Host-based Intrusion Detection Systems Inspired by Machine Learning of Agent-Based Artificial Immune Systems

Abstract

An adaptable agent-based IDS (AAIDS) inspired by the danger theory of artificial immune system is proposed. The learning mechanism of AAIDS is designed by emulating how dendritic cells (DC) in immune systems detect and classify danger signals. AG agent, DC agent and TC agent coordinate together and respond to system calls directly rather than analyze network packets. Simulations show AAIDS can determine several critical scenarios of the system behaviors where packet analysis is impractical.