Negative Selection Approach Application in Network Intrusion Detection Systems
It addresses network security for intrusion detection, but is incremental as it reviews existing applications without presenting new results.
The paper reviews the application of the negative selection approach from artificial immune systems in network intrusion detection systems, identifying challenges and providing recommendations for future work.
Nature has always been an inspiration to researchers with its diversity and robustness of its systems, and Artificial Immune Systems are one of them. Many algorithms were inspired by ongoing discoveries of biological immune systems techniques and approaches. One of the basic and most common approach is the Negative Selection Approach, which is simple and easy to implement. It was applied in many fields, but mostly in anomaly detection for the similarity of its basic idea. In this paper, a review is given on the application of negative selection approach in network security, specifically the intrusion detection system. As the work in this field is limited, we need to understand what the challenges of this approach are. Recommendations are given by the end of the paper for future work.