@InProceedings{10.1007/978-981-16-7618-5_46,
author="Makwana, Rikesh
and Shaikh, Talal",
editor="Ullah, Abrar
and Anwar, Sajid
and Rocha, {\'A}lvaro
and Gill, Steve",
title="Touchless Biometric User Authentication Using ESP32 WiFi Module",
booktitle="Proceedings of International Conference on Information Technology and Applications",
year="2022",
publisher="Springer Nature Singapore",
address="Singapore",
pages="527--537",
abstract="Due to the ubiquitous nature of WiFi, the use of WiFi signals for Biometric User Authentication (BUA) is ongoing research which has previously focused on using multi-antenna commercial off-the-shelf (COTS) devices such as Intel 5300 or Atheros 9390. However, due to high cost and limited availability, COTS devices are restricted to small scale deployment. To overcome this issue, researchers propose using Espressif ESP32, an inexpensive single antenna microcontroller equipped with WiFi and Bluetooth modules capable of capturing detailed WiFi Channel State Information (CSI). This paper explores and extends the application of ESP32 by proposing a model for device-less and touch-less BUA systems using a simple client--server architecture. The system identifies users as they perform day-to-day activities by recognizing behavioural and physiological characteristics using LSTM---a deep learning approach. Furthermore, the paper describes the Python tool developed for parsing and filtering WiFi CSI data.",
isbn="978-981-16-7618-5"
}