Results 81 to 90 of about 1,675 (182)

Neural Network Training on Encrypted Data with TFHE

CoRR
We present an approach to outsourcing of training neural networks while preserving data confidentiality from malicious parties. We use fully homomorphic encryption to build a unified training approach that works on encrypted data and learns quantized neural network models.
Luis Montero, Jordan Fréry, Celia Kherfallah, Roman Bredehoft, Andrei Stoian   +4 more
openaire   +2 more sources

A Fast Heuristic for Mapping Boolean Circuits to Functional Bootstrapping

Transactions on Cryptographic Hardware and Embedded Systems
Functional bootstrapping in FHE schemes such as FHEW and TFHE allows the evaluation of arbitrary functions on encrypted data, while simultaneously reducing noise.
Sergiu Carpov
doaj   +1 more source

Homomorphic Field Trace Revisited : Breaking the Cubic Noise Barrier

Transactions on Cryptographic Hardware and Embedded Systems
We present a novel homomorphic trace evaluation algorithm RevHomTrace, which mitigates the phase amplification problem that comes with the definition of the field trace.
Kang Hoon Lee, Ji Won Yoon
doaj   +1 more source

Oblivious network intrusion detection systems. [PDF]

Sci Rep, 2023
Sayed MA, Taha M.
europepmc   +1 more source

Putting up the swiss army knife of homomorphic calculations by means of TFHE functional bootstrapping [PDF]

, 2022
In this work, we first propose a new functional bootstrapping with TFHE for evaluating any function of domain and codomain the real torus T by using a small number of bootstrappings. This result improves some aspects of previous approaches: like them, we
Martin Zuber, Aymen Boudguiga, Cédric Gouy-Pailler, Pierre-Emmanuel Clet, Renaud Sirdey   +4 more
core  

Evaluating Homomorphic Encryption Schemes for Privacy and Security in Healthcare Data Management

Journal of Cybersecurity and Privacy
Ensuring data privacy and security in sensitive domains such as healthcare remains a critical challenge. Homomorphic Encryption (HE) offers a promising approach by enabling computations directly on encrypted data, but the diversity of available schemes ...
Henrique Jorge, Cristina Wanzeller, João Henriques   +2 more
doaj   +1 more source

Adaptive Autonomous Protocol for Secured Remote Healthcare Using Fully Homomorphic Encryption (AutoPro-RHC). [PDF]

Sensors (Basel), 2023
Sheu RK, Lin YC, Pardeshi MS, Huang CY, Pai KC, Chen LC, Huang CC.   +6 more
europepmc   +1 more source

Don’t be mean: Reducing Approximation Noise in TFHE through Mean Compensation

Transactions on Cryptographic Hardware and Embedded Systems
Fully Homomorphic Encryption (FHE) allows computations on encrypted data without revealing any information about the data itself. However, FHE ciphertexts include noise for security reasons, which increases during operations and can lead to decryption ...
Thomas de Ruijter, Jan-Pieter D’Anvers, Ingrid Verbauwhede   +2 more
doaj   +1 more source

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics. [PDF]

Sensors (Basel), 2023
Yang W, Wang S, Cui H, Tang Z, Li Y.
europepmc   +1 more source

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

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   +1 more source