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) This Book Focuses On The Technologies And Applications Of Artificial Immune Systems In Malware And Spam Detection Proposed In Recent Years By The Computation Intelligence Laboratory At Peking University, China. It Offers A Theoretical Perspective And Practical Solutions To Graduate Students, Practitioners, And Researchers Working In The Area Of Artificial Immune System, Machine Learning, Pattern Recognition, And Computer Security-- Artificial Immune System -- Malware Detection -- Immune Principle And Neural Networks-based Malware Detection -- Multiple-point Bit Mutation Method Of Detector Generation -- Malware Detection System Using Affinity Vectors -- Hierarchical Artificial Immune Model -- Negative Selection Algorithm With Penalty Factor -- Danger Feature-based Negative Selection Algorithm -- Immune Concentration-based Malware Detection Approaches -- Immune Cooperation Mechanism-based Learning Framework -- Class-wise Information Gai. Ying Tan. Includes Index. Includes Bibliographical References And Index. Mode Of Access: World Wide Web. "This book focuses on the technologies and applications of artificial immune systems in malware and spam detection proposed in recent years by the computation intelligence laboratory at Peking University, China. It offers a theoretical perspective and practical solutions to graduate students, practitioners, and researchers working in the area of artificial immune system, machine learning, pattern recognition, and computer security"-- Provided by publisher