| Privacy preservation of aggregates in hidden databases: why and how? |
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International Conference on Management of Data
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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
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Authors
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Arjun Dasgupta
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University of Texas at Arlington, Arlington, TX, USA
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Nan Zhang
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George Washington University, Washington D.C., DC, USA
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Gautam Das
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University of Texas at Arlington, Arlington, TX, USA
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Surajit Chaudhuri
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Microsoft Research, Redmond, WA, 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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N. Bruno, L. Gravano, A. Marian: Evaluating Top-k Queries over Web-Accessible Databases. ICDE 2002.
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9
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10
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11
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12
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13
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14
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C. Dwork, F. McSherry, K. Nissim, and A. Smith, Calibrating noise to sensitivity in private data analysis. Theory of Cryptography Conference 2006.
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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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J. Elson, J. R. Douceur, J. Howell, J. Saul: Asirra: a CAPTCHA that exploits interest-aligned manual image categorization, CCS 2007.
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19
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S. Hettich and S. D. Bay, The UCI KDD Archive {http://kdd.ics.uci.edu}. Irvine, CA: University of California, Department of Information and Computer Science. 1999.
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22
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Shubha U. Nabar , Bhaskara Marthi , Krishnaram Kenthapadi , Nina Mishra , Rajeev Motwani, Towards robustness in query auditing, Proceedings of the 32nd international conference on Very large data bases, September 12-15, 2006, Seoul, Korea
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