Homomorphic encryption (HE) is a very powerful tool that allows to compute on encrypted data. In particular, HE enables to securely outsource data computation to the cloud. However, HE by itself offers no guarantee that the returned result was …
The widespread application of machine learning algorithms is a matter of increasing concern for the data privacy research community, and many have sought to develop privacy-preserving techniques for it. Among existing approaches, the homomorphic …
Homomorphic encryption is one of the most secure solutions for processing sensitive information in untrusted environments, and there have been many recent advances towards its efficient implementation for the evaluation of linear functions and …
In this work, we describe our efforts to resume the investigation by [BVA18] on the possible advantages of replacing the NTT with the DGT for the implementation of polynomial multiplication in FHE cryptosystems. In particular, we target results …
MitID is the new eID system in Denmark. It provides access to a large quantity of online services, including online banking, insurances, taxes and health-information. In this paper, we analyze the security of the new system from the perspective of …
We study masking countermeasures for side-channel attacks against signature schemes constructed from the MPC-in-the-head paradigm, specifically when the MPC protocol uses preprocessing. This class of signature schemes includes Picnic, an alternate …
We present multiple contributions to the efficient software implementation of cryptographic algorithms for ARM devices. The talk has three parts: (i) LS-designs (represented by Fantomas), their efficient implementation and side-channel security; (ii) …
Since Fully Homomorphic Encryption (FHE) is still unpractical, one alternative to guarantee privacy while outsourcing data processing to the cloud is to develop homomorphic versions of algorithms to be executed over encrypted data using a leveled or …