Private Information Retrieval Schemes for Coded Data with Arbitrary Collusion Patterns

Razane Tajeddine; Oliver W. Gnilke; David Karpuk; Ragnar Freij-Hollanti; Camilla Hollanti; Salim El Rouayheb

Private Information Retrieval Schemes for Coded Data with Arbitrary Collusion Patterns

Information Theory 2017-06-23 v3 math.IT

Authors: Razane Tajeddine , Oliver W. Gnilke , David Karpuk , Ragnar Freij-Hollanti , Camilla Hollanti , Salim El Rouayheb

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Abstract

In Private Information Retrieval (PIR), one wants to download a file from a database without revealing to the database which file is being downloaded. Much attention has been paid to the case of the database being encoded across several servers, subsets of which can collude to attempt to deduce the requested file. With the goal of studying the achievable PIR rates in realistic scenarios, we generalize results for coded data from the case of all subsets of servers of size $t$ colluding, to arbitrary subsets of the servers. We investigate the effectiveness of previous strategies in this new scenario, and present new results in the case where the servers are partitioned into disjoint colluding groups.

Keywords

private information retrieval secure multi-party computation differential privacy

Cite

@article{arxiv.1701.07636,
  title  = {Private Information Retrieval Schemes for Coded Data with Arbitrary Collusion Patterns},
  author = {Razane Tajeddine and Oliver W. Gnilke and David Karpuk and Ragnar Freij-Hollanti and Camilla Hollanti and Salim El Rouayheb},
  journal= {arXiv preprint arXiv:1701.07636},
  year   = {2017}
}

Comments

Updated with a corrected statement of Theorem 2

Private Information Retrieval Schemes for Coded Data with Arbitrary Collusion Patterns

Abstract

Keywords

Cite

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