1. EPMDA-FED: Efficient and Privacy-Preserving Multidimensional Data Aggregation Scheme With Fast Error Detection in Smart Grid
- Author
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Tian Liu, Xiaopeng Zhao, Zhusen Liu, Zhenfu Cao, Xiaolei Dong, Haiyong Bao, and Jiachen Shen
- Subjects
Computer Networks and Communications ,business.industry ,Computer science ,Distributed computing ,Homomorphic encryption ,Encryption ,Computer Science Applications ,Paillier cryptosystem ,Public-key cryptography ,Smart grid ,Hardware and Architecture ,Data integrity ,Signal Processing ,Overhead (computing) ,business ,Semantic security ,Information Systems - Abstract
Smart grids bring advantages of reliabilty and high efficiency by real-time communication technologies in contrast to the traditional grids. However, smart grids also raise concerns about privacy and security for the individual fine-grained information collection. In order to guarantee privacy and securtiy in the grids, we propose an efficient and privacy-preserving multidimensional data aggregation scheme without a third trusted party and supporting fast error detection, named EPMDA-FED, in the paper. Firstly, we adopt Chinese Remainder Theorem to pack multidimensional data and encrypt the processed data using the keys generated by the negotiation among users and the control center. Secondly, our scheme is efficient for encryption without high-cost additive homomorphic public key encryption scheme, such as Paillier cryptosystem and supporting batch verification with fast error detection. Our proposed error detection algorithm is quite efficient with sublinear computation complexity. Besides, through security analysis, EPMDA-FED is semantically secure against collusion attack and the consistency of negotiated key, authenticity and data integrity of the users’ reports are guaranteed. Finally, performance evaluation shows EPMDA-FED is more efficient than existing competing approaches in terms of computation and communication overhead.
- Published
- 2022