Evaluating the Strength of Genomic Privacy Metrics

Abstract

The genome is a unique identifier for human individuals. The genome also contains highly sensitive information, creating a high potential for misuse of genomic data (for example, genetic discrimination). In this article, we investigate how genomic privacy can be measured in scenarios where an adversary aims to infer a person’s genomic markers by constructing probability distributions on the values of genetic variations. We measured the strength of privacy metrics by requiring that metrics are monotonic with increasing adversary strength and uncovered serious problems with several existing metrics currently used to measure genomic privacy. We provide suggestions on metric selection, interpretation, and visualization and illustrate the work flow using case studies for three real-world diseases.