A5057594551- Cryptography and Data Security
- Privacy-Preserving Technologies in Data
- Chaos-based Image/Signal Encryption
- Internet Traffic Analysis and Secure E-voting
- Cryptographic Implementations and Security
- Cryptography and Residue Arithmetic
- BIM and Construction Integration
- Cloud Data Security Solutions
- Coding theory and cryptography
- Security and Verification in Computing
- Numerical Methods and Algorithms
- Digital Filter Design and Implementation
Zone Atelier Moselle
2021-2023
Zama (France)
2021
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
2017
CEA LIST
2017
Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance
2017
Université de Bretagne Occidentale
2017
IMT Atlantique
2017
Centre National de la Recherche Scientifique
2017
Floating-point arithmetic plays a central role in computer science and is used various domains where precision computational scale are essential. One notable application machine learning, Fully Homomorphic Encryption (FHE) can play crucial safeguarding user privacy. In this paper, we focus on TFHE develop novel homomorphic operators designed to enable the construction of precise adaptable floating-point operations. Integrating within context FHE particularly challenging due constraints such...
Abstract Classification algorithms/tools become more and powerful pervasive. Yet, for some use cases, it is necessary to be able protect data privacy while benefiting from the functionalities they provide. Among tools that may used ensure such privacy, we are focusing in this paper on functional encryption . These relatively new cryptographic primitives enable evaluation of functions over encrypted inputs, outputting cleartext results. Theoretically, property makes them well-suited process...
In this work, we study the practical security of inner-product functional encryption. We left behind mathematical proof schemes, provided in literature, and focus on what attackers can use realistic scenarios without tricking protocol, how they retrieve more than should be able to. This is based proposed protocol from [1]. generalize scenario to an attacker possessing n secret keys. propose attacks machine learning, experiment them over MNIST dataset [2].
Fully Homomorphic Encryption has known impressive improvements in the last 15 years, going from a technology long thought to be impossible an existing family of encryption schemes able solve plethora practical use cases related privacy sensitive information. Recent results mainly focus on improving techniques within traditionally defined framework GLWE-based schemes, but recent CPU implementation are incremental. To keep this technology, one solution is modify aforementioned framework, by...