Provable de-anonymization of large datasets with sparse dimensions

• Main Authors: DATTA, Anupam, SHARMA, Divya, SINHA, Arunesh
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: Privacy; database; de-anonymization; Artificial Intelligence and Robotics; Computer Engineering
• 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
• Institution: Singapore Management University

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...