A survey of privacy vulnerabilities of mobile device sensors
The number of mobile devices, such as smartphones and smartwatches, is relentlessly
increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and …
increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and …
Quantifying privacy leakage in graph embedding
Graph embeddings have been proposed to map graph data to low dimensional space for
downstream processing (eg, node classification or link prediction). With the increasing …
downstream processing (eg, node classification or link prediction). With the increasing …
An adaptive batch size-based-CNN-LSTM framework for human activity recognition in uncontrolled environment
NA Choudhury, B Soni - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) is a process of identifying the daily living activities of an
individual using a set of sensors and appropriate learning algorithms. Most of the works on …
individual using a set of sensors and appropriate learning algorithms. Most of the works on …
[HTML][HTML] GaitPrivacyON: Privacy-preserving mobile gait biometrics using unsupervised learning
P Delgado-Santos, R Tolosana, R Guest… - Pattern Recognition …, 2022 - Elsevier
Numerous studies in the literature have already shown the potential of biometrics on mobile
devices for authentication purposes. However, it has been shown that, the learning …
devices for authentication purposes. However, it has been shown that, the learning …
Human activity recognition using wearable sensors based on image classification
S Zebhi - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Two-Dimensional Fast Fourier Transform (2-D FFT) and Wigner-Ville Transform (WVT) are
two popular transforms applied to find frequency and time-frequency representations …
two popular transforms applied to find frequency and time-frequency representations …
[HTML][HTML] Privacy-preserving human activity sensing: A survey
With the prevalence of various sensors and smart devices in people's daily lives, numerous
types of information are being sensed. While using such information provides critical and …
types of information are being sensed. While using such information provides critical and …
MixNN: protection of federated learning against inference attacks by mixing neural network layers
T Lebrun, A Boutet, J Aalmoes, A Baud - Proceedings of the 23rd ACM …, 2022 - dl.acm.org
Machine Learning (ML) has emerged as a core technology to provide learning models to
perform complex tasks. Boosted by Machine Learning as a Service (MLaaS), the number of …
perform complex tasks. Boosted by Machine Learning as a Service (MLaaS), the number of …
MixNN: Protection of federated learning against inference attacks by mixing neural network layers
A Boutet, T Lebrun, J Aalmoes, A Baud - arXiv preprint arXiv:2109.12550, 2021 - arxiv.org
Machine Learning (ML) has emerged as a core technology to provide learning models to
perform complex tasks. Boosted by Machine Learning as a Service (MLaaS), the number of …
perform complex tasks. Boosted by Machine Learning as a Service (MLaaS), the number of …
Gender-adversarial networks for face privacy preserving
Privacy concerns over face recognition systems have attracted extensive attention in various
fields. For gender privacy-preserving work, there are two key challenges: 1) privacy, ie …
fields. For gender privacy-preserving work, there are two key challenges: 1) privacy, ie …
An efficient 3D convolutional neural network with informative 3D volumes for human activity recognition using wearable sensors
S Zebhi - Multimedia Tools and Applications, 2024 - Springer
Abstract Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT)
are two popular transforms which can be used to find time‐frequency representations. By …
are two popular transforms which can be used to find time‐frequency representations. By …