About the Editors |
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xiii | |
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xv | |
Preface |
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xix | |
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1 Advanced Attacks and Protection Mechanisms in IoT Devices and Networks |
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1 | (30) |
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2 | (1) |
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1.2 Physical Security in IoT Devices |
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3 | (6) |
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3 | (1) |
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1.2.1.1 Side-channel Analysis Attacks |
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3 | (1) |
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1.2.1.2 Fault Analysis Attacks |
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4 | (1) |
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4 | (1) |
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1.2.3 Machine Learning and SCA |
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5 | (2) |
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7 | (1) |
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8 | (1) |
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1.3 Remote Attestation in IoT Devices |
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9 | (6) |
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1.3.1 Types of Remote Attestation |
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10 | (1) |
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1.3.1.1 Software-based Remote Attestation |
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10 | (1) |
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1.3.1.2 Hardware-based Remote Attestation |
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11 | (1) |
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1.3.1.3 Hybrid Architecture-based Remote Attestation |
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12 | (1) |
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1.3.2 Remote Attestation for Large IoT Networks |
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12 | (1) |
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1.3.2.1 Classical Swarm Attestation Techniques |
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12 | (2) |
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1.3.2.2 Swarm Attestation for IoT Services |
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14 | (1) |
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14 | (1) |
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1.3.3.1 Cloud-based RA Techniques |
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15 | (1) |
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1.3.3.2 RA in Novel Internet Technologies |
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15 | (1) |
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1.3.3.3 Blockchain Based RA |
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15 | (1) |
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1.4 Intrusion Detection in IoT Networks |
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15 | (16) |
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15 | (1) |
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1.4.2 Vulnerability Patching |
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16 | (1) |
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1.4.3 Signature- and Anomaly Detection-based Network Intrusion Detection |
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17 | (1) |
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1.4.4 Deep Learning-based Anomaly Detection |
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17 | (1) |
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18 | (1) |
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1.4.4.2 Modeling Packet Sequence Patterns |
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18 | (1) |
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1.4.4.3 Anomalous Packet Detection |
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19 | (1) |
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1.4.5 Federated Deep Learning-based IoT Intrusion Detection System |
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20 | (1) |
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1.4.5.1 Federated Learning |
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20 | (1) |
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1.4.5.2 Federated Self-Learning Anomaly Detection |
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20 | (2) |
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1.4.5.3 Challenges of Federated Learning-based Anomaly Detection System for IoT |
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22 | (1) |
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23 | (8) |
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2 Human Aspects of IoT Security and Privacy |
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31 | (26) |
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31 | (2) |
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2.2 An Overview of the Domestic IoT Environment |
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33 | (6) |
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2.3 Security Issues and the IoT Landscape |
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39 | (2) |
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2.4 Human Factors Challenges in IoT Security and Privacy |
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41 | (8) |
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2.4.1 Security Trade-offs for Individuals in IoT |
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43 | (1) |
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2.4.2 Data Ownership and Use |
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44 | (2) |
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2.4.3 Device Management and Administration Responsibilities |
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46 | (1) |
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2.4.4 The Age of Unwanted Intelligence |
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47 | (2) |
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2.5 Toward Improved User-facing Security in the IoT |
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49 | (2) |
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51 | (6) |
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51 | (1) |
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51 | (6) |
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3 Applying Zero Trust Security Principles to Defence Mechanisms Against Data Exfiltration Attacks |
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57 | (34) |
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57 | (2) |
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3.2 Data Exfiltration Types, Attack Mechanisms, and Defence Techniques |
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59 | (9) |
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3.2.1 Types of Data Exfiltration |
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59 | (1) |
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59 | (1) |
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60 | (1) |
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3.2.2 Data Exfiltration Attack Techniques |
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60 | (1) |
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60 | (1) |
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61 | (2) |
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3.2.3 Insider Data Exfiltration Threats |
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63 | (1) |
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3.2.3.1 Types of Insider Threats |
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63 | (2) |
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3.2.4 Approaches to Counter Data Exfiltration |
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65 | (1) |
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65 | (1) |
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66 | (1) |
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66 | (1) |
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3.2.5 Mechanisms to Defend Against Physical Data Exfiltration |
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67 | (1) |
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67 | (1) |
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67 | (1) |
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3.3 A Defence Mechanism for Physical Data Exfiltration Mitigation |
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68 | (7) |
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3.3.1 Confidential Data Identification |
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68 | (2) |
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3.3.2 Endpoint Access Rules |
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70 | (2) |
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3.3.3 Data Fingerprinting |
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72 | (1) |
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3.3.4 Relevance to Physical-Layer Protection |
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73 | (1) |
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3.3.5 Complementing Existing Firewall and Application-based Measures |
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73 | (2) |
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3.4 Implementation and Analysis |
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75 | (5) |
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75 | (2) |
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77 | (1) |
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3.4.3 Scenario Execution and Analysis |
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77 | (3) |
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80 | (6) |
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81 | (1) |
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82 | (1) |
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82 | (1) |
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83 | (1) |
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3.5.5 Results Analysis and Discussion |
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84 | (2) |
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86 | (5) |
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86 | (5) |
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4 eSIM-Based Authentication Protocol for UAV Remote Identification |
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91 | (32) |
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91 | (2) |
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93 | (5) |
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4.2.1 Drone Security in UTM |
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93 | (1) |
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94 | (1) |
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94 | (1) |
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4.2.1.3 Cyber-Physical Attacks |
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94 | (1) |
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4.2.2 Security Attacks on Drones |
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95 | (1) |
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4.2.3 Security Attacks from Drones |
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96 | (1) |
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4.2.3.1 Spying and Surveillance |
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96 | (1) |
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96 | (1) |
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97 | (1) |
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97 | (1) |
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98 | (2) |
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4.3.1 Drone Detection and Classification |
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98 | (1) |
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4.3.2 Interdiction Technologies |
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98 | (2) |
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4.4 UAV Remote Identification |
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100 | (3) |
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4.5 Authentication Protocol for Remote Identification |
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103 | (14) |
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104 | (1) |
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4.5.1.1 Assumptions and Notations |
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104 | (2) |
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106 | (1) |
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4.5.3 Secure Communication Protocol |
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107 | (1) |
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4.5.3.1 M1: A Challenge from the Operator (A) to the Drone (B) |
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108 | (1) |
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4.5.3.2 M2: A Response from the Drone (B) to the Operator (A) |
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109 | (1) |
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4.5.3.3 M3: Control Message from the Operator to the Drone |
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109 | (1) |
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4.5.3.4 M4: Drone's Response to the Control Message |
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110 | (1) |
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4.5.3.5 M5: Secure Broadcast of Remote Identification Message |
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110 | (1) |
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110 | (2) |
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4.5.5 Formal Verification |
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112 | (1) |
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4.5.5.1 Declaration of User-Defined Types and Terms |
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112 | (1) |
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4.5.5.2 Declaration of Cryptographic Primitives |
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113 | (1) |
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114 | (1) |
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4.5.5.4 Reachability and Secrecy Checking |
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114 | (1) |
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4.5.5.5 Verifying Mutual Authentication |
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115 | (2) |
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117 | (6) |
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117 | (6) |
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5 Collaborative Intrusion Detection in the Era of IoT: Recent Advances and Challenges |
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123 | (28) |
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123 | (1) |
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124 | (4) |
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5.2.1 Background on Intrusion Detection System |
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124 | (2) |
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5.2.2 Collaborative Intrusion Detection Framework |
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126 | (2) |
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5.3 Recent Development of Collaborative Intrusion Detection |
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128 | (8) |
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5.4 Open Challenges and Future Trend |
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136 | (5) |
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5.4.1 Advanced Insider Threats |
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136 | (1) |
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136 | (1) |
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137 | (1) |
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5.4.2 Open Challenges and Limitations |
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138 | (1) |
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139 | (2) |
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141 | (10) |
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141 | (10) |
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6 Cyber-Securing IoT Infrastructure by Modeling Network Traffic |
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151 | (26) |
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Hassan Habibi Gharakheili |
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151 | (2) |
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6.2 Cyber-Attacks on IoT Infrastructure |
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153 | (9) |
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154 | (1) |
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154 | (1) |
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6.2.2 Network Activity Analysis |
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154 | (1) |
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154 | (1) |
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6.2.3 Active Reconnaissance |
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155 | (1) |
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155 | (1) |
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156 | (1) |
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156 | (1) |
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6.2.5 Masquerading Attack |
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157 | (1) |
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157 | (1) |
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158 | (1) |
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158 | (1) |
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6.2.7 Active Crypto Attack |
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158 | (1) |
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159 | (1) |
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159 | (1) |
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159 | (1) |
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160 | (1) |
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160 | (1) |
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6.2.10 Sleep Deprivation Attack |
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160 | (1) |
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161 | (1) |
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6.2.11 Trigger Action Attack |
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161 | (1) |
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161 | (1) |
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6.3 Network Behavioral Model of IoTs |
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162 | (8) |
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6.3.1 Enforcing MUD Profile to Network |
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162 | (2) |
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6.3.2 MUD Protection Against Attacks |
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164 | (2) |
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166 | (1) |
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166 | (2) |
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168 | (1) |
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6.3.3 Monitoring MUD Activity |
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169 | (1) |
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170 | (7) |
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170 | (7) |
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7 Integrity of IoT Network Flow Records in Encrypted Traffic Analytics |
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177 | (6) |
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177 | (3) |
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180 | (3) |
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7.2.1 Encrypted Traffic Analytics (ETA) |
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180 | (1) |
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181 | (1) |
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7.2.3 Hashing for Flow Record Authentication |
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182 | (1) |
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183 | (24) |
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183 | (1) |
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7.3.2 Flow-Based Approaches |
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183 | (2) |
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7.3.3 Threats on Flow Telemetry |
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185 | (1) |
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7.4 Hashing-Based MAC for Telemetry Data |
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186 | (3) |
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7.5 Experimental Analysis |
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189 | (10) |
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7.5.1 Hashed Flow Records |
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189 | (3) |
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7.5.2 Symmetric Encryption with Hashed Flow Records |
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192 | (3) |
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7.5.3 Asymmetric Encryption with Hashed Flow Records |
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195 | (4) |
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199 | (8) |
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200 | (1) |
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200 | (1) |
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200 | (7) |
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8 Securing Contemporary eHealth Architectures: Techniques and Methods |
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207 | (28) |
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207 | (1) |
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208 | (7) |
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8.2.1 Why IoT Is Important in eHealth? |
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209 | (1) |
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8.2.2 Fog or Edge Computing for eHealth |
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210 | (2) |
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8.2.3 Cloud Computing for eHealth |
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212 | (1) |
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8.2.4 Applications of IoT in eHealth |
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212 | (1) |
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8.2.4.1 Sleep Monitoring System |
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212 | (1) |
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8.2.4.2 Real Time and Advanced Health Diagnoses |
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213 | (1) |
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8.2.4.3 Emotion Detection |
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213 | (1) |
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8.2.4.4 Nutrition Monitoring System |
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213 | (1) |
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8.2.4.5 Detection of Dyslexia |
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213 | (1) |
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213 | (1) |
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8.2.5.1 Implications of eHealth Security for Smart Cities |
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214 | (1) |
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8.3 eHealth Threat Landscape |
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215 | (6) |
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8.3.1 eHealth Threat Model |
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215 | (1) |
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216 | (1) |
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8.3.1.2 eHealth Attack Agents |
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216 | (2) |
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8.3.2 eHealth IoT Vulnerabilities and Threats |
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218 | (1) |
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218 | (1) |
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8.3.2.2 Attacks in Communication Layer |
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219 | (1) |
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8.3.2.3 Attacks in Healthcare Provider Layer |
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219 | (2) |
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221 | (1) |
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221 | (8) |
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8.4.1 Patient Data Protection |
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223 | (1) |
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8.4.2 Device and Communication Security Measures |
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224 | (1) |
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8.4.2.1 Securing Communication |
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225 | (1) |
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8.4.3 Adaptive Security Framework |
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226 | (2) |
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228 | (1) |
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229 | (6) |
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230 | (5) |
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9 Security and Privacy of Smart Homes: Issues and Solutions |
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235 | (26) |
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235 | (1) |
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9.2 State-of-the-Art in Smart Homes' Security and Privacy |
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236 | (8) |
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9.2.1 Smart Home Technologies |
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236 | (1) |
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9.2.2 User-Centric Privacy |
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237 | (1) |
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9.2.3 Consequences of Data Breaches |
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238 | (1) |
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9.2.4 Dimensions of Privacy Concerns |
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239 | (1) |
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9.2.5 Consequences of Information Security |
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240 | (2) |
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9.2.6 A Framework for Security and Privacy Concerns |
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242 | (2) |
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9.3 Privacy Techniques and Mechanisms |
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244 | (6) |
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244 | (2) |
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246 | (1) |
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247 | (1) |
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248 | (1) |
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9.3.5 UI/UX, User Awareness, and Control |
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249 | (1) |
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9.4 Toward Future Solutions |
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250 | (1) |
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251 | (10) |
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252 | (9) |
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10 IoT Hardware-Based Security: A Generalized Review of Threats and Countermeasures |
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261 | (36) |
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261 | (1) |
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262 | (12) |
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262 | (2) |
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10.2.1.1 Node-Level Threats |
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264 | (2) |
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266 | (3) |
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10.2.2 Hardware Design Threats |
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269 | (1) |
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269 | (1) |
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10.2.2.2 Reverse Engineering |
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269 | (1) |
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10.2.2.3 Intellectual Property Hijacking |
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270 | (1) |
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10.2.2.4 Hardware Trojans |
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270 | (1) |
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10.2.3 Side-Channel Attacks |
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270 | (1) |
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10.2.3.1 Types of Side-Channel Attacks |
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271 | (3) |
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10.3 Physical Security Attacks Countermeasures |
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274 | (15) |
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10.3.1 Mitigation Techniques for IoT Hardware Attacks |
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275 | (1) |
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10.3.2 Side-Channel Attacks |
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275 | (1) |
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10.3.2.1 Hardware Trojans |
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275 | (4) |
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10.3.2.2 Power Analysis Attack |
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279 | (4) |
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283 | (1) |
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10.3.2.4 Electromagnetic Analysis Attacks |
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284 | (1) |
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10.3.2.5 Acoustic Crypto-Analysis Attack |
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285 | (1) |
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10.3.3 Integrated Circuits Security |
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286 | (1) |
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286 | (1) |
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10.3.4 Radio Frequency Identification |
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287 | (1) |
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10.3.4.1 Physical Unclonable Function-based Authentication |
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287 | (1) |
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10.3.4.2 Preventing Physical Tampering Attacks (Enhancing Physical Security) |
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287 | (1) |
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10.3.4.3 Preventing Information Leakage |
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288 | (1) |
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10.3.4.4 Preventing Relay Attack |
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288 | (1) |
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289 | (8) |
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291 | (1) |
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291 | (6) |
Index |
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