Share Email Print

Proceedings Paper

Intrusion Detector using Hidden Markov Model against Denial of Service Attack in Wireless Networks
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The third-generation (3G) wireless network is a convergence of several types of telecommunication networks to support various wireless data services. Wireless LAN also supports mobility via mobile IP. As a result, the convergence and mobility have potential vulnerability in security. In this paper, a Denial-of-Service (DoS) attack which can waste wireless resource by sending a large number of nuisance packets to the spoofed destination address of IP packets is introduced. To effectively prevent the attack, fast detection, reliability, and efficiency with small overhead are suggested as requirements in a detection system. We propose a detector using Hidden Markov Model (HMM) to achieve these requirements and reduce the influences of the attack as fast as possible. The generation of the HMM for the detector are discussed and the operation of the detector are described. Weighting factors and second order Markov models are employed to improve the reliability of the detector. The proposed system is compared with the existing sequential detection approach in terms of the false alarm rate and optimum detection time interval to evaluate the performance of the detectors. Our simulation results using ns-2 simulator shows that the proposed HMM detector is reliable and fast to detect the attack due to its dynamic property.

Paper Details

Date Published: 8 August 2003
PDF: 11 pages
Proc. SPIE 5245, Internet Quality of Service, (8 August 2003); doi: 10.1117/12.511407
Show Author Affiliations
Junghun Park, Univ. of Southern California (United States)
Lei Huang, Loyola Marymount University (United States)
Fang Liu, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 5245:
Internet Quality of Service
Mohammed Atiquzzaman; Mahbub Hassan, Editor(s)

© SPIE. Terms of Use
Back to Top