A verifiable and privacy‐preserving multidimensional data aggregation scheme in mobile crowdsensing

Author(s):  
Yun Jiang ◽  
Bowen Zhao ◽  
Shaohua Tang ◽  
Hao‐Tian Wu
2020 ◽  
pp. 1-12
Author(s):  
Xiangjian Zuo ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Shoushan Luo ◽  
Yixian Yang

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yousheng Zhou ◽  
Xinyun Chen ◽  
Meihuan Chen

In a smart grid, data aggregation is a common method to evaluate regional power consumption. Data leakage in the process of data transmission poses a security threat to the privacy of users. Many existing data aggregation schemes can only aggregate one-dimensional data; however, it is necessary to aggregate multidimensional data in practical smart grid applications. Therefore, this paper proposes a privacy-preserving multidimensional data aggregation scheme, which can aggregate multidimensional data and protect the individual user’s identity and data privacy. The security of the proposed scheme is proved under the random oracle model. The simulation results show that the proposed scheme has great advantages in computing overhead, and the communication overhead also meets the requirements of the smart grid.


2021 ◽  
pp. 1-10
Author(s):  
Hongyang Li ◽  
Qingfeng Cheng ◽  
Xinghua Li ◽  
Siqi Ma ◽  
Jianfeng Ma

2017 ◽  
Vol 8 (5) ◽  
pp. 2411-2419 ◽  
Author(s):  
Debiao He ◽  
Neeraj Kumar ◽  
Sherali Zeadally ◽  
Alexey Vinel ◽  
Laurence T. Yang

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