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Privacy preservation of aggregates in hidden databases: why and how?
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International Conference on Management of Data archive
Proceedings of the 35th SIGMOD international conference on Management of data table of contents
Providence, Rhode Island, USA
SESSION: Research session 4: security II table of contents
Pages 153-164  
Year of Publication: 2009
ISBN:978-1-60558-551-2
Authors
Arjun Dasgupta  University of Texas at Arlington, Arlington, TX, USA
Nan Zhang  George Washington University, Washington D.C., DC, USA
Gautam Das  University of Texas at Arlington, Arlington, TX, USA
Surajit Chaudhuri  Microsoft Research, Redmond, WA, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Many websites provide form-like interfaces which allow users to execute search queries on the underlying hidden databases. In this paper, we explain the importance of protecting sensitive aggregate information of hidden databases from being disclosed through individual tuples returned by the search queries. This stands in contrast to the traditional privacy problem where individual tuples must be protected while ensuring access to aggregating information. We propose techniques to thwart bots from sampling the hidden database to infer aggregate information. We present theoretical analysis and extensive experiments to illustrate the effectiveness of our approach.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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A. Dasgupta, N. Zhang, G. Das, S. Chaudhuri, On Privacy Preservations of Aggregates in Hidden Databases, Technical Report TR-GWU-CS-09-001, George Washington University, 2009.
 
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Collaborative Colleagues:
Arjun Dasgupta: colleagues
Nan Zhang: colleagues
Gautam Das: colleagues
Surajit Chaudhuri: colleagues