A Genetic Attack Against Machine Learning Classifiers to Steal Biometric Actigraphy Profiles from Health Related Sensor Data.

In this work, we propose the use of a genetic-algorithm-based attack against machine learning classifiers with the aim of 'stealing' users' biometric actigraphy profiles from health related sensor data. The target classification model uses daily actigraphy patterns for user identification. The biome...

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Bibliographic Details

Published in:	Journal of Medical Systems Vol. 44; no. 10
Main Authors:	Garcia-Ceja, Enrique, Morin, Brice, Aguilar-Rivera, Anton, Riegler, Michael Alexander
Format:	equations & formulas research tables/charts Journal Article
Published:	Springer Nature Oct2020
Online Access:	View this record in EBSCOhost