The best privacy defense is a good privacy offense: obfuscating a search engine user’s profile-Reference-Cited by-同舟云学术

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The best privacy defense is a good privacy offense: obfuscating a search engine user’s profile

Published:2017-06-28 Issue:5 Volume:31 Page:1419-1443
ISSN:1384-5810
Container-title:Data Mining and Knowledge Discovery
language:en
Short-container-title:Data Min Knowl Disc

Author:

Wicker Jörg^ORCID,Kramer Stefan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://link.springer.com/article/10.1007/s10618-017-0524-z/fulltext.html

Reference29 articles.

1. Agrawal R, Srikant R (2000) Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD international conference on management of data. ACM, New York, pp 439–450

2. Aldeen YAAS, Salleh M, Razzaque MA (2015) A comprehensive review on privacy preserving data mining. SpringerPlus 4(1):694

3. Barreno M, Nelson B, Joseph AD, Tygar J (2010) The security of machine learning. Mach Learn 81(2):121–148

4. Barreno M, Nelson B, Sears R, Joseph AD, Tygar JD (2006) Can machine learning be secure? In: Proceedings of the 2006 ACM symposium on information, computer and communications security. ACM, New York, pp 16–25

5. Beato F, Conti M, Preneel B (2013) Friend in the middle (fim): tackling de-anonymization in social networks. In: IEEE international conference on pervasive computing and communications workshops (PERCOM Workshops), pp 279–284

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