| Popis: |
The coronavirus disease (COVID-19) pandemic has caused social and economic upheaval around the world. Contact tracing is a proven effective way that health authorities may contain the spread of COVID-19, but is challenging for airborne disease. In this paper, we propose LTESafe, a cellular-assisted privacy-preserving COVID-19 contact tracing system. LTESafe leverages a deep neural network based feature extractor to map the cellular CSI to a high-dimensional feature space, within which the Euclidean distance between points indicates the proximity of devices. By doing so, we preserve user privacy by hiding the physical locations of smartphones and at the same time achieve high accuracy. Our preliminary experimental results demonstrate that LTESafe achieves an overall accuracy of 92.79% in determining whether two devices are within six feet proximity or not, and only misses 1.35% of close contacts. |
