  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 paper, I
investigated 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. I 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. I provide suggestions on metric
selection, interpretation, and visualization, and illustrate the work flow
using a case study on Alzheimer's disease.
