Privacy gaurantees for personal mobility data in humanitarian response.

Emily Aiken

Abstract: Personal mobility data from mobile phones and other sensors are increasingly used to informpolicymaking during pandemics, natural disasters, and other humanitarian crises. However, evenaggregated mobility traces can reveal private information about individual movements to potentiallymalicious actors. This paper develops and tests an approach for releasing private mobility data, whichprovides formal guarantees over the privacy of the underlying subjects. Specifically, we (1) introducean algorithm for constructing differentially private mobility matrices and derive privacy and accuracybounds on this algorithm; (2) use real-world data from mobile phone operators in Afghanistan andRwanda to show how this algorithm can enable the use of private mobility data in two high-stakespolicy decisions: pandemic response and the distribution of humanitarian aid; and (3) discuss practicaldecisions that need to be made when implementing this approach, such as how to optimally balanceprivacy and accuracy. Taken together, these results can help enable the responsible use of privatemobility data in humanitarian response.