Abstract
In recent years, location-based social networks (LBSNs) such as Foursquare have emerged that enable users to share with each other, their (geographical) locations together with the semantic information associated with their locations. The semantic information captures the type of a location and is usually represented by a semantic tag. Semantic tag sharing increases the threat to users’ location privacy which is already at risk because of location sharing. The existing solution to protect the location privacy of users in such LBSNs is to obfuscate the location and the semantic tag independently of each other in a so called disjoint obfuscation approach. More precisely, in this approach, the semantic tag is obfuscated i.e., replaced by a more general tag. Also, the location is obfuscated i.e., replaced by a generalized area (called the cloaking area) made of the actual location and some of its nearby locations. However, since in this approach the location obfuscation is performed in a semantic-oblivious manner, an adversary can still increase his chance to infer the actual location by detecting semantic incompatibility between the locations in the cloaking area and the obfuscated semantic tag. In this work, we address this issue by proposing a joint obfuscation approach in which the location obfuscation is performed based on the result of the semantic tag obfuscation. We also provide a formal framework for evaluation and comparison of our joint approach with the disjoint approach. By running an experimental evaluation on a dataset of real-world user mobility traces, we show that in almost all cases (i.e., for different values of the obfuscation parameters), the joint approach outperforms the disjoint approach in terms of location privacy protection. We also study how different obfuscation parameters can affect the performance of the obfuscation approaches. In particular, we show how changing these parameters can improve the performance of the joint approach.
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Notes
- 1.
For simplicity’s sake, in this work we consider only obfuscation by generalization, both for locations and semantic tags.
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Acknowledgements
This research is partially funded by a UNIL/CHUV postdoc mobility grant disbursed by University of Lausanne and Lausanne University Hospital. We also thank Berker AÄźir for his comments and help regarding the disjoint obfuscation approach.
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Bostanipour, B., Theodorakopoulos, G. (2020). Joint Obfuscation for Privacy Protection in Location-Based Social Networks. In: Garcia-Alfaro, J., Navarro-Arribas, G., Herrera-Joancomarti, J. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2020 2020. Lecture Notes in Computer Science(), vol 12484. Springer, Cham. https://doi.org/10.1007/978-3-030-66172-4_7
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