This paper is published in Volume-6, Issue-4, 2020
Area
Electrical Engineering
Author
Ravinderpal Singh
Co-authors
Puneet Jain
Org/Univ
Adesh Institute of Engineering and Technology, Faridkot, Punjab, India
Pub. Date
29 July, 2020
Paper ID
V6I4-1285
Publisher
Keywords
Smart Grid, Privacy-Preserving, ANU, Perturbation

Citationsacebook

IEEE
Ravinderpal Singh, Puneet Jain. Lightweight privacy-preserving scheme for the smart grid data using ANU and Perturbation Algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Ravinderpal Singh, Puneet Jain (2020). Lightweight privacy-preserving scheme for the smart grid data using ANU and Perturbation Algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 6(4) www.IJARIIT.com.

MLA
Ravinderpal Singh, Puneet Jain. "Lightweight privacy-preserving scheme for the smart grid data using ANU and Perturbation Algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 6.4 (2020). www.IJARIIT.com.

Abstract

Smart Grid collects the data of smart meter and communicates the data to electricity generation, pricing, and billing departments. The departments used this information for electricity forecasting, real-time pricing, and generate electricity bills. The smart grid data contains customer personal information as well as electricity consumption details. Thus, sharing all information with the departments violates customer privacy. In addition, if no security mechanism provided for the data makes it prone to the attacks. In this paper, we have proposed a privacy-preserving algorithm for smart grid data security. The algorithm has two-phase. In the first phase, customer personal information and electricity consumption details separated. In the second phase, the customer's personal information is secured using a lightweight algorithm ANU and electricity consumption details are secured using noise addition on the data by applying the perturbation algorithm. The algorithm is coded and simulated in the MATLAB 2013a. The experimental results show that the proposed technique consumes less memory and provides better security as compared to the existing algorithms.
Paper PDF