Anti-Spam Techniques Based on Artificial Immune System

Today high volumes of spam not only waste resources and impede productivity, but also present severe threats to computer system security and personal privacy. This book introduces research on anti-spam techniques based on the artificial immune system, similar to the biological immune system, to identify and filter spam. Intelligent spam detection methods, highlighted in this book, are critical to designing spam filtering models and relevant online implementation. Efficient models and algorithms are described in detail.

Ying Tan, PhD, is a full professor and PhD advisor in the School of Electronics Engineering and Computer Science at Peking University, China. He is also director of the Computational Intelligence Laboratory at Peking University. He received his PhD from Southeast University in Nanjing, China. His research interests include computational intelligence, swarm intelligence, data mining, machine learning, fireworks algorithm, and intelligent information processing for information security. He has published more than 280 papers, has authored or coauthored six books and more than 10 book chapters, and holds three invention patents. He is editor in chief of theInternational Journal of Computational Intelligence and Pattern Recognition and is an associate editor ofIEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems. He is the general chair of the ICSI–CCI 2015 joint conference and ICSI series conference and is a senior member of the IEEE.