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Anti-spam techniques based on artificial immune system / Ying Tan.

By: Material type: TextTextPublication details: London CRC Press 2016Description: xxvii, 236 pages : illustrationsISBN:
  • 9781498725187
  • 149872518X
Subject(s): DDC classification:
  • 005.8 TAN
Contents:
Anti-Spam Technologies -- Artificial Immune System -- Term Space Partition-Based Feature Construction Approach -- Immune Concentration-Based Feature Construction Approach -- Local Concentration-Based Feature Extraction Approach -- Multi-Resolution Concentration-Based Feature Construction Approach -- Adaptive Concentration Selection Model -- Variable Length Concentration-Based Feature Construction Method -- Parameter Optimization of Concentration-Based Feature Construction Approaches -- Immune Danger Theory-Based EnsembleMethod -- Immune Danger Zone Principle-Based Dynamic Learning Method -- Immune-Based Dynamic Updating Algorithm -- AIS-Based Spam Filtering System and Implementation.
Summary: Email has become an indispensable communication tool in daily life. However, high volumes of spam waste resources, interfere with productivity, and present severe threats to computer system security and personal privacy. This book introduces research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam. It provides a single source of all anti-spam models and algorithms based on the AIS that have been proposed by the author for the past decade in various journals and conferences. Inspired by the biological immune system, the AIS is an adaptive system based on theoretical immunology and observed immune functions, principles, and models for problem solving. Among the variety of anti-spam techniques, the AIS has been highly effective and is becoming one of the most important methods to filter spam. The book also focuses on several key topics related to the AIS, including: extraction methods inspired by various immune principles, construction approaches based on several concentration methods and models, classifiers based on immune danger theory, the immune-based dynamic updating algorithm, and implementing AIS-based spam filtering systems. The book also includes several experiments and comparisons with state-of-the-art anti-spam techniques to illustrate the excellent performance AIS-based anti-spam techniques. Anti-Spam Techniques Based on Artificial Immune System gives practitioners, researchers, and academics a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques. It also contains the most current information on the general achievements of anti-spam research and approaches, outlining strategies for designing and applying spam-filtering models.
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Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Computer Science Reference Dept. of Computer Science 005.8 TAN (Browse shelf(Opens below)) Available DCS4771

Includes bibliographical references (pages 213-227) and index.

Anti-Spam Technologies -- Artificial Immune System -- Term Space Partition-Based Feature Construction Approach -- Immune Concentration-Based Feature Construction Approach -- Local Concentration-Based Feature Extraction Approach -- Multi-Resolution Concentration-Based Feature Construction Approach -- Adaptive Concentration Selection Model -- Variable Length Concentration-Based Feature Construction Method -- Parameter Optimization of Concentration-Based Feature Construction Approaches -- Immune Danger Theory-Based EnsembleMethod -- Immune Danger Zone Principle-Based Dynamic Learning Method -- Immune-Based Dynamic Updating Algorithm -- AIS-Based Spam Filtering System and Implementation.

Email has become an indispensable communication tool in daily life. However, high volumes of spam waste resources, interfere with productivity, and present severe threats to computer system security and personal privacy. This book introduces research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam. It provides a single source of all anti-spam models and algorithms based on the AIS that have been proposed by the author for the past decade in various journals and conferences. Inspired by the biological immune system, the AIS is an adaptive system based on theoretical immunology and observed immune functions, principles, and models for problem solving. Among the variety of anti-spam techniques, the AIS has been highly effective and is becoming one of the most important methods to filter spam. The book also focuses on several key topics related to the AIS, including: extraction methods inspired by various immune principles, construction approaches based on several concentration methods and models, classifiers based on immune danger theory, the immune-based dynamic updating algorithm, and implementing AIS-based spam filtering systems. The book also includes several experiments and comparisons with state-of-the-art anti-spam techniques to illustrate the excellent performance AIS-based anti-spam techniques. Anti-Spam Techniques Based on Artificial Immune System gives practitioners, researchers, and academics a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques. It also contains the most current information on the general achievements of anti-spam research and approaches, outlining strategies for designing and applying spam-filtering models.

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