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An efficient secure scheme for lossy and lossless data aggregation in smart grid

Sarenche, R ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/ISTEL.2018.8661157
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. In this paper, we propose an efficient secure data aggregation scheme for the smart grid, which supports both lossy and lossless data aggregation. In order to reduce the computational overhead of the control center, our proposed model includes a number of entities, called gateways, which act as intermediaries between the users and the control center. At the end of each measurement interval, each user generates a report which is encrypted using the Paillier cryptosystem and contains the user's consumption amount during the previous measurement interval as well as his or her prediction of consumption during another interval in the future. After receiving the user's reports, gateways perform both lossy and lossless aggregation on the encrypted reports without being aware of their contents. In lossy aggregation mode, thanks to the homomorphic property of Paillier cryptosystem, the gateways generate the aggregated data of users' predictions in order to help the control center to estimate the future electricity usage of the grid. In the lossless aggregation mode, gateways provide the control center with the users' billing information. Moreover, to encourage the users to predict their future consumption amounts more precisely, this scheme uses special billing policies in which the accuracy of users' predictions can affect their total electricity costs. © 2018 IEEE
  6. Keywords:
  7. Costs ; Cryptography ; Forecasting ; Smart power grids ; Billing ; Computational overheads ; Data aggregation ; Measurement interval ; Paillier cryptosystem ; Secure data aggregations ; Security ; Smart grid ; Electric power transmission networks
  8. Source: 9th International Symposium on Telecommunication, IST 2018, 17 December 2018 through 19 December 2018 ; 2019 , Pages 528-534 ; 9781538682746 (ISBN)
  9. URL: https://ieeexplore.ieee.org/abstract/document/8661157