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Full-Text Articles in Physical Sciences and Mathematics
Tunable Magnetic Anisotropy And Dzyaloshinskii-Moriya Interaction In An Ultrathin Van Der Waals Fe3gete2/In2se3 Heterostructure, Dong Chen, Wei Sun, Hang Li, Jian Li Wang, Yuanxu Wang
Tunable Magnetic Anisotropy And Dzyaloshinskii-Moriya Interaction In An Ultrathin Van Der Waals Fe3gete2/In2se3 Heterostructure, Dong Chen, Wei Sun, Hang Li, Jian Li Wang, Yuanxu Wang
Australian Institute for Innovative Materials - Papers
© Copyright © 2020 Chen, Sun, Li, Wang and Wang. The promise of future spintronic devices with nanoscale dimension, high-density, and low-energy consumption motivates the search for van der Waals heterostructure that stabilize topologically protected whirling spin textures such as magnetic skyrmions and domain walls. To translate these compelling features into practical devices, a key challenge lies in achieving effective manipulation of the magnetic anisotropy energy and the Dzyaloshinskii-Moriya (DM) interaction, the two key parameters that determine skyrmions. Through the first-principles calculation, we demonstrate that the polarization-induced broken inversion symmetry in the two-dimensional Fe3GeTe2/In2Se3 multiferroic heterostructure does cause an interfacial …
Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu
Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu
Electrical & Computer Engineering Faculty Publications
This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …