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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Detalles Bibliográficos
Publicado en:Journal of Medical Systems Vol. 44; no. 10
Autores principales: Garcia-Ceja, Enrique, Morin, Brice, Aguilar-Rivera, Anton, Riegler, Michael Alexander
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Oct2020
Acceso en línea:Ver este registro en EBSCOhost