Robust, Secure and Private Cache-aided Scalar Linear Function Retrieval from Distributed System with Blind and Adversarial Servers

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Yan, Qifa, Tang, Xiaohu, Zhou, Zhengchun
Formato: Preprint
Publicado: 2023
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866914883981803520
author Yan, Qifa
Tang, Xiaohu
Zhou, Zhengchun
author_facet Yan, Qifa
Tang, Xiaohu
Zhou, Zhengchun
contents In this work, a distributed server system composed of multiple servers that holds some coded files and multiple users that are interested in retrieving the linear functions of the files is investigated, where the servers are robust, blind and adversarial in the sense that any $J$ servers can together recover all files, while any $I$ colluding servers cannot obtain any information about the files, and at most $A$ servers maliciously provides erroneous information. In addition, the file library must be secure from a wiretapper who obtains all the signals, and the demands of any subset of users must kept private from the other users and servers, even if they collude. A coding scheme is proposed by incorporating the ideas of Shamir's secret sharing and key superposition into the framework of Placement Delivery Array (PDA), originally proposed to characterize the single-server coded caching system without any security or privacy constraints. It is shown that PDAs associated to Maddah-Ali and Niesen's coded caching scheme results in an achievable memory-storage-communication region, such that the storage size and communication load were optimal to within a multiplicative gap, except for the small memory regime when the number of files was smaller than the number of users.
format Preprint
id arxiv_https___arxiv_org_abs_2301_08711
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Robust, Secure and Private Cache-aided Scalar Linear Function Retrieval from Distributed System with Blind and Adversarial Servers
Yan, Qifa
Tang, Xiaohu
Zhou, Zhengchun
Information Theory
In this work, a distributed server system composed of multiple servers that holds some coded files and multiple users that are interested in retrieving the linear functions of the files is investigated, where the servers are robust, blind and adversarial in the sense that any $J$ servers can together recover all files, while any $I$ colluding servers cannot obtain any information about the files, and at most $A$ servers maliciously provides erroneous information. In addition, the file library must be secure from a wiretapper who obtains all the signals, and the demands of any subset of users must kept private from the other users and servers, even if they collude. A coding scheme is proposed by incorporating the ideas of Shamir's secret sharing and key superposition into the framework of Placement Delivery Array (PDA), originally proposed to characterize the single-server coded caching system without any security or privacy constraints. It is shown that PDAs associated to Maddah-Ali and Niesen's coded caching scheme results in an achievable memory-storage-communication region, such that the storage size and communication load were optimal to within a multiplicative gap, except for the small memory regime when the number of files was smaller than the number of users.
title Robust, Secure and Private Cache-aided Scalar Linear Function Retrieval from Distributed System with Blind and Adversarial Servers
topic Information Theory
url https://arxiv.org/abs/2301.08711