Results 181 to 190 of about 18,513 (227)

Circuit-Private Multi-key FHE

2017
Multi-key fully homomorphic encryption MFHE schemes allow polynomially many users without trusted setup assumptions to send their data encrypted under different FHE keys chosen by users independently of each other to an honest-but-curious server that can compute the output of an arbitrary polynomial-time computable function on this joint data and issue
Wutichai Chongchitmate, Rafail Ostrovsky
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Occurrence download FHE

2023
ALA occurrence record ...
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Faster Bootstrapping of FHE over the Integers

2020
In FHE over the integers, decryption function is simplified by sparse subset subset sum problem (SSSP) assumption, which is introduced by Dijk et al. (Eurocrypt 2010), so that bootstrapping can be achieved successfully. Later, Nuida and Kurowasa (Eurocrypt 2015) proposed an advanced method of which the degree is very low and the message space is non ...
Jung Hee Cheon, Kyoohyung Han, Duhyeong Kim   +2 more
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An Efficient Leveled Identity-Based FHE

2015
Gentry, Sahai and Waters constructed the first identity-based fully homomorphic encryption schemes from identity-based encryption schemes in CRYPTO 2013. In this work, we focus on improving their IBFHE schemes, using Micciancio and Peikert’s novel and powerful trapdoor in conjunction with Alperin-Sheriff and Peikert’s simple and tight noise analysis ...
Fuqun Wang, Kunpeng Wang 0001, Bao Li 0001   +2 more
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Leveled FHE with Matrix Message Space

2018
Up to now, almost all fully homomorphic encryption (FHE) schemes can only encrypt bit or vector. In PKC 2015, Hiromasa et al. [12] constructed the only leveled FHE scheme that encrypts matrices and supports homomorphic matrix addition and multiplication.
Biao Wang, Xueqing Wang, Rui Xue 0001
openaire   +2 more sources

HMC-FHE: A Heterogeneous Near Data Processing Framework for Homomorphic Encryption

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Fully homomorphic encryption (FHE) offers a promising solution to ensure data privacy by enabling computations directly on encrypted data. However, its notorious performance degradation severely limits the practical application, due to the explosion of ...
Zehao Chen, Zhining Cao, Zhaoyan Shen, Lei Ju   +3 more
semanticscholar   +1 more source

Doing Real Work with FHE

Proceedings of the 6th Workshop on Encrypted Computing & Applied Homomorphic Cryptography - WAHC '18, 2018
We describe our recent experience, building a system that uses fully-homomorphic encryption (FHE) to approximate the coefficients of a logistic-regression model, built from genomic data. The aim of this project was to examine the feasibility of a solution that operates "deep within the bootstrapping regime,'' solving a problem that appears too hard to ...
Jack L. H. Crawford, Craig Gentry, Shai Halevi, Daniel Platt, Victor Shoup   +4 more
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A Haskell to FHE Transpiler With Circuit Parallelisation

Proceedings of the 13th Workshop on Encrypted Computing & Applied Homomorphic Computing
Fully Homomorphic Encryption (FHE) enables the evaluation of programs directly on encrypted data. However, because only basic operations can be performed on ciphertexts, programs must be expressed as boolean or arithmetic circuits. This low-level representation makes implementing applications for FHE significantly more cumbersome than writing code in a
Anne Müller, Mohd Kashif, Nico Döttling   +2 more
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PPGNN: Fast and Accurate Privacy-Preserving Graph Neural Network Inference via Parallel and Pipelined Arithmetic-and-Logic FHE Accelerator

Design Automation Conference
Graph Neural Networks (GNNs) are increasingly used in fields like social media and bioinformatics, promoting the prosperity of cloud-based GNN inference services.
Yun-Tao Wei, Xue-Yan Wang, Song Bian, Yi-Cheng Huang, Wei-Sheng Zhao, Yi-Er Jin   +5 more
semanticscholar   +1 more source

FHEDA: Efficient Circuit Synthesis with Reduced Bootstrapping for Torus FHE

European Symposium on Security and Privacy
Fully Homomorphic Encryption (FHE) schemes are widely used cryptographic primitives for performing arbitrary computations on encrypted data. However, FHE incorporates a computationally intensive mechanism called bootstrapping, that resets the noise in ...
Animesh Singh, Smita Das, Anirban Chakraborty, Rajat Sadhukhan, Ayantika Chatterjee, Debdeep Mukhopadhyay   +5 more
semanticscholar   +1 more source