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Table of Contents
Preface; Contents; Chapter 1: Introduction: Emerging Threats Call for New Security Paradigms; 1.1 Emerging Threats Landscape; 1.2 Next Generation Cybersecurity Systems; References; Chapter 2: Botnets Threat Analysis and Detection; 2.1 Introduction; 2.2 Evolution of Botnets: History and Topologies; 2.3 Famous Botnets; 2.3.1 ZeuS or Zbot; 2.3.2 Koobface; 2.3.3 Windigo; 2.4 Botnet Detection Evasion Techniques; 2.5 Botnet Detection Methodologies; 2.5.1 Passive Techniques; 2.5.1.1 Packet Inspection; 2.5.1.2 Analysis of Flow Records; 2.5.1.3 DNS-Based Approaches; 2.5.1.4 Analysis of Spam Records.
2.5.1.5 Analysis of (Application) Log Files2.5.1.6 Honeypots; 2.5.1.7 Evaluation of Antivirus; 2.5.1.8 Software Feedback; 2.5.2 Active Techniques; 2.5.2.1 Sinkholing; 2.5.2.2 DNS Cache Snooping; 2.5.2.3 Infiltration; 2.5.2.4 Tracking of Fast-Flux Network; 2.6 Defense Against Botnet Using Network Security Devices; 2.6.1 Intrusion Prevention and Detection Systems; 2.6.2 Network Firewalls; 2.6.2.1 Dynamic and Administrator Blacklist Data; 2.6.2.2 Traffic Classification and Reporting; 2.6.2.3 Domain Name System Snooping; 2.7 Security Measures Against Botnets; 2.7.1 Network Design.
2.7.1.1 Advance Threat Protection2.7.1.2 Intrusion Prevention and Detection System; 2.7.1.3 Email Security Systems; 2.7.1.4 Forensic Analysis; 2.7.1.5 Security Event Monitoring; 2.7.2 Application Usage; 2.7.2.1 HIPS (Host-Based Intrusion Prevention System); 2.7.2.2 End Point Security; 2.7.2.3 Application Firewall; 2.8 Conclusion; References; Chapter 3: Collective Framework for Fraud Detection Using Behavioral Biometrics; 3.1 Background; 3.2 Fraud Detection Framework; 3.3 Behavioral Identity Verification; 3.4 Experimental Evaluation; 3.4.1 Evaluation Metrics and Procedures; 3.4.2 Results.
3.5 ConclusionReferences; Chapter 4: The Hardware Trojan System: An Online Suite of Tools for Hardware Trojan Analysis; 4.1 Introduction; 4.2 Hardware Trojan Analysis Techniques; 4.2.1 Trojan Classification; 4.2.2 Trojan Evaluation; 4.3 The Hardware Trojan System; 4.3.1 The Classification Tool; 4.3.2 The Evaluation Tool; 4.3.3 The Web Environment; 4.4 Case Study; 4.4.1 Classification Tool; 4.4.2 Evaluation Tool; 4.5 Conclusion; References; Chapter 5: Combining Mouse and Eye Movement Biometrics for User Authentication; 5.1 Introduction; 5.2 Related Work.
5.2.1 Previous Research on Mouse Movements5.2.2 Previous Research on Eye Movements; 5.3 Experiment Setting and Design; 5.3.1 Experiment Setting; 5.3.2 Participants; 5.3.3 Experiment Design; 5.3.4 Experiment Procedure; 5.4 Data Processing and Feature Extraction; 5.4.1 Data Alignment; 5.4.2 Data Cleaning; 5.4.3 Data Visualization; 5.4.4 Feature Extraction; 5.5 Proposed Approaches; 5.5.1 Simple Multi-class Classification Model; 5.5.2 Binary Classification Model; 5.5.3 Regression Model Using Fusion; 5.6 Result and Discussion; 5.7 Conclusion and Future Research Direction; References.
2.5.1.5 Analysis of (Application) Log Files2.5.1.6 Honeypots; 2.5.1.7 Evaluation of Antivirus; 2.5.1.8 Software Feedback; 2.5.2 Active Techniques; 2.5.2.1 Sinkholing; 2.5.2.2 DNS Cache Snooping; 2.5.2.3 Infiltration; 2.5.2.4 Tracking of Fast-Flux Network; 2.6 Defense Against Botnet Using Network Security Devices; 2.6.1 Intrusion Prevention and Detection Systems; 2.6.2 Network Firewalls; 2.6.2.1 Dynamic and Administrator Blacklist Data; 2.6.2.2 Traffic Classification and Reporting; 2.6.2.3 Domain Name System Snooping; 2.7 Security Measures Against Botnets; 2.7.1 Network Design.
2.7.1.1 Advance Threat Protection2.7.1.2 Intrusion Prevention and Detection System; 2.7.1.3 Email Security Systems; 2.7.1.4 Forensic Analysis; 2.7.1.5 Security Event Monitoring; 2.7.2 Application Usage; 2.7.2.1 HIPS (Host-Based Intrusion Prevention System); 2.7.2.2 End Point Security; 2.7.2.3 Application Firewall; 2.8 Conclusion; References; Chapter 3: Collective Framework for Fraud Detection Using Behavioral Biometrics; 3.1 Background; 3.2 Fraud Detection Framework; 3.3 Behavioral Identity Verification; 3.4 Experimental Evaluation; 3.4.1 Evaluation Metrics and Procedures; 3.4.2 Results.
3.5 ConclusionReferences; Chapter 4: The Hardware Trojan System: An Online Suite of Tools for Hardware Trojan Analysis; 4.1 Introduction; 4.2 Hardware Trojan Analysis Techniques; 4.2.1 Trojan Classification; 4.2.2 Trojan Evaluation; 4.3 The Hardware Trojan System; 4.3.1 The Classification Tool; 4.3.2 The Evaluation Tool; 4.3.3 The Web Environment; 4.4 Case Study; 4.4.1 Classification Tool; 4.4.2 Evaluation Tool; 4.5 Conclusion; References; Chapter 5: Combining Mouse and Eye Movement Biometrics for User Authentication; 5.1 Introduction; 5.2 Related Work.
5.2.1 Previous Research on Mouse Movements5.2.2 Previous Research on Eye Movements; 5.3 Experiment Setting and Design; 5.3.1 Experiment Setting; 5.3.2 Participants; 5.3.3 Experiment Design; 5.3.4 Experiment Procedure; 5.4 Data Processing and Feature Extraction; 5.4.1 Data Alignment; 5.4.2 Data Cleaning; 5.4.3 Data Visualization; 5.4.4 Feature Extraction; 5.5 Proposed Approaches; 5.5.1 Simple Multi-class Classification Model; 5.5.2 Binary Classification Model; 5.5.3 Regression Model Using Fusion; 5.6 Result and Discussion; 5.7 Conclusion and Future Research Direction; References.