An Immune System Inspired Approach of Collaborative Intrusion Detection System Using Mobile Agents in Wireless Ad Hoc Networks
- 725 Downloads
Many single points of failure exist in an intrusion detection system (IDS) based on a hierarchical architecture that does not have redundant communication lines and the capability to dynamically reconfigure relationships in the case of failure of key components. To solve this problem, we propose an IDS inspired by the human immune system based upon several mobile agents. The mobile agents act similarly to white blood cells of the immune system and travel from host to host in the network to detect any intrusions. As in the immune system, intrusions are detected by distinguishing between "self" and "non-self", or normal and abnormal process behavior respectively. In this paper we present our model, and show how mobile agent and artificial immune paradigms can be used to design efficient intrusion detection systems. We also discuss the validation of our model followed by a set of experiments we have carried out to evaluate the performance of our model using realistic case studies.
KeywordsIntrusion Detection Mobile Agent Intrusion Detection System Artificial Immune System Human Immune System
Unable to display preview. Download preview PDF.
- 1.Wagner, D., Dean, D.: Intrusion detection via static analysis. In: IEEE symposium on security and privacy (2001)Google Scholar
- 2.Crispin, C., Steve, B., John, J., Perry, W.: Pointguard - Protecting pointers from buer over vulnerabilities. In: Proceedings of the 12th USENIX Security Symposium, Washington, D.C. (2003)Google Scholar
- 3.Barrantes, E.G., Ackley, D.H., Forrest, S., Palmer, T.S., et al.: Randomized instruction set emulation to disrupt binary code injection attacks. In: Proceeding of the 10th ACM Conference on Computer and Communications Security (2003)Google Scholar
- 4.Jon, G., Somesh, J., Bart, M.: Efficient context-sensitive intrusion detection. In: Network and Distributed System Security Symposium (2004)Google Scholar
- 7.Forrest, S., Hofmeyr, S., Somayaji, A.: Computer Immunology. Communications of the ACM 40(10) (1997)Google Scholar