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Survey on Fully Homomorphic Encryption, Theory, and Applications.pdf (5.214Mb)
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Title
Survey on Fully Homomorphic Encryption, Theory, and Applications
Author
Manzano Castro, MarcMondragon Unibertsitatea
Author (from another institution)
Marcolla, Chiara
Sucasas, Victor
Bassoli, Riccardo
Fitzek, Frank H. P.
Aaraj, Najwa
Research Group
Análisis de datos y ciberseguridad
Published Date
2022
Publisher
IEEE
Keywords
Homomorphic encryption
neural networks
Cloud computing
Public key ... [+]
Homomorphic encryption
neural networks
Cloud computing
Public key
Gaussian distribution
Privacy
Internet of Things [-]
Abstract
Data privacy concerns are increasing significantly in the context of the Internet of Things, cloud services, edge computing, artificial intelligence applications, and other applications enabled by nex ... [+]
Data privacy concerns are increasing significantly in the context of the Internet of Things, cloud services, edge computing, artificial intelligence applications, and other applications enabled by next-generation networks. Homomorphic encryption addresses privacy challenges by enabling multiple operations to be performed on encrypted messages without decryption. This article comprehensively addresses homomorphic encryption from both theoretical and practical perspectives. This article delves into the mathematical foundations required to understand fully homomorphic encryption ( FHE ). It consequently covers design fundamentals and security properties of FHE and describes the main FHE schemes based on various mathematical problems. On a more practical level, this article presents a view on privacy-preserving machine learning using homomorphic encryption and then surveys FHE at length from an engineering angle, covering the potential application of FHE in fog computing and cloud computing services. It also provides a comprehensive analysis of existing state-of-the-art FHE libraries and tools, implemented in software and hardware, and the performance thereof. [-]
URI
https://hdl.handle.net/20.500.11984/5972
Publisher’s version
https://doi.org/10.1109/JPROC.2022.3205665
ISSN
1558-2256
Published at
Proceedings of the IEEE  Vol. 110. N. 10. Pp. 1572-1609. October, 2022
Document type
Article
Version
Postprint – Accepted Manuscript
Rights
© 2022 IEEE
Access
Embargoed Access (until 2024-10-31)
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  • Articles - Engineering [478]

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