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28 July 2022 Privacy-preserving method of edge computing based on secret sharing and homomorphic encryption
HaoDong Xie, YuanBo Guo, HaoRan Wang, QingLi Chen, Chen Fang, Ning Zhu
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Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 123030E (2022) https://doi.org/10.1117/12.2642617
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China
Abstract
Edge computing has been applied to all aspects of our life, and has a good development prospect. But the problems of “isolated data island” and “data privacy security” hinder the development and application of technology. Therefore, based on federated learning, this paper proposes a privacy-preserving method based on secret sharing and homomorphic encryption, which can enhance the privacy protection of edge computing without affecting the accuracy of the model. At the same time, theoretical analysis proves that this method can resist collusion attacks and reasoning attacks.
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HaoDong Xie, YuanBo Guo, HaoRan Wang, QingLi Chen, Chen Fang, and Ning Zhu "Privacy-preserving method of edge computing based on secret sharing and homomorphic encryption", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 123030E (28 July 2022); https://doi.org/10.1117/12.2642617
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KEYWORDS
Instrument modeling
Data modeling
Computer security
Clouds
Data storage
Machine learning
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