Performance characterization of deep learning models for breathing-based authentication on resource-constrained devices

• Main Authors: CHAUHAN, Jagmohan, RAJASEGARAN, Jathusan, SENEVIRATNE, Surang, MISRA, Archan, SENEVIRATNE, Aruan, LEE, Youngki
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Authentication; Breathing Gestures; GMM; IoT; LSTM; MLP; SVM; Security; Wearables; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4255; https://ink.library.smu.edu.sg/context/sis_research/article/5258/viewcontent/IMWUT_RNNBreathing_afv.pdf
• Institution: Singapore Management University

Providing secure access to smart devices such as mobiles, wearables and various other IoT devices is becoming increasinglyimportant, especially as these devices store a range of sensitive personal information. Breathing acoustics-based authentication offers a highly usable and possibly a secondary a...