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PIF: A Personalized Fine-Grained Spam Filtering Scheme With Privacy Preservation in Mobile Social Networks
2015
IEEE Transactions on Computational Social Systems
Mobile social network (MSN) emerges as a promising social network paradigm that enables mobile users' information sharing in the proximity and facilitates their cyber-physical-social interactions. As the advertisements, rumors, and spams spread in MSNs, it is necessary to filter spams before they arrive at the recipients to make the MSN energy efficient. To this end, we propose a personalized fine-grained filtering scheme (PIF) with privacy preservation in MSNs. Specifically, we first develop a
doi:10.1109/tcss.2016.2519819
fatcat:tu3z53chyrcu7d5va3neduktaa