Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
| Country | : |
Singapore |
| Department | : | Singapore Management University |
| Project Title | : | Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks |
| Researcher | : | LEE, Youngki , HU, Yining , SENEVIRATNE, Aruna , MISRA, Archan , SENEVIRATNE, Suranga , CHAUHAN, Jagmohan |
| Keyword | : | Digital Communications and Networking , OS and Networks |
| Publisher | : | Institutional Knowledge at Singapore Management University |
| Year End | : | 2018 |
| Identifier | : | https://ink.library.smu.edu.sg/sis_research/4054 , https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=5057&context=sis_research |
| Source | : | Research Collection School Of Computing and Information Systems |
| Abstract / Description | : |
Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics. |
References
LEE, Youngki and others / et al. (2018). Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks. Singapore: Singapore Management University.
LEE, Youngki and others / et al. 2018. "Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks". Singapore: Singapore Management University.
LEE, Youngki and others / et al. "Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks." Singapore: Singapore Management University, 2018. Print.
LEE, Youngki and others / et al. Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks. Singapore: Singapore Management University; 2018.