Results 11 to 20 of about 390 (116)

GPU Acceleration for FHEW/TFHE Bootstrapping [PDF]

Transactions on Cryptographic Hardware and Embedded Systems
Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data without decryption. Despite its great theoretical potential, the computational overhead remains a major obstacle for practical applications.
Yu Xiao, Feng-Hao Liu, Yu-Te Ku, Ming-Chien Ho, Chih-Fan Hsu, Ming-Ching Chang, Shih-Hao Hung, Wei-Chao Chen   +7 more
doaj   +3 more sources

VeloFHE: GPU Acceleration for FHEW and TFHE Bootstrapping [PDF]

Transactions on Cryptographic Hardware and Embedded Systems
Bit-wise Fully Homomorphic Encryption schemes like FHEW and TFHE offer efficient functional bootstrapping, enabling concurrent function evaluation and noise reduction.
Shiyu Shen, Hao Yang, Zhe Liu, Ying Liu, Xianhui Lu, Wangchen Dai, Lu Zhou, Yunlei Zhao, Ray C. C. Cheung   +8 more
doaj   +3 more sources

Improved Circuit Synthesis with Multi-Value Bootstrapping for FHEW-like Schemes [PDF]

Transactions on Cryptographic Hardware and Embedded Systems
In recent years, the research community has made great progress in improving techniques for privacy-preserving computation, such as fully homomorphic encryption (FHE).
Johannes Mono, Kamil Kluczniak, Tim Güneysu   +2 more
doaj   +5 more sources

Ring packing and amortized FHEW bootstrapping. [PDF]

IACR Cryptol. ePrint Arch., 2018
The FHEW fully homomorphic encryption scheme (Ducas and Micciancio, Eurocrypt 2015) offers very fast homomorphic NAND-gate computations (on encrypted data) and a relatively fast refreshing procedure that allows to homomorphically evaluate arbitrary NAND ...
Daniele Micciancio, Jessica Sorrell
openaire   +3 more sources

Large-Precision Homomorphic Sign Evaluation Using FHEW/TFHE Bootstrapping [PDF]

, 2022
A comparison of two encrypted numbers is an important operation needed in many machine learning applications, for example, decision tree or neural network inference/training.
Zeyu Liu 0008, Daniele Micciancio, Yuriy Polyakov   +2 more
core   +5 more sources

On Side-Channel and CVO Attacks against TFHE and FHEW. [PDF]

IACR Cryptol. ePrint Arch., 2022
The recent work of Chaturvedi et al. (ePrint 2022/685) claims to observe leakage about secret information in a ciphertext of TFHE through a timing side-channel on the (untrusted) server.
Michael Walter
core   +3 more sources

Faster FHEW Bootstrapping with Adaptive Key Update [PDF]

Lee et al. proposed a new bootstrapping algorithm based on homomorphic automorphism, which merges the empty sets of ciphertexts by adjusting the window size.
Qi Zhang, Mingqiang Wang, Xiaopeng Cheng
core   +5 more sources

Demystifying the comments made on "A Practical Full Key Recovery Attack on TFHE and FHEW by Inducing Decryption Errors". [PDF]

IACR Cryptol. ePrint Arch., 2022
Fully Homomorphic Encryption (FHE) allows computations on encrypted data without the need for decryption. Therefore, in the world of cloud computing, FHE provides an essential means for users to garner different computational services from potentially ...
Bhuvnesh Chaturvedi, Anirban Chakraborty 0003, Ayantika Chatterjee, Debdeep Mukhopadhyay   +3 more
core   +3 more sources

A New Fine Tuning Method for FHEW/TFHE Bootstrapping with IND-CPAD Security. [PDF]

IACR Cryptol. ePrint Arch.
Fully homomorphic encryption (FHE) schemes enable computation on encrypted data, making them a crucial component of privacy-enhancing technologies.
Deokhwa Hong, Young-Sik Kim, Yongwoo Lee, Eunyoung Seo   +3 more
core   +3 more sources

Optimizing FHEW-Like Homomorphic Encryption Schemes with Smooth Performance-Failure Trade-Offs. [PDF]

IACR Cryptol. ePrint Arch.
FHEW-like homomorphic encryption (HE) schemes, introduced by Ducas and Micciancio (Eurocrypt 2015), represent the most efficient family of HE schemes in terms of both latency and key size.
Deokhwa Hong, Yongwoo Lee
core   +3 more sources