Private Index Coding
Private Index Coding
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DOI:
10.1109/tit.2021.3130629
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发表时间:
2020
影响因子:
2.5
通讯作者:
V. Prabhakaran
中科院分区:
文献类型:
--
作者:
Varun Narayanan;Jithin Ravi;V. Mishra;B. Dey;Nikhil Karamchandani;V. Prabhakaran
We study the fundamental problem of index coding under an additional privacy constraint that requires each receiver to learn nothing more about the collection of messages beyond its demanded messages from the server and what is available to it as side information. To enable such private communication, we allow the use of a collection of independent secret keys, each of which is shared amongst a subset of users and is known to the server. The goal is to study properties of the key access structures that make the problem feasible and then design encoding and decoding schemes efficient in the size of the server transmission as well as the sizes of the secret keys. We call this the private index coding problem. We begin by characterizing the key access structures that make private index coding feasible. We also give conditions to check if a given linear scheme is a valid private index code. For up to three users, we characterize the rate region of feasible server transmission and key rates, and show that all feasible rates can be achieved using scalar linear coding and time sharing; we also show that scalar linear codes are sub-optimal for four receivers. The outer bounds used in the case of three users are extended to arbitrary number of users and seen as a generalized version of the well-known polymatroidal bounds for the standard non-private index coding. We also show that the presence of common randomness and private randomness does not change the rate region. Furthermore, we study the case where the server has the ability to multicast to any subset of users, and demonstrate how this flexibility can be used to provide privacy and characterize the minimum number of server multicasts required.
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DOI:
10.1109/isit.2018.8437816
发表时间:
2018-06
期刊:
2018 IEEE International Symposium on Information Theory (ISIT)
影响因子:
--
作者:
L. Ong;J. Kliewer;Badri N. Vellambi
通讯作者:
L. Ong;J. Kliewer;Badri N. Vellambi
DOI:
10.1109/itw44776.2019.8989161
发表时间:
2019
期刊:
2019 IEEE Information Theory Workshop
影响因子:
--
作者:
Liu, Tang;Tuninetti, Daniela
通讯作者:
Tuninetti, Daniela
影响因子:
2.5
作者:
Karmoose, Mohammed;Song, Linqi;Cardone, Martina;Fragouli, Christina
通讯作者:
Fragouli, Christina
影响因子:
2.5
作者:
Sun, Hua
通讯作者:
Sun, Hua
DOI:
10.1109/isit44484.2020.9173957
发表时间:
2020
期刊:
2020 IEEE International Symposium on Information Theory
影响因子:
--
作者:
Liu, Tang;Tuninetti, Daniela
通讯作者:
Tuninetti, Daniela