Results 21 to 30 of about 1,675 (182)

Deep Neural Networks for Encrypted Inference with TFHE [PDF]

, 2023
Fully homomorphic encryption (FHE) is an encryption method that allows to perform computation on encrypted data, without decryption. FHE preserves the privacy of the users of online services that handle sensitive data, such as health data, biometrics, credit scores and other personal information.
Andrei Stoian, Jordan Fréry, Roman Bredehoft, Luis Montero, Celia Kherfallah, Benoît Chevallier-Mames   +5 more
openaire   +4 more sources

Non-Interactive Decision Trees and Applications with Multi-Bit TFHE

Algorithms, 2022
Machine learning classification algorithms, such as decision trees and random forests, are commonly used in many applications. Clients who want to classify their data send them to a server that performs their inference using a trained model.
Jestine Paul, Benjamin Hong Meng Tan, Bharadwaj Veeravalli, Khin Mi Mi Aung   +3 more
doaj   +2 more sources

Improved homomorphic evaluation for hash function based on TFHE

Cybersecurity
Homomorphic evaluation of hash functions offers a solution to the challenge of data integrity authentication in the context of homomorphic encryption. The earliest attempt to achieve homomorphic evaluation of SHA-256 hash function was proposed by Mella ...
Benqiang Wei, Xianhui Lu
doaj   +2 more sources

YATA: Yet Another TFHE Accelerator with Key Compression and Radix-8 NTT

Transactions on Cryptographic Hardware and Embedded Systems
This paper introduces a silicon-proven ASIC accelerator, YATA, specifically designed for TFHE’s most demanding operation, the BlindRotate. The architecture tackles the main bottleneck in TFHE—massive memory bandwidth—by applying Key Compression to ...
Kotaro Matsuoka, Takashi Sato
doaj   +2 more sources

Improved FHE Bootstrapping and Its Applications in Discretized Neural Networks

IET Information Security
The inefficiency of bootstrapping is the primary bottleneck preventing fully homomorphic encryption (FHE) from practical applications. One of the main obstacles to improving the bootstrapping performance using hardware acceleration is the large storage ...
Kaixing Wang, Binwu Xiang, Jiang Zhang, Yi Deng, Dengguo Feng   +4 more
doaj   +2 more sources

Further Improvements in AES Execution over TFHE [PDF]

IACR Communications in Cryptology
Making the most of TFHE advanced capabilities such as programmable or circuit bootstrapping and their generalizations for manipulating data larger than the native plaintext domain of the scheme is a very active line of research. In this context, AES is a particularly interesting benchmark, as an example of a nontrivial algorithm which has eluded ...
Sonia Belaïd, Nicolas Bon, Aymen Boudguiga, Renaud Sirdey, Daphné Trama, Nicolas Ye   +5 more
openaire   +2 more sources

OFHE: An Electro-Optical Accelerator for Discretized TFHE

Proceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design
This paper presents \textit{OFHE}, an electro-optical accelerator designed to process Discretized TFHE (DTFHE) operations, which encrypt multi-bit messages and support homomorphic multiplications, lookup table operations and full-domain functional bootstrappings.
Mengxin Zheng, Cheng Chu, Qian Lou, Nathan Youngblood, Mo Li, Sajjad Moazeni, Lei Jiang 0001   +6 more
openaire   +3 more sources

SMOOTHIE: (Multi-)Scalar Multiplication Optimizations On TFHE. [PDF]

IACR Cryptol. ePrint Arch.
The (Multi-)Scalar multiplication is a crucial operation during FHE-related AI applications, and its performance has a significant impact on the overall efficiency of these applications. In this paper we introduce SMOOTHIE: (Multi-)Scalar Multiplication Optimizations On TFHE, introducing new techniques to improve the performance of single- and multi ...
Pottier, Xander, D'Anvers, Jan-Pieter, de Ruijter, Thomas, Verbauwhede, Ingrid   +3 more
openaire   +3 more sources

Practical TFHE Ciphertext Sanitization for Oblivious Circuit Evaluation [PDF]

Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security
Homomorphic encryption (FHE) enables the computation of arbitrary circuits over encrypted data. A widespread application of HE is oblivious circuit evaluation, where a sender evaluates its private circuit over a receiver\u27s encrypted data, covering ...
Intak Hwang, Seonhong Min, Jinyeong Seo, Yongsoo Song   +3 more
openaire   +2 more sources

Fat mass and obesity-associated protein regulates arecoline-exposed oral cancer immune response through programmed cell death-ligand 1. [PDF]

Cancer Sci, 2022
PD‐L1 expression is upregulated in arecoline‐exposed OSCC cell lines and tissues and is associated with areca nut exposure. FTO promotes the stability and expression levels of PD‐L1 transcripts through modulating m6A modification and MYC, respectively.
Li X, Chen W, Gao Y, Song J, Gu Y, Zhang J, Cheng X, Ai Y.   +7 more
europepmc   +2 more sources