Soft Computing for Computer Security Intrusion Detection Based Upon Artificial Immunity Model

摘要

Despite extensive efforts during recent years within the technical community to improve computer security, serious problems of computer security continue to receive increasing coverage in both the popular and technical media. A large part of the problem is that current techniques are external, and not internal. In biological systems, natural internal immune system responses identify and protect the organism. A key mechanism in this immunity process is to distinguish between self (i.e. normal organisms or behaviors) and non-self (i.e. abnormal or anomalous behavior). To deal with the ambiguities in the process of anomaly detection for computer system security, we introduce a hierarchical fuzzy inference system to capture normal behavior deviations. Fully logic has been widely used in control systems, decision-making, information retrieval, and many other applications. In mis paper, we explore its capability in the area of computer security threat evaluation modeling and anomaly detection. Initial studies of command sequences indicate promising results for this approach.