Modeling an Intrusion Detection System Based on Adaptive Immunology

Author:

Alaparthy Vishwa1,Morgera Salvatore D.1

Affiliation:

1. Electrical Engineering, University of South Florida, Tampa, USA

Abstract

Network security has always has been an area of priority and extensive research. Recent years have seen a considerable growth in experimenting with biologically inspired techniques. This is a consequence of the authors increased understanding of living systems and the application of that understanding to machines and software. The mounting complexity of telecommunications networks and the need for increasing levels of security have been the driving factors. The human body can act as a great role model for its unique abilities in protecting itself from external entities owing to its diverse complexities. Many abnormalities in the human body are similar to that of the attacks in wireless sensor networks (WSN). This article presents the basic ideas that can help modelling a system to counter the attacks on a WSN by monitoring parameters such as energy, frequency of data transfer, data sent and received. This is implemented by exploiting an immune concept called danger theory, which aggregates the anomalies based on the weights of the anomalous parameters. The objective is to design a cooperative intrusion detection system (IDS) based on danger theory.

Publisher

IGI Global

Subject

Computer Networks and Communications

Reference17 articles.

1. The Danger Theory and its Application to Artificial Immune Systems

2. A Survey of Intrusion Detection Systems in Wireless Sensor Networks

3. Immunity-based intrusion detection system: a general framework.;D.Dasgupta;Proc. of the 22nd NISSC,1999

4. Self-nonself discrimination in a computer

5. n.d.). Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection.;J.Greensmith;Proceedings of the 4th International Conference on Artificial Immune Systems

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