These researchers will address cybersecurity problems related to protected health information (PHI) on mobile health devices. Drawing upon theory from statistics, machine learning, principal-agent modeling, and mean-field game models, they will design scalable machine-learning methods to identify duplicate or stolen/counterfeit PHI in order to secure the use of PHI for identification and authentication of patients, and they will study the problem of incentivizing investments and software updates for cybersecurity of PHI on mobile health devices.
