Data Privacy for a ρ-Recoverable Function

A user's data is represented by a finite-valued random variable. Given a function of the data, a querier is required to recover, with at least a prescribed probability, the value of the function based on a query response provided by the user. The user devises the query response, subject to the...

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Bibliographic Details
Published in:2018 IEEE International Symposium on Information Theory (ISIT) pp. 1046 - 1050
Main Authors: Nageswaran, Ajaykrishnan, Narayan, Prakash
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2018
Subjects:
Chernoff radius
function computation
Information theory
Measurement uncertainty
Privacy
recoverability
Upper bound
Zinc
ISSN:2157-8117
Online Access:Get full text
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Summary:A user's data is represented by a finite-valued random variable. Given a function of the data, a querier is required to recover, with at least a prescribed probability, the value of the function based on a query response provided by the user. The user devises the query response, subject to the recoverability requirement, so as to maximize privacy of the data from the querier. Privacy is measured by the probability of error incurred by the querier in estimating the data from the query response. We analyze single and multiple independent query responses, with each response satisfying the recoverability requirement, that provide maximum privacy to the user. Achievability schemes with explicit randomization mechanisms for query responses are given and their privacy compared with converse upper bounds.
ISSN:2157-8117
DOI:10.1109/ISIT.2018.8437327