A Network Intrusion Detection Model Based on Immune Multi-Agent

Abstract

A new network intrusion detection model based on immune multi-agent theory is established and the concept of multi-agents is advanced to realize the logical structure and running mechanism of immune multi-agent as well as multi-level and distributed detection mechanism against network intrusion, using the adaptability, diversity and memory properties of artificial immune algorithm and combing the robustness and distributed character of multi-agents system structure. The experiment results conclude that this system is working pretty well in network security detection

The Research of Learning Mechanism in Fault Diagnosis System of CNC Based on MAS

“…Immune algorithm derives from somatic cell theory and network theory, and realizes functions of self-adjusting and generating different antibodies similar to immune system [8] . Comparing with traditional learning algorithms, immune algorithm has advantages as followed.…”

An Immune Agents System for Network Intrusions Detection

“…However, with the networks widening they generate much false alarm, and became less and less reliable to new attack's forms. To overcome difficulties met by these models, new research works are interested in multi-agents systems and immunology principles such as (MAAIS [19], NIDIMA [14], DAMIDAIS [11], IMASNID [7], etc). These systems succeed in decreasing the false alarm rate thanks to the processes employed; namely communication process between the agents and the distinction process between self and not-self.…”