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Author Tan, Ying, 1964- author.

Title Anti-spam techniques based on artificial immune system / Ying Tan
Published Boca Raton : CRC Press, [2016]
Online access available from:
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Description 1 online resource
Contents Front Cover; Contents; List of Figures; List of Tables; List of Symbols; Preface; Acknowledgments; Author; Chapter 1: Anti-Spam Technologies; 1.1 Spam Problem; 1.1.1 Definition of Spam; 1.1.2 Scale and Influence of Spam; 1.2 Prevalent Anti-Spam Technologies; 1.2.1 Legal Means; 1.2.2 E-Mail Protocol Methods; 1.2.3 Simple Techniques; 1.2.4 Intelligent Spam Detection Approaches; 1.3 E-Mail Feature Extraction Approaches; 1.3.1 Term Selection Strategies; 1.3.2 Text-Based Feature Extraction Approaches; 1.3.3 Image-Based Feature Extraction Approaches
1.3.4 Behavior-Based Feature Extraction Approaches; 1.4 E-Mail Classification Techniques; 1.5 Performance Evaluation and Standard Corpora; 1.5.1 Performance Measurements; 1.5.2 Standard Corpora; 1.6 Summary; Chapter 2: Artificial Immune System; 2.1 Introduction; 2.2 Biological Immune System; 2.2.1 Overview; 2.2.2 Adaptive Immune Process; 2.2.3 Characteristics of BIS; 2.3 Artificial Immune System; 2.3.1 Overview; 2.3.2 AIS Models and Algorithms; 2.3.3 Characteristics of AIS; 2.3.4 Application Fields of AIS; 2.4 Applications of AIS in Anti-Spam; 2.4.1 Heuristic Methods; 2.4.2 Negative Selection
2.4.3 Immune Network; 2.4.4 Dynamic Algorithms; 2.4.5 Hybrid Models; 2.5 Summary; Chapter 3: Term Space Partition-Based Feature Construction Approach; 3.1 Motivation; 3.2 Principles of the TSP Approach; 3.3 Implementation of the TSP Approach; 3.3.1 Preprocessing; 3.3.2 Term Space Partition; 3.3.3 Feature Construction; 3.4 Experiments; 3.4.1 Investigation of Parameters; 3.4.2 Performance with Different Feature Selection Metrics; 3.4.3 Comparison with Current Approaches; 3.5 Summary; Chapter 4: Immune Concentration-Based Feature Construction Approach; 4.1 Introduction
4.2 Diversity of Detector Representation in AIS; 4.3 Motivation of Concentration-Based Feature Construction Approach; 4.4 Overview of Concentration-Based Feature Construction Approach; 4.5 Gene Library Generation; 4.6 Concentration Vector Construction; 4.7 Relation to Other Methods; 4.8 Complexity Analysis; 4.9 Experimental Validation; 4.9.1 Experiments on Different Concentrations; 4.9.2 Experiments with Two-Element Concentration Vector; 4.9.3 Experiments with Middle Concentration; 4.10 Discussion; 4.11 Summary; Chapter 5: Local Concentration-Based Feature Extraction Approach; 5.1 Introduction
5.2 Structure of Local Concentration Model; 5.3 Term Selection and Detector Sets Generation; 5.4 Construction of Local Concentration-Based Feature Vectors; 5.5 Strategies for Defining Local Areas; 5.5.1 Using a Sliding Window with Fixed Length; 5.5.2 Using a Sliding Window with Variable Length; 5.6 Analysis of Local Concentration Model; 5.7 Experimental Validation; 5.7.1 Selection of a Proper Tendency Threshold; 5.7.2 Selection of Proper Feature Dimensionality; 5.7.3 Selection of a Proper Sliding Window Size; 5.7.4 Selection of Optimal Terms Percentage
Summary Introducing research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam, this authoritative book provides a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques -- Edited summary from book
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (EBSCO, viewed December 18, 2015)
Subject Artificial immune systems.
Spam filtering (Electronic mail)
Artificial immune systems.
COMPUTERS / Computer Literacy
COMPUTERS / Computer Science
COMPUTERS / Data Processing
COMPUTERS / Hardware / General
COMPUTERS / Information Technology
COMPUTERS / Machine Theory
COMPUTERS / Reference
Spam filtering (Electronic mail)
Form Electronic book
ISBN 1498725198