Confidential carbon commuting: exploring a privacy-sensitive architecture for incentivising 'greener' commuting

  • Authors:
  • Chris Elsmore;Anil Madhavapeddy;Ian Leslie;Amir Chaudhry

  • Affiliations:
  • Cambridge University Computer Laboratory, Cambridge, UK;Cambridge University Computer Laboratory, Cambridge, UK;Cambridge University Computer Laboratory, Cambridge, UK;Cambridge University Computer Laboratory, Cambridge, UK

  • Venue:
  • Proceedings of the First Workshop on Measurement, Privacy, and Mobility
  • Year:
  • 2012

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Abstract

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.