Now showing items 1-4 of 4

    • Bridging the Gap between Computer Science and Legal Approaches to Privacy 

      Nissim, Kobbi; Bembenek, Aaron; Wood, Alexandra B; Bun, Mark Mar; Gaboardi, Marco; Gasser, Urs; O'Brien, David; Vadhan, Salil P.; Steinke, Thomas (Harvard Law School, 2018)
      The analysis and release of statistical data about individuals and groups of individuals carries inherent privacy risks, and these risks have been conceptualized in different ways within the fields of law and computer ...
    • Fingerprinting codes and the price of approximate differential privacy 

      Bun, Mark Mar; Ullman, Jonathan; Vadhan, Salil P. (Association of Computing Machinery, 2014)
      We show new lower bounds on the sample complexity of (ε, δ)-differentially private algorithms that accurately answer large sets of counting queries. A counting query on a database D ∈ ({0, 1}d)n has the form "What fraction ...
    • New Separations in the Complexity of Differential Privacy 

      Bun, Mark Mar (2016-08-03)
      In this thesis, we study when algorithmic tasks can be performed on sensitive data while protecting the privacy of individuals whose information is collected. We focus on the notion of differential privacy, which gives a ...
    • Separating Computational and Statistical Differential Privacy in the Client-Server Model 

      Bun, Mark Mar; Chen, Yi-Hsiu; Vadhan, Salil P. (2016)
      Differential privacy is a mathematical definition of privacy for statistical data analysis. It guarantees that any (possibly adversarial) data analyst is unable to learn too much information that is specific to an individual. ...