학술논문
Anon-Pass: Practical Anonymous Subscriptions
Document Type
Periodical
Source
IEEE Security & Privacy IEEE Secur. Privacy Security & Privacy, IEEE. 12(3):20-27 Jun, 2014
Subject
Language
ISSN
1540-7993
1558-4046
1558-4046
Abstract
Electronic subscriptions are widespread and quickly becoming the dominant mode of access for services like music and video streaming, news, and academic articles. Although electronic subscriptions are convenient for users, they reveal a lot of information, ranging from personal preferences to geographic movements. Many users want electronic services, but they also want privacy. Simply anonymizing data doesn’t always protect users’ privacy. Indeed, multiple anonymized datasets released for research purposes, including the AOL search dataset1 and the Netflix Prize dataset,2 have been partially deanonymized through correlation or by understanding of the semantics of the released data.