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Simulatable auditing

Simulatable auditing Simulatable Auditing Krishnaram Kenthapadi — Nina Mishra Kobbi Nissim ¡ ABSTRACT Given a data set consisting of private information about individuals, we consider the online query auditing problem: given a sequence of queries that have already been posed about the data, their corresponding answers “ where each answer is either the true answer or œdenied  (in the event that revealing the answer compromises privacy) “ and given a new query, deny the answer if privacy may be breached or give the true answer otherwise. A related problem is the o „ine auditing problem where one is given a sequence of queries and all of their true answers and the goal is to determine if a privacy breach has already occurred. We uncover the fundamental issue that solutions to the of ‚ine auditing problem cannot be directly used to solve the online auditing problem since query denials may leak information. Consequently, we introduce a new model called simulatable auditing where query denials provably do not leak information. We demonstrate that max queries may be audited in this simulatable paradigm under the classical definition of privacy where a breach occurs if a sensitive value is fully compromised. We also http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Simulatable auditing

Association for Computing Machinery — Jun 13, 2005

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References (23)

Datasource
Association for Computing Machinery
Copyright
Copyright © 2005 by ACM Inc.
ISBN
1-59593-062-0
doi
10.1145/1065167.1065183
Publisher site
See Article on Publisher Site

Abstract

Simulatable Auditing Krishnaram Kenthapadi — Nina Mishra Kobbi Nissim ¡ ABSTRACT Given a data set consisting of private information about individuals, we consider the online query auditing problem: given a sequence of queries that have already been posed about the data, their corresponding answers “ where each answer is either the true answer or œdenied  (in the event that revealing the answer compromises privacy) “ and given a new query, deny the answer if privacy may be breached or give the true answer otherwise. A related problem is the o „ine auditing problem where one is given a sequence of queries and all of their true answers and the goal is to determine if a privacy breach has already occurred. We uncover the fundamental issue that solutions to the of ‚ine auditing problem cannot be directly used to solve the online auditing problem since query denials may leak information. Consequently, we introduce a new model called simulatable auditing where query denials provably do not leak information. We demonstrate that max queries may be audited in this simulatable paradigm under the classical definition of privacy where a breach occurs if a sensitive value is fully compromised. We also

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