A New Negative Selection Algorithm for Adaptive Network Intrusion Detection System

Abstract

Negative Selection Algorithm (NSA) is one of the widely used techniques for Intrusion Detection Systems (IDS) designing. In this paper, the proposed is an IDS based on a new model of NSA namely HNSA-IDSA (Hybrid NSA for Intrusion Detection System Adaptation). The proposed system can detect unknown attacks; moreover can be adapted automatically when new profiles' changes of the system are detected. To determine the efficiency of the proposed approach, the standard KDD99 dataset was used for performing experiments. The obtained results show that the authors' mechanism outperforms some literature techniques providing variant important properties as high detection rate, low false positive, adaptability and new attacks detection.