Presentation	2013-11-12 Query auditing for privacy preserving similarity search Hiromi Arai, Koji Tsuda, Jun Sakuma,
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Abstract(in English)	In this paper, we propose a query auditing method for similarity searches that examines whether database responces satisfy privacy preserving requirements. We assume that the database answers a set of similar records's IDs against each query. We introduce the probability of a certain private value given database responsesas as a privacy measure. We describe auditing with such a privacy measure as an enumeration problem and apply the efficient and accurate algorithm. The computational efficiency and the result of this auditing method is examined on the real world dataset.
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Paper #	IBISML2013-46
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Committee	IBISML
Conference Date	2013/11/5(1days)
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Registration To	Information-Based Induction Sciences and Machine Learning (IBISML)
Language	JPN
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Title (in English)	Query auditing for privacy preserving similarity search
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1st Author's Name	Hiromi Arai
1st Author's Affiliation	RIKEN Advanced Center for Computing and Communication()
2nd Author's Name	Koji Tsuda
2nd Author's Affiliation	Computational Biology Research Center National Institute of Advanced Industrial Science and Technology
3rd Author's Name	Jun Sakuma
3rd Author's Affiliation	Department of Computer Science, University of Tsukuba
Date	2013-11-12
Paper #	IBISML2013-46
Volume (vol)	vol.113
Number (no)	286
Page	pp.pp.-
#Pages	7
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