Intro; Preface; Contents; Acronyms; 1 Introduction; 1.1 Background; 1.2 Definition of Location Privacy; 1.2.1 Location-Based Services; 1.2.2 Representation of Location Information; 1.2.3 The Definition of Location Privacy; 1.2.4 Location Privacy Versus Data Privacy; 1.3 Location Attacks and Adversaries; 1.3.1 Location Information Obtaining Methods; 1.3.2 Types of Adversarial Knowledge; 1.3.3 Attack Targets; 1.3.4 Types of Attack Methods; 1.3.5 Emerging Trends; 1.4 People's View About Location Privacy

1.4.1 Do People Really Know How Much of Their Location Information Has Been Collected or Revealed?1.4.2 How Do People Care About Their Location Privacy?; 1.5 Location-Based Services in Practical Applications; 1.6 The Unified Location Privacy Research Framework; 1.7 Outline and Book Overview; References; 2 Location Privacy-Preserving Mechanisms; 2.1 Cryptographic Mechanism; 2.2 Anonymization Mechanisms; 2.2.1 k-Anonymity; 2.2.2 Mix-Zone; 2.3 Obfuscation Mechanisms; 2.3.1 Dummy Locations; 2.3.2 Location Obfuscation; 2.3.3 Differential Privacy-Based Methods

2.4 Reducing Location Information Sharing2.4.1 Caching; 2.4.2 Game Theory; 2.5 Comparisons and Discussions; 2.5.1 LPPMs Versus Other Privacy Preservation Techniques; 2.5.2 Comparisons of the Four Different Groups; 2.6 Performance Evaluation: Location Privacy Metrics; 2.6.1 Certainty; 2.6.2 Correctness; 2.6.3 Information Gain or Loss; 2.6.4 Geo-Indistinguishability; 2.6.5 Time; 2.6.6 Discussion on Performance Metrics; References; 3 Location Privacy in Mobile Social Network Applications; 3.1 Introduction; 3.2 Sensitive Location Prediction by Users Social Network Data

3.2.1 Content-Based Approach3.2.2 Check-In-Based Approach; 3.2.3 Check-In Behavior of Users in Mobile Social Networks; 3.2.4 Home Location Prediction Algorithms; 3.2.5 The Adversary and Attack Models; 3.2.6 Privacy Metrics; 3.3 Protecting Important Locations in Social Networks; 3.3.1 Community-Based Geo-Location Information Sharing Scheme; 3.3.2 Aggregated Check-In Behavior of Users in a Community; 3.3.3 Datasets and Evaluation Setup; 3.3.4 Impact on Spatial Feature of the Check-Ins; 3.3.5 Impact on Home Location Prediction Algorithms; 3.4 Summary; References

4 Location Privacy in Mobile Crowd Sensing Applications4.1 Introduction; 4.2 System Model and Problem Formulation; 4.2.1 The General Mobile Crowd Sensing System; 4.2.2 The Basic Idea of Privacy-Preserving MCS Application Framework; 4.2.3 Location Privacy Metric; 4.2.4 Economic Models for the MCS Application; 4.2.5 Problem Formulation; 4.3 Privacy-Preserving MCS Schemes Based on Economic Models; 4.3.1 The Monopoly Model-Based Scheme (MMBS); 4.3.2 Cournot's Oligopoly Model-Based Scheme (COMBS); 4.3.3 Privacy Analysis of Our Proposed Schemes; 4.4 Performance Evaluation; 4.4.1 Simulation Setup