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An Intrusion Detection Technique Based on Change in Hurst Parameter with Application to Network Security


C. M. Akujuobi, N. K. Ampah, Matthew N.O. Sadiku


Vol. 7  No. 5  pp. 55-64


Securing Enterprise networks has been considered under two broad topics (i. e. Intrusion Detection Systems - IDS and Intrusion Prevention Systems - IPS). So far, there is no algorithm, which guarantees absolute protection for a given network from intruders. Most existing IDS and IPS techniques introduce high false positive and false negative rates, which need to be eliminated or reduced considerably. This paper will concentrate on network packets behavior leading to network-based intrusion detection. It will employ anomaly detection as its analysis strategy. In the field of signal analysis, the methods of wavelet transform have gotten wide application because of its unique merit. That novel idea will be tapped in this paper. The self-similarity property of real network traffic will be used together with the signal detection abilities of wavelets in detecting attacks. The justification for using change in Hurst parameter as an estimator for detection is given here. The technique used here will also try to reduce the effectiveness of distributed attacks, which deny authorized users access to system resources. Securing of all network security data, which is an important limitation to existing IDS and IPS is ensured by the techniques we used.


Intrusion detection and prevention, enterprise network, anomaly detection, self-similarity, multi-resolution technique