@inproceedings{36437650f9f94e6893000520737c19e7,
title = "Effects of Pressure on Acoustic Hand Biometric Authentication",
abstract = "Growing concerns regarding digital security have prioritized effective and secure mobile device authentication. Current methods utilize fingerprint and facial recognition, raising privacy concerns. In contrast with traditional biometric authen-Tication systems, our Acoustic Hand Biometric Authentication System relies on unique hand geometries and the acoustic distortion caused by hand grips of varying pressure. We utilized MATLAB to create a machine learning model that classifies users based on recordings of distorted chirp sounds. Our research demonstrates the viability of a pressure sensitive password that differentiates between a series of strong and normal strength grips in order to authenticate the user.",
author = "Angela Claveria and Raina Maldonado and Akshay Mistry and Yingying Chen and Kevin Song and Srinidhi Venkatesh and Siddharth Parikh and Yilin Yang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE MIT Undergraduate Research Technology Conference, URTC 2021 ; Conference date: 08-10-2021 Through 10-10-2021",
year = "2021",
doi = "10.1109/URTC54388.2021.9701647",
language = "English (US)",
series = "2021 IEEE MIT Undergraduate Research Technology Conference, URTC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE MIT Undergraduate Research Technology Conference, URTC 2021",
address = "United States",
}