The active badge location system
ACM Transactions on Information Systems (TOIS)
Who wants to know what when? privacy preference determinants in ubiquitous computing
CHI '03 Extended Abstracts on Human Factors in Computing Systems
Location disclosure to social relations: why, when, & what people want to share
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who gets to know what when: configuring privacy permissions in an awareness application
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Practical Lessons from Place Lab
IEEE Pervasive Computing
User-Controllable Security and Privacy for Pervasive Computing
HOTMOBILE '07 Proceedings of the Eighth IEEE Workshop on Mobile Computing Systems and Applications
From awareness to repartee: sharing location within social groups
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who's viewed you?: the impact of feedback in a mobile location-sharing application
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A framework of energy efficient mobile sensing for automatic user state recognition
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Understanding and capturing people's privacy policies in a mobile social networking application
Personal and Ubiquitous Computing
A theory of expressiveness in mechanisms
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Methodology for designing reasonably expressive mechanisms with application to ad auctions
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Understanding User Preferences and Awareness: Privacy Mechanisms in Location-Based Services
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
Access Control for Home Data Sharing: Attitudes, Needs and Practices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Do i do what i say?: observed versus stated privacy preferences
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction
Empirical models of privacy in location sharing
Proceedings of the 12th ACM international conference on Ubiquitous computing
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PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
When are users comfortable sharing locations with advertisers?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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HotSec'11 Proceedings of the 6th USENIX conference on Hot topics in security
Who's your best friend?: targeted privacy attacks In location-sharing social networks
Proceedings of the 13th international conference on Ubiquitous computing
Super-Ego: a framework for privacy-sensitive bounded context-awareness
CASEMANS '11 Proceedings of the 5th ACM International Workshop on Context-Awareness for Self-Managing Systems
Improving users' consistency when recalling location sharing preferences
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part I
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User Modeling and User-Adapted Interaction
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The implications of offering more disclosure choices for social location sharing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
"Check out where I am!": location-sharing motivations, preferences, and practices
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Reasons, rewards, regrets: privacy considerations in location sharing as an interactive practice
Proceedings of the Eighth Symposium on Usable Privacy and Security
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Leveraging media repertoires to create new social ties
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
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Proceedings of the 20th International Conference on Advances in Geographic Information Systems
My privacy policy: exploring end-user specification of free-form location access rules
FC'12 Proceedings of the 16th international conference on Financial Cryptography and Data Security
A comparative study of location-sharing privacy preferences in the United States and China
Personal and Ubiquitous Computing
Preference-based location sharing: are more privacy options really better?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Privacy manipulation and acclimation in a location sharing application
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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DUXU'13 Proceedings of the Second international conference on Design, User Experience, and Usability: web, mobile, and product design - Volume Part IV
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Location sharing privacy preference: analysis and personalized recommendation
Proceedings of the 19th international conference on Intelligent User Interfaces
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Proceedings of the 23rd international conference on World wide web
Crowdsourcing privacy preferences in context-aware applications
Personal and Ubiquitous Computing
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We present a 3-week user study in which we tracked the locations of 27 subjects and asked them to rate when, where, and with whom they would have been comfortable sharing their locations. The results of analysis conducted on over 7,500聽h of data suggest that the user population represented by our subjects has rich location-privacy preferences, with a number of critical dimensions, including time of day, day of week, and location. We describe a methodology for quantifying the effects, in terms of accuracy and amount of information shared, of privacy-setting types with differing levels of complexity (e.g., setting types that allow users to specify location- and/or time-based rules). Using the detailed preferences we collected, we identify the best possible policy (or collection of rules granting access to one's location) for each subject and privacy-setting type. We measure the accuracy with which the resulting policies are able to capture our subjects' preferences under a variety of assumptions about the sensitivity of the information and user-burden tolerance. One practical implication of our results is that today's location-sharing applications may have failed to gain much traction due to their limited privacy settings, as they appear to be ineffective at capturing the preferences revealed by our study.