Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Privacy preserving itemset mining through fake transactions
Proceedings of the 2007 ACM symposium on Applied computing
Disappearing for a while - using white lies in pervasive computing
Proceedings of the 2007 ACM workshop on Privacy in electronic society
End-user privacy in human-computer interaction
Foundations and Trends in Human-Computer Interaction
Privacy: Theory meets Practice on the Map
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Realistic Driving Trips For Location Privacy
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Noise Injection for Search Privacy Protection
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 03
Inference attacks on location tracks
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Unraveling an old cloak: k-anonymity for location privacy
Proceedings of the 9th annual ACM workshop on Privacy in the electronic society
Protecting location privacy against inference attacks
Proceedings of the 9th annual ACM workshop on Privacy in the electronic society
On the privacy of web search based on query obfuscation: a case study of TrackMeNot
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
Protecting location privacy: optimal strategy against localization attacks
Proceedings of the 2012 ACM conference on Computer and communications security
Web search query privacy: Evaluating query obfuscation and anonymizing networks
Journal of Computer Security
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The amount of contextual data collected, stored, mined, and shared is increasing exponentially. Street cameras, credit card transactions, chat and Twitter logs, e-mail, web site visits, phone logs and recordings, social networking sites, all are examples of data that persists in a manner not under individual control, leading some to declare the death of privacy. We argue here that the ability to generate convincing fake contextual data can be a basic tool in the fight to preserve privacy. One use for the technology is for an individual to make his actual data indistinguishable amongst a pile of false data. In this paper we consider two examples of contextual data, search engine query data and location data. We describe the current state of faking these types of data and our own efforts in this direction.