malicious users due to, mainly, the cooperation among their nodes. The methods for detection of attacks are grouped into two categories: analysis of anomalies and signatures. The former detects possible new attacks, which have not been previously discovered and the latter depends on prior knowledge to classify the attacks. This paper presents a proposal that uses wavelets and neural networks for detection and classification of attacks. Evaluations by simulation and environmental testing are also presented, and the results indicate that this approach is very promising.
ISSN:1545-0678
2332-5666
DOI:10.1109/ICDCSW.2009.69