Abstract
Location privacy has drawn much attention among mobile social network users, as the geo-location information can be used by the adversaries to launch localization attacks which focus on finding people’s sensitive locations such as home and office place. In this paper, we propose a community based information sharing scheme to help the users to protect their home locations. First, we study the existing home location prediction algorithms and conclude that they are all mainly based on the spatial and temporal features of the check-in data. Then we design the community based information sharing scheme which aggregates the check-ins of all community members, thus change the overall spatial and temporal features. Finally, our simulation results validate that our proposed scheme greatly reduces the home location predication accuracy and therefore can protect the user’s privacy effectively.
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Liu, B. et al. (2017). Home Location Protection in Mobile Social Networks: A Community Based Method (Short Paper). In: Liu, J., Samarati, P. (eds) Information Security Practice and Experience. ISPEC 2017. Lecture Notes in Computer Science(), vol 10701. Springer, Cham. https://doi.org/10.1007/978-3-319-72359-4_43
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DOI: https://doi.org/10.1007/978-3-319-72359-4_43
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