Visible to the public State Estimation Based Energy Theft Detection Scheme with Privacy Preservation in Smart Grid

TitleState Estimation Based Energy Theft Detection Scheme with Privacy Preservation in Smart Grid
Publication TypeConference Paper
Year of Publication2018
AuthorsWen, M., Yao, D., Li, B., Lu, R.
Conference Name2018 IEEE International Conference on Communications (ICC)
Keywordsabnormal data, abnormal users, attacked meters, composability, cryptography, data privacy, Data Transmission, electricity bill payments, energy consumption, energy savings, energy theft behaviors, Human Behavior, individual households, information privacy issues, Local area networks, Logic gates, Metrics, power engineering computing, power system security, PPTD scheme, privacy, privacy preservation, privacy-preserving energy theft detection scheme, pubcrawl, recursive filter, recursive filters, security, Smart grid, Smart Grid Privacy, Smart grids, smart meters, smart power grids, state estimation based energy theft detection scheme

The increasing deployment of smart meters at individual households has significantly improved people's experience in electricity bill payments and energy savings. It is, however, still challenging to guarantee the accurate detection of attacked meters' behaviors as well as the effective preservation of users'privacy information. In addition, rare existing research studies jointly consider both these two aspects. In this paper, we propose a Privacy-Preserving energy Theft Detection scheme (PPTD) to address the energy theft behaviors and information privacy issues in smart grid. Specifically, we use a recursive filter based on state estimation to estimate the user's energy consumption, and detect the abnormal data. During data transmission, we use the lightweight NTRU algorithm to encrypt the user's data to achieve privacy preservation. Security analysis demonstrates that in the PPTD scheme, only authorized units can transmit/receive data, and data privacy are also preserved. The performance evaluation results illustrate that our PPTD scheme can significantly reduce the communication and computation costs, and effectively detect abnormal users.

Citation Keywen_state_2018