Privately Connecting Mobility to Infectious Diseases via Applied\n Cryptography

Abstract

Recent work has shown that cell phone mobility data has the unique potential\nto create accurate models for human mobility and consequently the spread of\ninfected diseases. While prior studies have exclusively relied on a mobile\nnetwork operator's subscribers' aggregated data in modelling disease dynamics,\nit may be preferable to contemplate aggregated mobility data of infected\nindividuals only. Clearly, naively linking mobile phone data with health\nrecords would violate privacy by either allowing to track mobility patterns of\ninfected individuals, leak information on who is infected, or both. This work\naims to develop a solution that reports the aggregated mobile phone location\ndata of infected individuals while still maintaining compliance with privacy\nexpectations. To achieve privacy, we use homomorphic encryption, validation\ntechniques derived from zero-knowledge proofs, and differential privacy. Our\nprotocol's open-source implementation can process eight million subscribers in\n70 minutes.\n