Online-Offline Homomorphic Signatures for Polynomial Functions

The advent of cloud computing has given rise to a plethora of work on verifiable delegation of computation. Homomorphic signatures are powerful tools that can be tailored for verifiable computation, as long as they are efficiently verifiable. The main advantages of homomorphic signatures for verifiable computation are twofold: \begin{inparaenum}[(i)] \item Any third party can verify the correctness of the delegated computation, \item and this third party is not required to have access to the dataset on which the computation was performed. \end{inparaenum} In this paper, we design a homomorphic signature suitable for multivariate polynomials of bounded degree, which draws upon the algebraic properties of \emph{eigenvectors} and \emph{leveled multilinear maps}. The proposed signature yields an efficient verification process (in an amortized sense) and supports online-offline signing. Furthermore, our signature is provably secure and its size grows only linearly with the degree of the evaluated polynomial

Homomorphic Signatures: Implementation and Performance Evaluation

Homomorphic signatures allow users to outsource computation on their data while ensuring the integrity of the results, and to prove certain facts about official documents to third parties without sharing those documents. The signature scheme is capable of efficiently calculating several data analytical functions, including the average and standard deviation, on signed data and produce a signature for the result. We present a fully functional implementation of the homomorphic signature scheme for polynomial functions by Boneh and Freeman (2011). We give a performance evaluation of our implementation, and measure the effects of two major performance improvements

Fully leakage-resilient signatures revisited: Graceful degradation, noisy leakage, and construction in the bounded-retrieval model

We construct new leakage-resilient signature schemes. Our schemes remain unforgeable against an adversary leaking arbitrary (yet bounded) information on the entire state of the signer (sometimes known as fully leakage resilience), including the random coin tosses of the signing algorithm. The main feature of our constructions is that they offer a graceful degradation of security in situations where standard existential unforgeability is impossible

Ring Learning With Errors: A crossroads between postquantum cryptography, machine learning and number theory

The present survey reports on the state of the art of the different cryptographic functionalities built upon the ring learning with errors problem and its interplay with several classical problems in algebraic number theory. The survey is based to a certain extent on an invited course given by the author at the Basque Center for Applied Mathematics in September 2018.Comment: arXiv admin note: text overlap with arXiv:1508.01375 by other authors/ comment of the author: quotation has been added to Theorem 5.