Nash Equilibria of Packet Forwarding Strategies in Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Security and Cooperation in Wireless Networks: Thwarting Malicious and Selfish Behavior in the Age of Ubiquitous Computing
A survey of computational location privacy
Personal and Ubiquitous Computing
On non-cooperative location privacy: a game-theoretic analysis
Proceedings of the 16th ACM conference on Computer and communications security
Achieving efficient query privacy for location based services
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
Challenges and business models for mobile location-based services and advertising
Communications of the ACM
Tracking games in mobile networks
GameSec'10 Proceedings of the First international conference on Decision and game theory for security
Network Security: A Decision and Game-Theoretic Approach
Network Security: A Decision and Game-Theoretic Approach
Collaborative Location Privacy
MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
Exploring dependency for query privacy protection in location-based services
Proceedings of the third ACM conference on Data and application security and privacy
Protecting query privacy in location-based services
Geoinformatica
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Recent smartphones incorporate embedded GPS devices that enable users to obtain geographic information about their surroundings by providing a location-based service (LBS) with their current coordinates. However, LBS providers collect a significant amount of data from mobile users and could be tempted to misuse it, by compromising a customer's location privacy (her ability to control the information about her past and present location). Many solutions to mitigate this privacy threat focus on changing both the architecture of location-based systems and the business models of LBS providers. MobiCrowd does not introduce changes to the existing business practices of LBS providers, rather it requires mobile devices to communicate wirelessly in a peer-to-peer fashion. To lessen the privacy loss, users seeking geographic information try to obtain this data by querying neighboring nodes, instead of connecting to the LBS. However, such a solution will only function if users are willing to share regional data obtained from the LBS provider. We model this collaborative location-data sharing problem with rational agents following threshold strategies. Initially, we study agent cooperation by using pure game theory and then by combining game theory with an epidemic model that is enhanced to support threshold strategies to address a complex multi-agent scenario. From our game-theoretic analysis, we derive cooperative and non-cooperative Nash equilibria and the optimal threshold that maximizes agents' expected utility.