Privacy-Preserving and Efficient Aggregation Based on Blockchain for Power Grid Communications in Smart Communities

By Zhitao Guan, Guanlin Si, Xiaosong Zhang, Longfei Wu, Nadra Guizani, Xiaojiang Du, Yinglong Ma. IEEE Communications Magazine, 2018

328 citations recorded by the source corpus.

Intelligence is one of the most important aspects in the development of our future communities. Ranging from smart home to smart building to smart city, all these smart infrastructures must be supported by intelligent power supply. Smart grid is proposed to solve all challenges of future electricity supply. In smart grid, in order to realize optimal scheduling, an SM is installed at each home to collect the near-real-time electricity consumption data, which can be used by the utilities to offer better smart home services. However, the near-real-time data may disclose a user's private information. An adversary may track the application usage patterns by analyzing the user's electricity consumption profile. In this article, we propose a privacy-preserving and efficient data aggregation scheme. We divide users into different groups, and each group has a private blockchain to record its members' data. To preserve the inner privacy within a group, we use pseudonyms to hide users' identities, and each user may create multiple pseudonyms and associate his/ her data with different pseudonyms. In addition, the bloom filter is adopted for fast authentication. The analysis shows that the proposed scheme can meet the security requirements and achieve better performance than other popular methods.

Subfields: Artificial Intelligence, Control and Systems Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/2d2c7cf5a6f8abe1fb7288f222c3416b721a9409

How researchers see this paper

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In Artificial Intelligence

  1. Francesco Longo
  2. Aruna Prasad Seneviratne
  3. Ming Ding
  4. Nenghai Yu
  5. Antonio Puliafito
  6. Dinh C. Nguyen
  7. Alfonso Panarello
  8. Pubudu N. Pathirana

In Control and Systems Engineering

  1. Pubudu N. Pathirana

In Information Systems

  1. Dinh C. Nguyen
  2. Pubudu N. Pathirana
  3. Ming Ding
  4. Aruna Prasad Seneviratne
  5. Francesco Longo
  6. Peilin Hong
  7. Kaiping Xue
  8. Nenghai Yu

Citations in the corpus