Artificial Immune System: Applications in Computer Security

This book deals with malware detection in terms of Artificial Immune System (AIS), and presents a number of AIS models and immune-based feature extraction approaches as well as their applications in computer security

• Covers all of the current achievements in computer security based on immune principles, which were obtained by the Computational Intelligence Laboratory of Peking University, China
• Includes state-of-the-art information on designing and developing artificial immune systems (AIS) and AIS-based solutions to computer security issues
• Presents new concepts such as immune danger theory, immune concentration,  and class-wise information gain (CIG)

Table of Contents

Chapter 1: Artificial Immune System
Chapter 2: Malware Detection
Chapter 3: Immune Principle and Neural Networks-Based Malware Detection
Chapter 4: Multiple-Point Bit Mutation Method of Detector Generation
Chapter 5: Malware Detection System Using Affinity Vectors
Chapter 6: Hierarchical Artificial Immune Model
Chapter 7: Negative Selection Algorithm with Penalty Factor
Chapter 8: Danger Feature-Based Negative Selection Algorithm
Chapter 9: Immune Concentration-Based Malware Detection Approaches
Chapter 10: Immune Cooperation Mechanism-Based Learning Framework
Chapter 11: Class-Wise Information Gain