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crossref
Tikaram Sanyashi, Darshil Desai, Bernard Menezes
2019-08-14T12:52:56Z
置信度 0.70
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How to simultaneously guarantee data processing and data hiding has become a topical issue because of the increasing needs for enhancing privacy protection. Homomorphic encryption is a privacy computing technology that can satisfy the above requirements and st…
crossref
Junfei Wu
2022-09-17T11:54:39Z
置信度 0.70
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Nowadays security and authentication of user’s data is a major concern over cloud environment. Unauthorized users try to attack outsourced data over the cloud. Different researchers proposed various algorithms based upon data security. Authentication technique…
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Deepika Bhatia, Meenu Dave
2019-09-18T07:30:53Z
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Ninghui Li
2009-09-16T08:23:52Z
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2024-02-29T05:31:11Z
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crossref
Berry Schoenmakers
2011-10-27T09:51:00Z
置信度 0.70
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In this paper, we construct a new noiseless homomorphic encryption scheme based on the hardness of AGCD problem. We give a succinct and efficient algorithm that produces necessary secret keys for homomorphic evaluation of higher degree polynomial circuits. We …
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Jonghee Chun, Hee Han, Stefano V. Kang, Hyo Keun Wang
2024-10-09T07:17:40Z
置信度 0.70
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Artificial intelligence-based medical diagnostics is of great concern when it comes to data privacy, such as medical imaging. We propose to use symmetric (AES), asymmetric (RSA), and homomorphic encryption (HE) to create a secure AI diagnostic pipeline where t…
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Keerthana G V, Usha N, Roopa Y, Nayan M M
2025-09-01T13:26:47Z
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Mehdi Sadi
2021-04-30T15:15:27Z
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Exploration de l'apprentissage automatique avec le chiffrement homomorphe dans l'internet des objets/Cloud L'apprentissage automatique en tant que service (MLaaS) a accéléré l'adoption des techniques d'apprentissage automatique dans divers domaines. Toutefois,…
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2026-04-08T13:38:41Z
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2022-01-03T18:02:43Z
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2016-03-01T21:08:00Z
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2020-03-26T15:12:11Z
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Chris Gilbert, Mercy Abiola Gilbert
2024-11-27T05:59:09Z
置信度 0.70
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Homomorphic encryption (HE) is one technique that enables privacy-preserving computation. Operations (or circuit evaluations) are performed directly on homomorphically encrypted data. The result can then be decrypted. Since its introduction 46 years ago, homom…
crossref
2026-04-29T09:32:50Z
置信度 0.70
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Contributions à la confidentialité des données en apprentissage machine par chiffrement homomorphe L’objectif de mes travaux tout au long de cette thèse a été de permettre à des algorithmes complexes d’apprentissage machine de pouvoir être appliqués (lors de l…
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Martin Zuber
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Unnimaya M U, Dr. Shibily Joseph
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Nawal Almutairi, Frans Coenen, Keith Dures
2018-09-27T07:15:07Z
置信度 0.70
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This dissertation focuses on the new techniques for secure and private computation for signal processing and machine learning. Specifically, the thesis will focuses on extending Fully Homomorphic Encryption (FHE) technique in a cloud computing set up by runnin…
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Thomas M. Shortell, Ali Shokoufandeh
2021-07-16T02:22:51Z
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Nawal Almutairi, Frans Coenen, Keith Dures
2026-03-20T12:02:46Z
置信度 0.70
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Shashwat Shah
2024-11-13T11:58:34Z
置信度 0.70
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Data security has always been a concern for digital users. In general, cloud Service Providers (CSPs) provide security to data during communication, storage, etc., using various cryptographic techniques. But still, data security during computation remains a ch…
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Ramkumar Ramachandran Ketti, Sonam Mittal
2022-03-01T22:07:25Z
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Bastiaan Quast
2024-06-13T06:34:46Z
置信度 0.70
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This paper addresses the challenges of data privacy and computational efficiency in artificial intelligence (AI) models by proposing a novel hybrid model that combines homomorphic encryption (HE) with AI to enhance security while maintaining learning accuracy.…
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Quoc Bao Phan, Tuy Tan Nguyen
2024-09-24T12:52:44Z
置信度 0.70
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Prem Kumar P
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Anjali Kadao, Sonali Mondal
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2024-08-06T12:41:09Z
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Aymen Boudguiga, Oana Stan, Abdessamad Fazzat, Houda Labiod 等
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2022-01-03T18:02:43Z
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crossref
Alexander Viand, Hossein Shafagh
2018-10-16T12:56:36Z
置信度 0.70
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In today's internet world the use of Machine Learning as A Service (MLaaS) is increasing day by day especially automated Machine Learning. In which users upload their dataset and auto Machine Learning (ML) will develop models after studying dataset. Due to thi…
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Harsh J. Kiratsata, Mahesh Panchal
2021-05-25T23:19:52Z
置信度 0.70
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crossref
Guangli Xiang, Can Shao
2021-10-16T04:00:24Z
置信度 0.70
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Homomorphic encryption allows servers to perform privacy-preserving inference on encrypted data, enabling machine learning services while protecting user privacy. Most existing research focuses on reducing the computational overhead of private inference on the…
crossref
Yufei Zhou, Lihao Pan
2026-02-02T13:52:08Z
置信度 0.70
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We propose an identity-based fully homomorphic encryption (IBFHE) schemebased on the Module Learning with Errors (Module-LWE) assumption. Theconstruction merges the GSW fully homomorphic encryption frameworkwhich operates without evaluation keyswith compact ap…
crossref
Shan Ma, YiChen Li, ChunYu Qiu
2026-03-03T23:43:58Z
置信度 0.70
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The traditional definition of fully homomorphic encryption (FHE) is not composable, i.e., it does not guarantee that evaluating two (or more) homomorphic computations in a sequence produces correct results. We formally define and investigate a stronger notion …
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Daniele Micciancio
2025-04-08T17:23:17Z
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Yaissa Campos Siqueira
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With the increased incorporation of digital technology, the emerging challenges in ensuring that the rights of private legal documents are adequately protected concerning confidentiality and integrity have come to light. This study proposes a new framework tha…
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H.M. Thulana Thidaswin, Danishka Navin
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Aashka Raval, Jaivik Jariwala, Vrundan Sojitra, Nishant Doshi
2025-03-11T16:44:21Z
置信度 0.70
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With the tremendous growth of technology, providing data security to critical applications such as smart grid, health care, and military is indispensable. On the other hand, due to the proliferation of external data threats in these applications, the loss incu…
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2012-07-23T11:12:29Z
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2025-07-02T03:46:40Z
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