2020/03/29 by Didem Demirağ, Demirag, Didem, Erman Ayday +1
Computer Science · Social Sciences · #COVID-19 Digital Contact Tracing #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Privacy, Security, and Data Protection #Privacy-Preserving Technologies in Data
paper · pdf · doi:10.48550/arxiv.2003.13073
openalex publication_date 2020/03/29 · openalex created_date 2021/08/16 · openalex updated_date 2026/07/28
Today, tracking and controlling the spread of a virus is a crucial need for\nalmost all countries. Doing this early would save millions of lives and help\ncountries keep a stable economy. The easiest way to control the spread of a\nvirus is to immediately inform the individuals who recently had close contact\nwith the diagnosed patients. However, to achieve this, a centralized authority\n(e.g., a health authority) needs detailed location information from both\nhealthy individuals and diagnosed patients. Thus, such an approach, although\nbeneficial to control the spread of a virus, results in serious privacy\nconcerns, and hence privacy-preserving solutions are required to solve this\nproblem. Previous works on this topic either (i) compromise privacy (especially\nprivacy of diagnosed patients) to have better efficiency or (ii) provide\nunscalable solutions. In this work, we propose a technique based on private set\nintersection between physical contact histories of individuals (that are\nrecorded using smart phones) and a centralized database (run by a health\nauthority) that keeps the identities of the positive diagnosed patients for the\ndisease. Proposed solution protects the location privacy of both healthy\nindividuals and diagnosed patients and it guarantees that the identities of the\ndiagnosed patients remain hidden from other individuals. Notably, proposed\nscheme allows individuals to receive warning messages indicating their previous\ncontacts with a positive diagnosed patient. Such warning messages will help\nthem realize the risk and isolate themselves from other people. We make sure\nthat the warning messages are only observed by the corresponding individuals\nand not by the health authority. We also implement the proposed scheme and show\nits efficiency and scalability via simulations.\n