Differential Privacy

Towards usable differentially private analyses — Exploring suitable metaphors for lay users

We present our work on the suitability of the metaphors for aiding informed decisions of data subjects on sharing their data with differential privacy (DP) systems and discuss open research challenges.

Differential Privacy — A Balancing Act

Data privacy is an ever important aspect of data analyses. Historically, a plethora of privacy techniques have been introduced to protect data, but few have stood the test of time. From investigating the overlap between big data research, and security and privacy research, I have found that _differential privacy_ presents itself as a promising defender of data privacy.