A5019332272- Cryptography and Data Security
- Cryptographic Implementations and Security
- Cryptography and Residue Arithmetic
- Advanced Memory and Neural Computing
- Industrial Vision Systems and Defect Detection
- Advanced Neural Network Applications
- Privacy-Preserving Technologies in Data
KU Leuven
2023
The Multi-Scalar Multiplication (MSM) is the main barrier to accelerating Zero-Knowledge applications. In recent years, hardware acceleration of this algorithm on both FPGA and GPU has become a popular research topic subject multi-million dollar prize competition (ZPrize). This work presents OPTIMSM: Optimized Processing Through Iterative Multiplication. novel accelerator focuses MSM for any Elliptic Curve (EC) by improving upon Pippenger algorithm. A new iteration technique introduced...
Homomorphic encryption (HE) enables calculating on encrypted data, which makes it possible to perform privacy-preserving neural network inference. One disadvantage of this technique is that several orders magnitudes slower than calculation unencrypted data. Neural networks are commonly trained using floating-point, while most homomorphic libraries calculate integers, thus requiring a quantisation the network. A straightforward approach would be quantise large integer sizes (e.g. 32 bit)...
Homomorphic encryption (HE) enables calculating on encrypted data, which makes it possible to perform privacypreserving neural network inference. One disadvantage of this technique is that several orders magnitudes slower than calculation unencrypted data. Neural networks are commonly trained using floating-point, while most homomorphic libraries calculate integers, thus requiring a quantisation the network. A straightforward approach would be quantise large integer sizes (e.g. 32 bit) avoid...