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An efficient data aggregation scheme with local differential privacy in smart grid 被引量:6
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作者 na gai Kaiping Xue +3 位作者 Bin Zhu Jiayu Yang Jianqing Liu Debiao He 《Digital Communications and Networks》 SCIE CSCD 2022年第3期333-342,共10页
By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the ... By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the smart grid collect the users' power usage data on a regular basis and upload it to the control center to complete the smart grid data acquisition. The control center can evaluate the supply and demand of the power grid through aggregated data from users and then dynamically adjust the power supply and price, etc. However, since the grid data collected from users may disclose the user's electricity usage habits and daily activities, privacy concern has become a critical issue in smart grid data aggregation. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring a trusted third party. 展开更多
关键词 Local differential privacy Data aggregation Smart grid Privacy preserving
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