Rigorous Metrics for Emerging Data Privacy Challenges

Abstract

The modern day technological economy hinges on the collection, analysis and usage of personal data, which is analyzed to drive decisions and make profits. From a social perspective, however, these data driven decision systems pose severe and unique privacy challenges that current privacy solutions are incapable of addressing adequately. This proposal addresses three such major privacy challenges. First, we consider preserving the privacy of location trajectories in the presence of prior information. Second, we consider datadeletion from machine learning models learned via empirical risk minimization. Finally, we consider auditing machine learning models to determine if a specific persons data was used to build it. All these privacy challenges are addressed by proposing unique privacy metrics with rigorous goals.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 29, 2020
Source ID
N000142012334

Entities

People

  • Kamalika Chaudhuri

Organizations

  • Office of Naval Research
  • United States Navy
  • University of California, San Diego

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Economics

Technology Areas

  • AI & ML