Applying Homomoprhic Encryption to Data Spaces Takashi Michikata.

2023 IEEE International Conference on Big Data (BigData)(2023)

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摘要
Many applications utilizing big data are being used every day, and the importance of data utilization is increasing day by day. Data spaces, a federated data management system, is gaining increasing attention in Europe and Japan. To promote data spaces into real applications and increase data exchange between companies and individuals, the data exchanged over data spaces must be well protected. To achieve that goal, we propose to apply homomorphic encryption scheme to data spaces, propose its architecture, and analyze its advantages. Furthermore, we also investigate the feasibility of the proposed architecture based on results of calculation of GHG emission of a self-driving electric vehicle in the real-world experiment.
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关键词
data spaces,bigdata,GHG emission,homomorphic encryption
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