GASP Codes for Secure Distributed Matrix Multiplication

By Rafael G. L. D'Oliveira, Salim el Rouayheb, David A. Karpuk. 2018

122 citations recorded by the source corpus.

We consider the problem of secure distributed matrix multiplication (SDMM) in which a user wishes to compute the product of two matrices with the assistance of honest but curious servers. We construct polynomial codes for SDMM by studying a combinatorial problem on a special type of addition table, which we call the degree table. The codes are based on arithmetic progressions, and are thus named GASP (Gap Additive Secure Polynomial) Codes. GASP Codes are shown to outperform all previously known polynomial codes for secure distributed matrix multiplication in terms of download rate.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

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In Artificial Intelligence

1. Jörg Kliewer
2. Osvaldo Simeone
3. Malihe Aliasgari
4. Robert Akl
5. Robin Chataut

In Computational Theory and Mathematics

1. Jörg Kliewer
2. Osvaldo Simeone
3. Malihe Aliasgari

Citations in the corpus

• Distributed and Private Coded Matrix Computation with Flexible Communication Load (2019, methodology): “In [14], [15], [17] a reduction of the communication load is addressed by extending polynomial codes.”