Intelligent Data Analytics for Terror Threat Prediction. Группа авторов
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8 Rule-Based Approach for Botnet Behavior Analysis 8.1 Introduction 8.2 State-of-the-Art 8.3 Bots and Botnets 8.4 Methodology 8.5 Results and Analysis 8.6 Conclusion and Future Scope References
13 9 Securing Biometric Framework with Cryptanalysis 9.1 Introduction 9.2 Basics of Biometric Systems 9.3 Biometric Variance 9.4 Performance of Biometric System 9.5 Justification of Biometric System 9.6 Assaults on a Biometric System 9.7 Biometric Cryptanalysis: The Fuzzy Vault Scheme 9.8 Conclusion & Future Work References
14 10 The Role of Big Data Analysis in Increasing the Crime Prediction and Prevention Rates 10.1 Introduction: An Overview of Big Data and Cyber Crime 10.2 Techniques for the Analysis of BigData 10.3 Important Big Data Security Techniques 10.4 Conclusion References
15 11 Crime Pattern Detection Using Data Mining 11.1 Introduction 11.2 Related Work 11.3 Methods and Procedures 11.4 System Analysis 11.5 Analysis Model and Architectural Design 11.6 Several Criminal Analysis Methods in Use 11.7 Conclusion and Future Work References
16 12 Attacks and Security Measures in Wireless Sensor Network 12.1 Introduction 12.2 Layered Architecture of WSN 12.3 Security Threats on Different Layers in WSN 12.4 Threats Detection at Various Layers in WSN 12.5 Various Parameters for Security Data Collection in WSN 12.6 Different Security Schemes in WSN 12.7 Conclusion References
17 13 Large Sensing Data Flows Using Cryptic Techniques 13.1 Introduction 13.2 Data Flow Management 13.3 Design of Big Data Stream 13.4 Utilization of Security Methods 13.5 Analysis of Security on Attack 13.6 Artificial Intelligence Techniques for Cyber Crimes 13.7 Conclusions References
18 14 Cyber-Crime Prevention Methodology 14.1 Introduction 14.2 Credit Card Frauds and Skimming 14.3 Hacking Over Public WiFi or the MITM Attacks 14.4 SQLi Injection 14.5 Denial of Service Attack 14.6 Dark Web and Deep Web Technologies 14.7 Conclusion References
19 Index
List of Tables
1 Chapter 1Table 1.1 Social network users [24].Table 1.2 Dataset features [31].
2 Chapter 5Table 5.1 Similarity score of keyword ‘Authentication’ in various Document ID.Table 5.2 Similarity score of keyword ‘SQL injection’ in various documents.Table 5.3 Accuracy for searching cyber-attack related keywords using hybrid appr...
3 Chapter 6Table 6.1 Topics in the dataset.Table 6.2 Events present in the topics.Table 6.3 Precision.Table 6.4 Sensitivity.Table 6.5 Specificity.Table 6.6 Accuracy.
4 Chapter 8Table 8.1 Features extracted from Wireshark.Table 8.2 Rules generated.Table 8.3 Error rate.
5 Chapter 9Table 9.1 The representation schemes along with matching algorithms for Biometri...Table 9.2 Comparisons of Biometric Identifiers on the basis of various factors [...Table 9.3 Examples of apps using biometric recognizance [39, 40].Table 9.4 Advantages & disadvantages of biometric