Abstract
A large number of Bluetooth-based mobile apps have been developed recently to help tracing close contacts of contagious COVID-19 individuals. These apps make decisions based on whether two users are in close proximity (e.g., within 6 ft) according to the distance measured from the received signal strength (RSSI) of Bluetooth. This paper provides a detailed study of the current practice of RSSI-based distance measurements among contact tracing apps by analyzing various factors that can affect the RSSI value and how each app has responded to them. Our analysis shows that configurations for the signal transmission power (TxPower) and broadcasting intervals that affect RSSI vary significantly across different apps and a large portion of apps do not consider these affecting factors at all, or with quite limited tuning.
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Acknowledgement
This work was supported in part by the National Science Foundation (NSF) under Grant No. CNS 1618520, CNS 1834215, and CNS 2028547. Any opinions, findings, conclusions, and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
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Zhao, Q., Wen, H., Lin, Z., Xuan, D., Shroff, N. (2020). On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps. In: Park, N., Sun, K., Foresti, S., Butler, K., Saxena, N. (eds) Security and Privacy in Communication Networks. SecureComm 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 335. Springer, Cham. https://doi.org/10.1007/978-3-030-63086-7_4
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