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Secure Fully Homomorphic Authenticated Encryption
IEEE Access, 2021 Homomorphic authenticated encryption allows implicit computation on plaintexts using corresponding ciphertexts without losing privacy, and provides authenticity of the computation and the resultant plaintext of the computation when performing a ...
Jeongsu Kim, Aaram Yun
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Combinatorially Homomorphic Encryption [PDF]
, 2023 Homomorphic encryption enables public computation over encrypted data. In the past few decades, homomorphic encryption has become a staple of both the theory and practice of cryptography. Nevertheless, while there is a general loose understanding of what
Yuval Ishai +2 more
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Survey on Application of Homomorphic Encryption in Deep Learning [PDF]
Jisuanji kexue yu tansuoWith the widespread application of deep learning in various fields, data privacy and security issues have become increasingly important. Homomorphic encryption, a technique that allows computations to be performed directly on encrypted data, offers a ...
YANG Hongchao, YI Mengjun, LI Peijia, ZHANG Hanwen, SHEN Furao, ZHAO Jian, WANG Liuwang
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Lattices, Homomorphic Encryption, and CKKS [PDF]
CoRR, 2022 One should note that CKKS has been proven to have some vulnerabilities due to an attack from Micciancio and Li. In particular, CKKS does not satisfy the security definition which they propose for for approximate encryption schemes (CKKS is one such approximate encryption scheme)
Pathak, Vir
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HOMOMORPHIC ENCRYPTION: CLOUD COMPUTING SECURITY AND OTHER APPLICATIONS (A SURVEY)
Informatika, 2016 Homomorphic encryption is a form of encryption which allows specific types of computations to be carried out on cipher text and to obtain an encrypted result which matches the result of operations performed on the plain text. The article presents a basic
A. I. Trubei
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Leveled homomorphic encryption schemes for homomorphic encryption standard [PDF]
Journal of Mathematical CryptologyAbstract Homomorphic encryption allows for computations on encrypted data without exposing the underlying plaintext, enabling secure and private data processing in various applications such as cloud computing and machine learning. This article presents a comprehensive mathematical foundation for three prominent homomorphic encryption ...
Shuhong Gao, Kyle Yates
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Privacy Preserving Machine Learning With Homomorphic Encryption and Federated Learning
Future Internet, 2021 Privacy protection has been an important concern with the great success of machine learning. In this paper, it proposes a multi-party privacy preserving machine learning framework, named PFMLP, based on partially homomorphic encryption and federated ...
Quan Qian
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Building Applications with Homomorphic Encryption
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018 In 2009, Craig Gentry introduced the first "fully" homomorphic encryption scheme allowing arbitrary circuits to be evaluated on encrypted data. Homomorphic encryption is a very powerful cryptographic primitive, though it has often been viewed by practitioners as too inefficient for practical applications.
Roger A. Hallman +6 more
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Privacy and correctness trade-offs for information-theoretically secure quantum homomorphic encryption [PDF]
Quantum, 2023 Quantum homomorphic encryption, which allows computation by a server directly on encrypted data, is a fundamental primitive out of which more complex quantum cryptography protocols can be built.
Yanglin Hu +2 more
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Potential of Homomorphic Encryption for Cloud Computing Use Cases in Manufacturing
Journal of Cybersecurity and Privacy, 2023 Homomorphic encryption enables secure cloud computing over the complete data lifecycle. As so-called in-use encryption methodology, it allows using encrypted data for, e.g., data analysis—in contrast to classic encryption methods.
Raphael Kiesel +5 more
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