Intrusion Detection Mechanisms Based on Queuing Theory in Remote Distribution Sensor Networks

Article Preview

Abstract:

Recently, sensor networks are usually applied on collecting remote sensing information. The deployed sensor nodes are separated and responsible for specific purposes, and act as an individual device. They cooperatively transmit sensed data to the base station, as shown in Fig.1. However, the transmitted data are exposed to open environments, and possibly contain confidential information. If malicious attacks interfere in the communication using huge packets to break the communication, thus the system can not work properly. In general, attackers exploit a broadcast storm or a Distributed Denial-of-Service (DDoS) attack to paralyze the entire network. Therefore, this study proposes a queuing theory based scheme to detect whether the system encounters malicious attacks. Our proposed scheme provides the arrival requests with a queuing service on the base station, which is responsible for dealing with transmitted jobs. Once the jammed traffic is anomalous for long periods, the system immediately detects the malicious attacks using our proposed approach.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 121-122)

Pages:

58-63

Citation:

Online since:

June 2010

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2010 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] P. Kammas1, T. Komninos, Y. C. Stamatiou1, A Queuing Theory Based Model for Studying Intrusion Evolution and Elimination in Computer Networks, in Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security, pp.167-171, Sept., (2008).

DOI: 10.1109/ias.2008.60

Google Scholar

[2] D. H. Lee, D. Y. Kim, J. Jung, Mobile Agent Based Intrusion Detection System Adopting Hidden Markov Model, Lecture Notes in Computer Science, vol. 4706, pp.122-130, Aug., (2007).

DOI: 10.1007/978-3-540-74477-1_12

Google Scholar

[3] G. Bolch, S. Greiner, H. Meer, K. S. Trivedi, Queuing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications, Wiley, Apr., (2006).

DOI: 10.1002/0471791571

Google Scholar

[4] V. S. Sharma, Study Report on Markov Chains and Queuing Networks, Roll No. Y211165, CSE, IIT Kanpur.

Google Scholar