[HTML][HTML] Deepfakes: current and future trends
ÁF Gambín, A Yazidi, A Vasilakos, H Haugerud… - Artificial Intelligence …, 2024 - Springer
Abstract Advances in Deep Learning (DL), Big Data and image processing have facilitated
online disinformation spreading through Deepfakes. This entails severe threats including …
online disinformation spreading through Deepfakes. This entails severe threats including …
A systematic overview of the machine learning methods for mobile malware detection
Y Kim, JJ Lee, MH Go, HY Kang… - Security and …, 2022 - Wiley Online Library
With the deployment of the 5G cellular system, the upsurge of diverse mobile applications
and devices has increased the potential challenges and threats posed to users. Industry and …
and devices has increased the potential challenges and threats posed to users. Industry and …
Federated learning for 5G base station traffic forecasting
Cellular traffic prediction is of great importance on the path of enabling 5G mobile networks
to perform intelligent and efficient infrastructure planning and management. However …
to perform intelligent and efficient infrastructure planning and management. However …
Toward 6G security: technology trends, threats, and solutions
Toward 6G, we are witnessing various technology trends including network openness and
open source SW-based mobile communication systems, network AI, privacy protection …
open source SW-based mobile communication systems, network AI, privacy protection …
Sustainable marine ecosystems: Deep learning for water quality assessment and forecasting
An appropriate management of the available resources within oceans and coastal regions is
vital to guarantee their sustainable development and preservation, where water quality is a …
vital to guarantee their sustainable development and preservation, where water quality is a …
A general approach for traffic classification in wireless networks using deep learning
Traffic Classification (TC) systems allow inferring the application that is generating the traffic
being analyzed. State-of-the-art TC algorithms are based on Deep Learning (DL) and have …
being analyzed. State-of-the-art TC algorithms are based on Deep Learning (DL) and have …
Identify what you are doing: Smartphone apps fingerprinting on cellular network traffic
L Zhai, Z Qiao, Z Wang, D Wei - 2021 IEEE Symposium on …, 2021 - ieeexplore.ieee.org
Apps installed on smartphones may reveal users' privacy, which is often under malicious
attacks. Most privacy attacks are based on network layer traffic. However, the encryption …
attacks. Most privacy attacks are based on network layer traffic. However, the encryption …
On enhancing network slicing Life-Cycle through an AI-native orchestration architecture
Legacy experimental network infrastructures can still host innovative services through novel
network slicing orchestration architectures. Network slicing orchestration architectures …
network slicing orchestration architectures. Network slicing orchestration architectures …
INSAR deformation time series classification using a convolutional neural network
SM Mirmazloumi, ÁF Gambin… - … Archives of the …, 2022 - isprs-archives.copernicus.org
Temporal analysis of deformations Time Series (TS) provides detailed information of various
natural and humanmade displacements. Interferometric Synthetic Aperture Radar (InSAR) …
natural and humanmade displacements. Interferometric Synthetic Aperture Radar (InSAR) …
Locality sensitive hashing for network traffic fingerprinting
N Mashnoor, J Thom, A Rouf… - 2023 IEEE 29th …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) introduced new complexities and challenges to computer
networks. Due to their simple nature, these devices are more vulnerable to cyber-attacks …
networks. Due to their simple nature, these devices are more vulnerable to cyber-attacks …