کاوش داده‌های امن

This era of information technology has a distinctive features of enormous amount of data being produced and stored by all forms human activities. Computers are used to store a huge portion of this database called computer databases, making the data accessible by the computer technology. However, enormous amount of data creates a problem of extraction of valuable knowledge from the database. This books gives a secure method of data mining techniques taking into account the privacy and security of the data. Even in the disturbed environment, this approach can keep up the validity and authenticity of the data to produce the data after computation. Cover 1 Title Page 5 Copyright 6 ABOUT THE AUTHOR 7 TABLE OF CONTENTS 9 List of Figures 13 Lis of Tables 15 Preface 17 Chapter 1 Fundamentals of Data Mining 19 1.1. Introduction 20 1.2. Moving Toward the Information Era 20 1.3. Data Mining 21 1.4. What Type of Data Are We Gathering? 25 1.5. What Kind of Data Can Be Mined? 28 1.6. What May Be Discovered? 34 1.7. Is Everything you Discover Fascinating and Beneficial? 37 1.8. Different Types of Data Mining Setups 37 1.9. Problems in Data Mining 38 References 42 Chapter 2 Security in Data Mining 49 2.1. Introduction 50 2.2. Classification and Detection Using Data mining Techniques 53 2.3. Clustering 58 2.4. Privacy-Preserving Data Mining (PPDM) 62 2.5. Intrusion Detection System (idsIDS) 67 2.6. Classification of Phishing Websites 74 2.7. Artificial Neural Networks (ANN) 75 2.8. Outlier Detection/Anomaly Detection 76 References 83 Chapter 3 Classification Approaches in Data Mining 93 3.1. Introduction 94 3.2. Preprocessing of Data 95 3.3. Selection of Feature 96 3.4. Categorization 97 3.5. Categorization Techniques 99 References 106 Chapter 4 Application of Secure Data Mining in Fraud Detection 111 4.1. Introduction 112 4.2. Existing Fraud Detection Systems 113 4.3. Applications 119 4.4. Model Performance 125 References 130 Chapter 5 Application of Data Mining in Crime Detection 135 5.1. Introduction 136 5.2. Fundamentals of Intelligent Crime Analysis 137 5.3. Components of the Planned Technique: Toward a Crime Matching Outline 139 References 147 Chapter 6 Data Mining in Telecommunication Industry 151 6.1. Introduction 152 6.2. Role of Data Mining in Telecommunication Industry 153 6.3. Data Mining and Telecommunication Industry 154 6.4. Data Mining Focus Areas in Telecommunication 157 6.5. A Learning System for Decision Support in Telecommunications – Case Study 161 6.6. Knowledge Processing in Control Systems 163 6.7. Data Mining for Maintenance of Complex Systems – A Case Study 166 Reference 169 Chapter 7 Data Mining In Security Systems 175 7.1. Introduction 176 7.2. Roles of Data Mining in Security Systems 178 7.3. Data Mining and Security Systems 178 7.4. Real-Time Data Mining-Based Intrusion Detection Systems 179 References 199 Chapter 8 Recent Trends and Future Projections of Data Mining 207 8.1. Introduction 208 8.2. A sequence of Data Mining: Time-Series, Symbolic and Biological Sequences 208 8.3. The search of Resemblance in the Time-Series Data 209 8.4. Analysis of Regression and Trend in the Time-Series Data 210 8.5. Advancement of Information and Social Networks 211 8.6. Data Mining Uses 212 8.7. Mining of Data and Society 222 8.8. Trends of Data Mining 228 References 232 Index 241 Back Cover 244 Data mining is a process to extract useful knowledge from large amounts of data. To conduct data mining, we often need to collect data. However, privacy concerns may prevent people from sharing the data and some types of information about the data. How we conduct data mining without breaching data privacy presents a challenge. Secure Data Mining provides solutions to the problem of data mining without compromising data privacy. This professional book is designed for practitioners and researchers in industry, as well as a secondary textbook for advanced-level students in computer science.