Encrypted Classification for Prevention of Adversarial Perturbation and Individual Identification in Health-Monitoring-Reference-Cited by-同舟云学术

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Encrypted Classification for Prevention of Adversarial Perturbation and Individual Identification in Health-Monitoring

Published:2023-06-28 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
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Author:

Kawase Hiroaki¹,Meinhold Waiman¹,Zeagler Clint²,Miles Toni P³,Ueda Jun¹

Affiliation:

1. Georgia Institute of Technology,Woodruff School of Mechanical Engineering,Atlanta,Georgia,USA

2. Institute for People and Technology, Georgia Institute of Technology,Atlanta,Georgia,USA

3. Morehouse School of Medicine,Department of Community Health and Preventive Medicine,Atlanta,Georgia,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10196083/10196094/10196163.pdf?arnumber=10196163

Reference18 articles.

1. Person identification by using ar model for eeg signals;mohammadi;Proceeding of World Academy of Science Engineering and Technology,2006

2. The Identification of ECG Signals Using Wavelet Transform and WOA-PNN

3. A large electroencephalographic motor imagery dataset for electroen-cephalographic brain computer interfaces;kaya;Scientific Data,2018

4. An Effective and Computationally Efficient Approach for Anonymizing Large-Scale Physical Activity Data

5. Identifying Continuous Glucose Monitoring Data Using Machine Learning

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