Using randomized response techniques for privacy-preserving data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Characterizing privacy in online social networks
Proceedings of the first workshop on Online social networks
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Privacy integrated queries: an extensible platform for privacy-preserving data analysis
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
On the leakage of personally identifiable information via online social networks
ACM SIGCOMM Computer Communication Review
ICDCN'11 Proceedings of the 12th international conference on Distributed computing and networking
SpotME If You Can: Randomized Responses for Location Obfuscation on Mobile Phones
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Towards statistical queries over distributed private user data
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
A cloud-based consumer-centric architecture for energy data analytics
Proceedings of the fourth international conference on Future energy systems
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We discuss the problem of building a user-acceptable infrastructure for a large organisation that wishes to measure its employees' travel-to-work carbon footprint, based on the gathering of high resolution geolocation data on employees in a privacy-sensitive manner. This motivated the construction of a distributed system of personal containers in which individuals record fine-grained location information into a private data-store which they own, and from which they can trade portions of data to the organisation in return for specific benefits. This framework can be extended to gather a wide variety of personal data and facilitates the transformation of private information into a public good, with minimal and assessable loss of individual privacy. This is currently a work in progress. We report on the hardware, software and social aspects of piloting this scheme on the University of Cambridge's experimental cloud service, as well as contrasting it to a traditional centralised model.