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CryptoDL: deep neural networks over encrypted data. 2017. doi:10.48550\/arXiv.1711.05189."},{"key":"ref7","series-title":"2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)","first-page":"1199","article-title":"CryptoNN: training neural networks over encrypted data","author":"Xu","year":"2019"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.1109\/TDSC.2021.3074439","article-title":"NN-EMD: efficiently training neural networks using encrypted multi-sourced datasets","volume":"19","author":"Xu","year":"2022 Jul\u2013Aug 1","journal-title":"IEEE Trans Dependable Secure Comput"},{"key":"ref9","first-page":"20","article-title":"Consideration of data security and privacy using machine learning techniques","volume":"2","author":"Phan","year":"2023","journal-title":"Int J Data Inform Intell Comput"},{"key":"ref10","series-title":"Proceedings of the 24th Annual International Conference on the Theory and Applications of Cryptographic Techniques","first-page":"457","article-title":"Fuzzy identity-based encryption","author":"Sahai","year":"2005"},{"key":"ref11","series-title":"Proceedings of the 8th Theory of Cryptography Conference","first-page":"253","article-title":"Functional encryption: definitions and challenges","author":"Boneh","year":"2011"},{"key":"ref12","series-title":"Proceedings of the International Conference on the Theory and Application of Cryptology and Information Security","first-page":"98","article-title":"Registered (inner-product) functional encryption","author":"Francati","year":"2023"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1109\/TIFS.2023.3255171","article-title":"Privacy-preserving federated learning via functional encryption, revisited","volume":"18","author":"Chang","year":"2023","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"ref14","series-title":"Proceedings of the 41st Annual International Cryptology Conference","first-page":"208","article-title":"Multi-input quadratic functional encryption from pairings","author":"Agrawal","year":"2021"},{"key":"ref15","series-title":"Proceedings of the International Conference on the Theory and Application of Cryptology and Information Security","first-page":"467","article-title":"Inner-product functional encryption with fine-grained access control","author":"Abdalla","year":"2020"},{"key":"ref16","series-title":"Proceedings of the Annual International Cryptology Conference","first-page":"747","article-title":"Dynamic decentralized functional encryption","author":"Chotard","year":"2020"},{"key":"ref17","series-title":"Proceedings of the IACR International Conference on Public-Key Cryptography","first-page":"95","article-title":"A new paradigm for public-key functional encryption for degree-2 polynomials","author":"Gay","year":"2020"},{"key":"ref18","series-title":"Proceedings of the International Conference on Security and Cryptography for Networks","first-page":"544","article-title":"Function-hiding inner product encryption is practical","author":"Kim","year":"2018"},{"key":"ref19","series-title":"Proceedingsof the 29th Annual International Conference on the Theory and Applications of Cryptographic Techniques","first-page":"62","article-title":"Fully secure functional encryption: attribute-based encryption and (hierarchical) inner product encryption","author":"Lewko","year":"2010"},{"key":"ref20","series-title":"Proceedings of the 32nd Annual Cryptology Conference","first-page":"162","article-title":"Functional encryption with bounded collusions via multi-party computation","author":"Gorbunov","year":"2012"},{"key":"ref21","series-title":"Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security","first-page":"747","article-title":"5Gen-C: multi-input functional encryption and program obfuscation for arithmetic circuits","author":"Carmer","year":"2017"},{"key":"ref22","series-title":"Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security","first-page":"981","article-title":"5Gen: a framework for prototyping applications using multilinear maps and matrix branching programs","author":"Lewi","year":"2016"},{"key":"ref23","series-title":"Proceedings of the IACR International Workshop on Public Key Cryptography","first-page":"733","article-title":"Simple functional encryption schemes for inner products","author":"Abdalla","year":"2015"},{"key":"ref24","series-title":"Proceedings in Cryptology-CRYPTO 2018: 38th Annual International Cryptology Conference","first-page":"597","article-title":"Multi-input functional encryption for inner products: function-hiding realizations and constructions without pairings","author":"Abdalla","year":"2018"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"18951","DOI":"10.1109\/JIOT.2024.3349381","article-title":"Vulnerability of machine learning approaches applied in IoT-based smart grid: a review","volume":"11","author":"Zhang","year":"2024 Jun 1","journal-title":"IEEE Internet Things J"},{"key":"ref26","series-title":"Proceedings in Cryptology-CRYPTO 2018: 38th Annual International Cryptology Conference","first-page":"483","article-title":"Fast homomorphic evaluation of deep discretized neural networks","author":"Bourse","year":"2018"},{"key":"ref27","series-title":"Proceedings in Cryptology-ASIACRYPT 2016: 22nd International Conference on the Theory and Application of Cryptology and Information Security","first-page":"3","article-title":"Faster fully homomorphic encryption: bootstrapping in less than 0.1 seconds","author":"Chillotti","year":"2016"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"1704","DOI":"10.1109\/TCST.2020.3019501","article-title":"Secure state estimation using hybrid homomorphic encryption scheme","volume":"29","author":"Zhang","year":"2021 Jul","journal-title":"IEEE Trans Control Syst Technol"},{"key":"ref29","series-title":"Proceedings of the International Conference on Information Security and Cryptology","first-page":"1","article-title":"ML confidential: machine learning on encrypted data","author":"Graepel","year":"2012"},{"key":"ref30","unstructured":"Chou E, Beal J, Levy D, Yeung S, Haque A, Fei-Fei L. Faster cryptonets: leveraging sparsity for real-world encrypted inference. 2018. doi:10.48550\/arXiv.1811.09953."},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Ligier D, Carpov S, Fontaine C, Sirdey R. Privacy preserving data classification using inner-product functional encryption. In: Proceedings of the International Conference on Information Systems Security and Privacy; 2017. p. 423\u201330. doi:10.5220\/0006206704230430.","DOI":"10.5220\/0006206704230430"},{"key":"ref32","article-title":"Reading in the dark: classifying encrypted digits with functional encryption","author":"Dufour-Sans","year":"2018","journal-title":"Cryptology EPrint Archive"},{"key":"ref33","unstructured":"Ryffel T, Dufour-Sans E, Gay R, Bach F, Pointcheval D. Partially encrypted machine learning using functional encryption. 2019. doi:10.48550\/arXiv.1905.10214."},{"key":"ref34","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.comcom.2022.11.002","article-title":"Privacy-preserving spam filtering using homomorphic and functional encryption","volume":"197","author":"Nguyen","year":"2023","journal-title":"Comput Commun"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun","year":"1998","journal-title":"Proc IEEE"},{"key":"ref36","unstructured":"Xiao H, Rasul K, Vollgraf R. Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. 2017. doi:10.48550\/arXiv.1708.07747."},{"key":"ref37","unstructured":"Krizhevsky A, Hinton G. Learning multiple layers of features from tiny images [Ph.D. dissertation]. Canada: University of Toronto; 2009."}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-82-3\/TSP_CMC_59718\/TSP_CMC_59718.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:28:43Z","timestamp":1763101723000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v82n3\/59907"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":37,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.059718","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]}}}