Practical Inference Control for Data Cubes

The fundamental problem for inference control in data cubes is how to efficiently calculate the lower and upper bounds for each cell value given the aggregations of cell values over multiple dimensions. In this paper, we provide the first practical solution for estimating exact bounds in two-dimensi...

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Main Authors: LI, Yingjiu, LU, Haibing, DENG, Robert H.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2006
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Online Access:https://ink.library.smu.edu.sg/sis_research/597
http://dx.doi.org/10.1109/SP.2006.31
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spelling sg-smu-ink.sis_research-15962015-12-20T08:00:37Z Practical Inference Control for Data Cubes LI, Yingjiu LU, Haibing DENG, Robert H. The fundamental problem for inference control in data cubes is how to efficiently calculate the lower and upper bounds for each cell value given the aggregations of cell values over multiple dimensions. In this paper, we provide the first practical solution for estimating exact bounds in two-dimensional irregular data cubes (i.e., data cubes in which certain cell values are known to a snooper). Our results imply that the exact bounds cannot be obtained by a direct application of the Fréchet bounds in some cases. We then propose a new approach to improve the classic Fréchet bounds for any high-dimensional data cube in the most general case. The proposed approach improves upon the Fréchet bounds in the sense that it gives bounds that are at least as tight as those computed by Fréchet, yet is simpler in terms of time complexity. Based on our solutions to the fundamental problem, we discuss two security applications, privacy protection of released data and fine-grained access control and auditing. 2006-03-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/597 info:doi/10.1109/SP.2006.31 http://dx.doi.org/10.1109/SP.2006.31 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Information Security
spellingShingle Information Security
LI, Yingjiu
LU, Haibing
DENG, Robert H.
Practical Inference Control for Data Cubes
description The fundamental problem for inference control in data cubes is how to efficiently calculate the lower and upper bounds for each cell value given the aggregations of cell values over multiple dimensions. In this paper, we provide the first practical solution for estimating exact bounds in two-dimensional irregular data cubes (i.e., data cubes in which certain cell values are known to a snooper). Our results imply that the exact bounds cannot be obtained by a direct application of the Fréchet bounds in some cases. We then propose a new approach to improve the classic Fréchet bounds for any high-dimensional data cube in the most general case. The proposed approach improves upon the Fréchet bounds in the sense that it gives bounds that are at least as tight as those computed by Fréchet, yet is simpler in terms of time complexity. Based on our solutions to the fundamental problem, we discuss two security applications, privacy protection of released data and fine-grained access control and auditing.
format text
author LI, Yingjiu
LU, Haibing
DENG, Robert H.
author_facet LI, Yingjiu
LU, Haibing
DENG, Robert H.
author_sort LI, Yingjiu
title Practical Inference Control for Data Cubes
title_short Practical Inference Control for Data Cubes
title_full Practical Inference Control for Data Cubes
title_fullStr Practical Inference Control for Data Cubes
title_full_unstemmed Practical Inference Control for Data Cubes
title_sort practical inference control for data cubes
publisher Institutional Knowledge at Singapore Management University
publishDate 2006
url https://ink.library.smu.edu.sg/sis_research/597
http://dx.doi.org/10.1109/SP.2006.31
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