The advent of social apps, smart phones and ubiquitous computing has brought the biggest transformation to our day-to-day life since the industrial revolution. The incredible pace with which the new and disruptive services continue to emerge, challenges our perception of privacy. We see an important part of this challenge in devising agile methods and frameworks, which keep apace with this rapidly evolving cyber reality, to develop privacy-preserving systems that align with evolving user’s privacy expectations.
Tackling this issues requires a multidisciplinary approach that brings computer scientists, formal methods experts and privacy researchers. Contextual integrity (CI) addresses this challenge by offering a model for conceptualizing privacy that is able to bridge scientific and technical approaches, on the one hand, with ethical, legal, and policy approaches, on the other. CI’s bedrock claim is that protecting privacy means protecting appropriate informational flows. It further stipulates that appropriate information flows are flows that comport with contextual informational norms (or rules), specified by the actors (senders, recipients and subjects), attributes (the type of information at hand) and transmission principles (type of constraints).
In our work we are guided by the theory of contextual integrity in exploring ways of capturing societal privacy that can be verified for consistency and enforced by the system.
LinkedIn makes the primary email address associated with an account visible to all direct connections, as well as to people who have your email address in their contacts lists. Read More ›