Authors:
Jean-Guillaume Dumas
1
;
Pascal Lafourcade
2
;
Jean-Baptiste Orfila
1
and
Maxime Puys
1
Affiliations:
1
Université Grenoble Alpes, France
;
2
University Clermont Auvergne, France
Keyword(s):
Secure Multiparty Computation (MPC), Distributed Matrix Multiplication, Trust Evaluation, Proverif.
Related
Ontology
Subjects/Areas/Topics:
Data and Application Security and Privacy
;
Formal Methods for Security
;
Information and Systems Security
;
Privacy
;
Security Protocols
;
Trust Management and Reputation Systems
Abstract:
This paper deals with distributed matrix multiplication. Each player owns only one row of both matrices and
wishes to learn about one distinct row of the product matrix, without revealing its input to the other players.
We first improve on a weighted average protocol, in order to securely compute a dot-product with a
quadratic volume of communications and linear number of rounds. We also propose a protocol with five communication
rounds, using a Paillier-like underlying homomorphic public key cryptosystem, which is secure in
the semi-honest model or secure with high probability in the malicious adversary model. Using ProVerif, a
cryptographic protocol verification tool, we are able to check the security of the protocol and provide a countermeasure
for each attack found by the tool. We also give a randomization method to avoid collusion attacks.
As an application, we show that this protocol enables a distributed and secure evaluation of trust relationships
in a network, for a large cl
ass of trust evaluation schemes.
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