Achieving differential privacy of data disclosure in the smart grid

2014 ◽  
Author(s):  
Jing Zhao ◽  
Taeho Jung ◽  
Yu Wang ◽  
Xiangyang Li
Keyword(s):  
Smart Grid ◽  
Differential Privacy

A Decentralized Mechanism Based on Differential Privacy for Privacy-Preserving Computation in Smart Grid

2021 ◽  
pp. 1-1
Author(s):  
Zhigao Zheng ◽  
Tao Wang ◽  
Ali Kashif Bashir ◽  
Mamoun Alazab ◽  
Shahid Mumtaz ◽  
...  
Keyword(s):  
Smart Grid ◽  
Differential Privacy ◽  
Privacy Preserving ◽  
Decentralized Mechanism

Towards Differential Privacy-Based Online Double Auction for Smart Grid

2020 ◽  
Vol 15 ◽  
pp. 971-986 ◽  
Author(s):  
Donghe Li ◽  
Qingyu Yang ◽  
Wei Yu ◽  
Dou An ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Smart Grid ◽  
Differential Privacy ◽  
Double Auction

scholarly journals Privacy-Preserving Publication of Time-Series Data in Smart Grid

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Franklin Leukam Lako ◽  
Paul Lajoie-Mazenc ◽  
Maryline Laurent
Keyword(s):  
Time Series ◽  
Smart Grid ◽  
Differential Privacy ◽  
Time Series Data ◽  
Real Data ◽  
Series Data ◽  
Discrete Wavelet ◽  
Privacy Concern ◽  
Fine Grained ◽  
Grid Operators

The collection of fine-grained consumptions of users in the smart grid enables energy suppliers and grid operators to propose new services (e.g., consumption forecasts and demand-response protocols) allowing to improve the efficiency and reliability of the grid. These services require the knowledge of aggregate consumption of users. However, an aggregate can be vulnerable to reidentification attacks which allow revealing the users’ individual consumption. Revealing an aggregate data is a key privacy concern. This paper focuses on publishing an aggregate of time-series data such as fine-grained consumptions, without indirectly disclosing individual consumptions. We propose novel algorithms which guarantee differential privacy, based on the discrete Fourier transform and the discrete wavelet transform. Experimental results using real data from the Irish Commission for Regulation of Utilities (CRU) demonstrate that our algorithms achieve better utility than previously proposed algorithms.

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