Privacy-preserving data aggregation scheme against deletion and tampering attacks from aggregators

• Published in: Journal of King Saud University. Computer and information sciences 2023-04, Vol.35 (4), p.100-111
• Main Authors: Zhang, Jianhong, Dong, Chenghe
• Format: Article
• Language: English
• Subjects: Malicious attacks; Privacy-preserving data aggregation; Symmetric homomorphic encryption
• ISSN: 1319-1578; 2213-1248
• DOI: 10.1016/j.jksuci.2023.03.002

Because privacy-preserving data aggregation protocols provide data privacy and data compression, they have been extensively studied in smart grids. However, most of the existing data aggregation protocols are based on honest-but-curious aggregators, or adopt computationally intensive asymmetric homomorphic encryption, making these protocols only provably secure in weak security models, or resulting in high computational complexity for terminal users. To address the aforementioned issues, in this work, we propose a novel lightweight privacy-preserving data aggregation scheme against malicious aggregators based on our symmetric homomorphic encryption. The proposed scheme can reduce the computational cost of smart meters while also resisting tampering and deletion attacks from malicious aggregators. One of the highlights of the proposed scheme is its ability to withstand deletion attacks from malicious aggregators, which makes it unnecessary for the malicious aggregator to aggregate the readings of all smart meters instead of only a part of them. Therefore, our scheme is more secure than other schemes. It is the first privacy-preserving data aggregation scheme based on a stronger security model without multiple rounds of interaction. Finally, the detailed security analysis shows that the proposed scheme satisfies desirable security properties. Moreover, experimental results demonstrate that the proposed scheme is superior to the other four schemes in terms of computational complexity and communication overhead.