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Table of Contents
Intro; Preface; Contents; Acronyms; 1 Introduction; 1.1 Fog Computing; 1.2 Fog-Enabled IoT; 1.2.1 Architecture of Fog-Enabled IoT; 1.2.2 Applications of Fog-Enabled IoT; 1.2.2.1 Smart Parking Navigation; 1.2.2.2 Mobile Crowdsensing; 1.2.2.3 Smart Grid; 1.3 Security and Privacy Challenges; 1.4 Aim of the Monograph; References; 2 Privacy-Enhancing Technologies; 2.1 Identity Privacy-Enhancing Techniques; 2.1.1 Pseudonymization; 2.1.2 k-Anonymity; 2.1.3 Mix-Network; 2.1.4 Blind Signature; 2.1.5 Group Signature; 2.1.6 Ring Signature; 2.2 Location Privacy-Enhancing Techniques; 2.2.1 Obfuscation.
2.2.2 Differential Location Privacy2.2.3 Privacy-Preserving Location Matching; 2.3 Data Privacy-Enhancing Techniques; 2.3.1 Randomization; 2.3.2 Data Encryption; 2.3.3 Differential Privacy; 2.3.4 Zero-Knowledge Proof; 2.4 Summary; References; 3 Identity Privacy Protection in Smart Parking Navigation; 3.1 Problem Statement; 3.1.1 System Model; 3.1.2 Security Threats; 3.1.3 Security Goals; 3.2 P-SPAN; 3.2.1 Overview of P-SPAN; 3.2.2 The Detailed P-SPAN; 3.2.2.1 System Setup; 3.2.2.2 Service Registration; 3.2.2.3 Parking Query; 3.2.2.4 Result Retrieval; 3.2.2.5 Driver Tracing.
3.3 Security Discussion3.4 Retrieving Probability and Performance Analysis; 3.4.1 Retrieving Probability; 3.4.2 Computational Overhead; 3.4.3 Communication Overhead; 3.5 Summary; References; 4 Location Privacy Protection in Mobile Crowdsensing; 4.1 Problem Statement; 4.1.1 System Model; 4.1.2 Threat Model; 4.1.3 Design Goals; 4.2 PPFMC; 4.3 Security Discussion; 4.4 Performance Evaluation; 4.4.1 Computational Overhead; 4.4.2 Communication Overhead; 4.5 Summary; References; 5 Data Privacy Protection in Smart Grid; 5.1 Problem Statement; 5.1.1 System Model; 5.1.2 Security Model.
5.1.3 Design Goals5.2 P2SM; 5.2.1 Overview of P2SM; 5.2.2 The Detailed P2SM; 5.2.2.1 System Initialization; 5.2.2.2 Customer Registration; 5.2.2.3 Report Generation; 5.2.2.4 Report Aggregation; 5.2.2.5 Report Reading; 5.2.2.6 Dynamic Billing; 5.3 Security Analysis; 5.4 Performance Evaluation; 5.4.1 Computational Cost; 5.4.2 Communication and Storage Overhead; 5.5 Summary; References; 6 Summary and Future Directions; 6.1 Summary; 6.2 Future Research Directions; 6.2.1 Detection of Rogue Fogs and Devices; 6.2.2 Privacy Exposure in Data Combination.
2.2.2 Differential Location Privacy2.2.3 Privacy-Preserving Location Matching; 2.3 Data Privacy-Enhancing Techniques; 2.3.1 Randomization; 2.3.2 Data Encryption; 2.3.3 Differential Privacy; 2.3.4 Zero-Knowledge Proof; 2.4 Summary; References; 3 Identity Privacy Protection in Smart Parking Navigation; 3.1 Problem Statement; 3.1.1 System Model; 3.1.2 Security Threats; 3.1.3 Security Goals; 3.2 P-SPAN; 3.2.1 Overview of P-SPAN; 3.2.2 The Detailed P-SPAN; 3.2.2.1 System Setup; 3.2.2.2 Service Registration; 3.2.2.3 Parking Query; 3.2.2.4 Result Retrieval; 3.2.2.5 Driver Tracing.
3.3 Security Discussion3.4 Retrieving Probability and Performance Analysis; 3.4.1 Retrieving Probability; 3.4.2 Computational Overhead; 3.4.3 Communication Overhead; 3.5 Summary; References; 4 Location Privacy Protection in Mobile Crowdsensing; 4.1 Problem Statement; 4.1.1 System Model; 4.1.2 Threat Model; 4.1.3 Design Goals; 4.2 PPFMC; 4.3 Security Discussion; 4.4 Performance Evaluation; 4.4.1 Computational Overhead; 4.4.2 Communication Overhead; 4.5 Summary; References; 5 Data Privacy Protection in Smart Grid; 5.1 Problem Statement; 5.1.1 System Model; 5.1.2 Security Model.
5.1.3 Design Goals5.2 P2SM; 5.2.1 Overview of P2SM; 5.2.2 The Detailed P2SM; 5.2.2.1 System Initialization; 5.2.2.2 Customer Registration; 5.2.2.3 Report Generation; 5.2.2.4 Report Aggregation; 5.2.2.5 Report Reading; 5.2.2.6 Dynamic Billing; 5.3 Security Analysis; 5.4 Performance Evaluation; 5.4.1 Computational Cost; 5.4.2 Communication and Storage Overhead; 5.5 Summary; References; 6 Summary and Future Directions; 6.1 Summary; 6.2 Future Research Directions; 6.2.1 Detection of Rogue Fogs and Devices; 6.2.2 Privacy Exposure in Data Combination.