New Instantiations of the CRYPTO 2017 Masking Schemes

  • Pierre KarpmanEmail author
  • Daniel S. RocheEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11273)


At CRYPTO 2017, Belaïd et al. presented two new private multiplication algorithms over finite fields, to be used in secure masking schemes. To date, these algorithms have the lowest known complexity in terms of bilinear multiplication and random masks respectively, both being linear in the number of shares \(d+1\). Yet, a practical drawback of both algorithms is that their safe instantiation relies on finding matrices satisfying certain conditions. In their work, Belaïd et al. only address these up to \(d=2\) and 3 for the first and second algorithm respectively, limiting so far the practical usefulness of their constructions.

In this paper, we use in turn an algebraic, heuristic, and experimental approach to find many more safe instances of Belaïd et al.’s algorithms. This results in explicit instantiations up to order \(d = 6\) over large fields, and up to \(d = 4\) over practically relevant fields such as \(\mathbb {F}_{2^8}\).


Masking Linear algebra MDS matrices 



We thank Daniel Augot for the interesting discussions we had in the early stages of this work.

This work was performed while the second author was graciously hosted by the Laboratoire Jean Kuntzmann at the Université Grenoble Alpes.

The first author was supported in part by the French National Research Agency through the framework of the “Investissements d’avenir” program (ANR-15-IDEX-02).

The second author was supported in part by the National Science Foundation under grants #1319994 and #1618269, and in part by the Office of Naval Research award #N0001417WX01516.

Some of the computations were performed using the Grace supercomputer hosted by the U.S. Naval Academy Center for High Performance Computing, with funding from the DoD HPC Modernization Program.


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Copyright information

© International Association for Cryptologic Research 2018

Authors and Affiliations

  1. 1.Univ. Grenoble Alpes, CNRSGrenobleFrance
  2. 2.INP, Institute of Engineering Univ. Grenoble Alpes, LJKGrenobleFrance
  3. 3.United States Naval AcademyAnnapolisUSA

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