Provable de-anonymization of large datasets with sparse dimensions
There is a significant body of empirical work on statistical de-anonymization attacks against databases containing micro-dataabout individuals, e.g., their preferences, movie ratings, or transactiondata. Our goal is to analytically explain why such attacks work. Specifically, we analyze a variant of...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2012
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/4471 https://ink.library.smu.edu.sg/context/sis_research/article/5474/viewcontent/dss_post12_1_.pdf |
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| Institution: | Singapore Management University |
| Language: | English |