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The aggregation of residents’ private data drives improvements in the smart homes, however it comes with compromising on privacy. Hence, privacy preservation has become an increasing requirement for residents. Since users might have different privacy requirements, and their privacy requirements might be sensitive information, smart homes need a privacy preservation scheme to meet their demands. In this scheme, a user preserves the privacy of his/her data and privacy level locally by specifying his own privacy level in confidence, without trusting anyone else in smart homes. In addition, a user replies a single data element to the collector each time, instead of the whole dataset. It makes the scheme more challenging than the traditional centralized situation. In this paper, we propose a novel personalized local differential privacy preservation scheme for smart homes, which retains desirable utility while providing rigorous privacy guarantee. Keywords-smart homes; aggregation; differential privacy;

Personalized Differential Privacy Preserving Data Aggregation for Smart Homes