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Achievable Rate of Private Function Retrieval from MDS Coded Databases

2018/02/22 by Sarah A. Obead, Jorg Kliewer, Jörg Kliewer
Computer Science · Mathematics · #Advanced Data Storage Technologies #Code rate #Cryptography and Data Security #Data retrieval #Function (biology) #Privacy-Preserving Technologies in Data #Private information retrieval #Scheme (mathematics) #cs.IT #math.IT

paper · pdf · doi:10.1109/isit.2018.8437655

published as IEEE International Symposium on Information Theory (ISIT), Vail, CO, USA, June 2018, pp. 2117-2121 · 5 pages, 1 table, submitted for publication

arxiv created 2018/02/22 · openalex created_date 2018/03/06 · openalex publication_date 2018/06/01 · arxiv updated 2021/06/29 · openalex updated_date 2026/08/05

Abstract

We study the problem of private function retrieval (PFR) in a distributed storage system. In PFR the user wishes to retrieve a linear combination of M messages stored in non-colluding (N, K) MDS coded databases while revealing no information about the coefficients of the intended linear combination to any of the individual databases. We present an achievable scheme for MDS coded PFR with a rate that matches the capacity for coded private information retrieval derived recently, R = (1+Rc+Rc2+...+RcM-1)-1=[(1-Rc)/(1-RcM)], where Rc=[K/N] is the rate of the MDS code.

Citations