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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Vydáno v:2018 IEEE International Symposium on Information Theory (ISIT) s. 1046 - 1050
Hlavní autoři: Nageswaran, Ajaykrishnan, Narayan, Prakash
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2018
Témata:
Chernoff radius
function computation
Information theory
Measurement uncertainty
Privacy
recoverability
Upper bound
Zinc
ISSN:2157-8117
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Shrnutí: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