Quantifying the cost of privately storing data in distributed storage systems

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Authors
Chou, Rémi
Advisors
Issue Date
2022-07-01
Type
Preprint
Keywords
Costs , Distributed databases , Data models , Servers , Information theory
Research Projects
Organizational Units
Journal Issue
Citation
R. A. Chou, "Quantifying the Cost of Privately Storing Data in Distributed Storage Systems," 2022 IEEE International Symposium on Information Theory (ISIT), 2022, pp. 3274-3279, doi: 10.1109/ISIT50566.2022.9834900.
Abstract

Consider a user who wishes to store a file in multiple servers such that at least t servers are needed to reconstruct the files, and z colluding servers cannot learn any information about the file. Unlike traditional models, where perfectly secure channels are assumed to be available at no cost between the user and each server, we assume that the user can only send data to the servers via public channels, and that the user and each server share an individual secret key with length n. For a given n, we determine the maximal length of the file that the user can store, and thus quantify the necessary cost to store a file with a certain length, in terms of the length of the secret that the user needs to share with the servers. Additionally, for this maximal file length, we determine (i) the optimal amount of local randomness needed at the user, (ii) the optimal amount of public communication from the user to the servers, and (iii) the optimal amount of storage requirement at the servers. © 2022 IEEE.

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Description
Preprint version available from arXiv. Click on the DOI to access the publisher's version of this article.
Publisher
IEEE
Journal
Book Title
Series
2022 IEEE International Symposium on Information Theory (ISIT)
2022
PubMed ID
DOI
ISSN
2157-8117
EISSN