Private Index Coding

Narayanan, Varun; Ravi, Jithin; Mishra, Vivek; Dey, Bikash Kumar; Karamchandani, Nikhil; Prabhakaran, Vinod M.

doi:10.1109/tit.2021.3130629

Cited by 7 publications

(16 citation statements)

References 26 publications

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“…Since any converse bound with no privacy requirement is also a converse bound with privacy. So, to prove the converse result, we need to show only the second inequality in (22) and in (21). Furthermore, observe that substituting N = 2 in the second inequality in (22) gives the second inequality in (21).…”

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

“…So, to show the converse of Theorem 6, we prove that for N ≥ K = 2, any (M, R) pair under privacy satisfies the second inequality in (22). Full proof of the converse can be found in Subsection IV-F. Outline of achievability: To show the achievability of the region in (21), we use a particular non-private scheme from [34]. Using this particular non-private scheme, we can show that for any (M, R) pair in the region by (21), there exists an (2, 4, M, R)-D RS -non-private scheme.…”

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

“…So, to prove the converse result, we need to show only the second inequality in (22) and in (21). Furthermore, observe that substituting N = 2 in the second inequality in (22) gives the second inequality in (21). So, to show the converse of Theorem 6, we prove that for N ≥ K = 2, any (M, R) pair under privacy satisfies the second inequality in (22).…”

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

“…Next we give some outlines of the achievability schemes and the converse to obtain Theorem 6. Outline of converse: Any (M, R) pair that is achievable under no privacy requirement needs to satisfy the first and third inequalities in (21) for N = K = 2 [1]. Similarly, for N > K = 2, any (M, R) pair satisfies the first and third inequalities in (22) under no privacy [34].…”

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

“…Two types of security/privacy issues have been studied in index coding. The works [21], [22] addressed the problem of file privacy where the constraint is that each user should not get any information about any file other than the requested one. The work [23] studied index coding with demand privacy where each user should not get any information about the identity of the file requested by other users.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Fundamental Limits of Demand-Private Coded Caching

Gurjarpadhye¹,

Ravi²,

Kamath³

et al. 2021

Preprint

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We consider the coded caching problem with an additional privacy constraint that a user should not get any information about the demands of the other users. We first show that a demand-private scheme for N files and K users can be obtained from a non-private scheme that serves only a subset of the demands for the N files and N K users problem. We further use this fact to construct a demand-private scheme for N files and K users from a particular known non-private scheme for N files and N K − K + 1 users. It is then demonstrated that, the memoryrate pair (M, min{N, K}(1 − M/N )), which is achievable for non-private schemes with uncoded transmissions, is also achievable under demand privacy. We further propose a scheme that improves on these ideas by removing some redundant transmissions. The memory-rate trade-off achieved using our schemes is shown to be within a multiplicative factor of 3 from the optimal when K < N and of 8 when N ≤ K. Finally, we give the exact memory-rate trade-off for demand-private coded caching problems with N ≥ K = 2.

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Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

Section: E Tightness Of the Achievable Memory-rate Pairsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fundamental Limits of Demand-Private Coded Caching

Gurjarpadhye¹,

Ravi²,

Kamath³

et al. 2021

Preprint

Self Cite

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Privacy in Index Coding: $k$ -Limited-Access Schemes

Karmoose

Song

Cardone

et al. 2020

IEEE Trans. Inform. Theory

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In the traditional index coding problem, a server employs coding to send messages to n clients within the same broadcast domain. Each client already has some messages as side information and requests a particular unknown message from the server. All clients learn the coding matrix so that they can decode and retrieve their requested data. Our starting observation is that, learning the coding matrix can pose privacy concerns: it may enable a client to infer information about the requests and side information of other clients. In this paper, we mitigate this privacy concern by allowing each client to have limited access to the coding matrix. In particular, we design coding matrices so that each client needs only to learn some of (and not all) the rows to decode her requested message. By means of two different privacy metrics, we first show that this approach indeed increases the level of privacy. Based on this, we propose the use of k-limited-access schemes: given an index coding scheme that employs T transmissions, we create a k-limited-access scheme with T k ≥ T transmissions, and with the property that each client needs at most k transmissions to decode her message. We derive upper and lower bounds on T k for all values of k, and develop deterministic designs for these schemes, which are universal, i.e., independent of the coding matrix. We show that our schemes are order-optimal when either k or n is large. Moreover, we propose heuristics that complement the universal schemes for the case when both n and k are small.

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Sun

2022

IEEE Trans. Inform. Theory

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Private Index Coding

Cited by 7 publications

References 26 publications

Fundamental Limits of Demand-Private Coded Caching

Fundamental Limits of Demand-Private Coded Caching

Privacy in Index Coding: $k$ -Limited-Access Schemes

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