Biological Inspired Intrusion Prevention and Self-healing System for Network Security Based on Danger Theory

This paper presents a model for intrusion prevention and self-healing system for network security. The model detects, prevents, and heals harmful events, which are the actual reasons for damage of any of the system’s components. The proposed model explores the design and implementation of artificial immune systems (AISs) inspired by the human immune system. A novel approaches for network security based on the combination of biological intrusion prevention (IP) and self-healing concepts are implemented in the proposed model. These approaches are based upon data inspired by the human immune system (HIS), which applied to the autonomous defense system. The system integrates an artificial immune intrusion prevention system for network security inspired by the immunology theory known as danger theory and adaptive immune system. The present model looks at the danger model and its application to attack defense in order to create a fully decentralized model. The intrusion prevention system (IPS) analyzes the behavior of system processes and network traffic to detect harmful events. Abnormal behaviors are the actual reason for damage of any of the system’s components. The detection of the damage caused by different types of malicious events or attack profiles is used to trigger the self - healing (SH) mechanism. This system is autonomous and enhances the fault repair and system recovery.