Measuring privacy loss and the impact of privacy protection in web browsing
Proceedings of the 3rd symposium on Usable privacy and security
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Fighting online click-fraud using bluff ads
ACM SIGCOMM Computer Communication Review
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Privad: practical privacy in online advertising
Proceedings of the 8th USENIX conference on Networked systems design and implementation
When are users comfortable sharing locations with advertisers?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 18th ACM conference on Computer and communications security
For sale : your data: by : you
Proceedings of the 10th ACM Workshop on Hot Topics in Networks
Don't kill my ads!: balancing privacy in an ad-supported mobile application market
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Koi: a location-privacy platform for smartphone apps
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Measuring and fingerprinting click-spam in ad networks
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
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A practical solution to location privacy should be incrementally deployable. We claim it should hence reconcile the economic value of location to aggregators, usually ignored by prior works, with a user's control over her information. Location information indeed is being collected and used by many mobile services to improve revenues, and this gives rise to a heated debate: Privacy advocates ask for stricter regulation on information collection, while companies argue that it would jeopardize the thriving economy of the mobile web. We describe a system that gives users control over their information and does not degrade the data given to aggregators. Recognizing that the first challenge is to express locations in a way that is meaningful for advertisers and users, we propose a keyword-based design. Keywords characterize locations, let the users inform the system about their sensitivity to disclosure, and build information directly usable by an advertiser's targeting campaign. Our work makes two main contributions: we design a market of location information based on keywords and we analyze its robustness to attacks using data from ad-networks, geo-located services, and cell networks.