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Covid-19 is primarily spread through contact with the virus which may surviveon surfaces with lifespan of more than hours. To curb its spread, it is henceof vital importance to detect and quarantine those who have been in contactwith the virus for sustained period of time, the so-called close contacts. Inthis work, we study, for the first time, automatic contact detection when thevirus has a lifespan. Leveraging upon the ubiquity of WiFi signals, we proposea novel, private, and fully distributed WiFi-based approach called vContact.Users installing an app continuously scan WiFi and store its hashed IDs. Givena confirmed case, the signals of the major places he/she visited are thenuploaded to a server and matched with the stored signals of users to detectcontact. vContact is not based on phone pairing, and no information of anyother users is stored locally. The confirmed case does not need to haveinstalled the app for it to work properly. As WiFi data are sampledsporadically, we propose efficient signal processing approaches and similaritymetric to align and match signals of any time. We conduct extensive indoor andoutdoor experiments to evaluate the performance of vContact. Our resultsdemonstrate that vContact is efficient and robust for contact detection. Theprecision and recall of contact detection are high (in the range of 50-90%) forclose contact proximity (2m). Its performance is robust with respect to signallengths (AP numbers) and phone heterogeneity. By implementing vContact as anapp, we present a case study to demonstrate the validity of our design innotifying its users their exposure to virus with lifespan.

vContact: Private WiFi-based Contact Tracing with Virus Lifespan