Disclosure Analysis for Two-Way Contingency Tables
Disclosure analysis in two-way contingency tables is important in categorical data analysis. The disclosure analysis concerns whether a data snooper can infer any protected cell values, which contain privacy sensitive information, from available marginal totals (i.e., row sums and column sums) in a...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2006
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/569 https://ink.library.smu.edu.sg/context/sis_research/article/1568/viewcontent/Lu2006_Chapter_DisclosureAnalysisForTwo_WayCo.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Disclosure analysis in two-way contingency tables is important in categorical data analysis. The disclosure analysis concerns whether a data snooper can infer any protected cell values, which contain privacy sensitive information, from available marginal totals (i.e., row sums and column sums) in a two-way contingency table. Previous research has been targeted on this problem from various perspectives. However, there is a lack of systematic definitions on the disclosure of cell values. Also, no previous study has been focused on the distribution of the cells that are subject to various types of disclosure. In this paper, we define four types of possible disclosure based on the exact upper bound and/or the lower bound of each cell that can be computed from the marginal totals. For each type of disclosure, we discover the distribution pattern of the cells subject to disclosure. Based on the distribution patterns discovered, we can speed up the search for all cells subject to disclosure. |
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