Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
[HTML][HTML] Deep reinforcement learning in recommender systems: A survey and new perspectives
In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …
research and several fruitful results in recent years, this survey aims to provide a timely and …
A survey of deep reinforcement learning in recommender systems: A systematic review and future directions
In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …
research and several fruitful results in recent years, this survey aims to provide a timely and …
Adversarial machine learning for 5G communications security
Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …
spectrum and support better understanding of spectrum resources and their efficient …
Survey on physical layer security for 5G wireless networks
Physical layer security is a promising approach that can benefit traditional encryption
methods. The idea of physical layer security is to take advantage of the propagation …
methods. The idea of physical layer security is to take advantage of the propagation …
Adversarial machine learning for flooding attacks on 5G radio access network slicing
Y Shi, YE Sagduyu - 2021 IEEE International Conference on …, 2021 - ieeexplore.ieee.org
Network slicing manages network resources as virtual resource blocks (RBs) for the 5G
Radio Access Network (RAN). Each communication request comes with quality of …
Radio Access Network (RAN). Each communication request comes with quality of …
Adversarial attacks on deep learning based mmWave beam prediction in 5G and beyond
Deep learning provides powerful means to learn from spectrum data and solve complex
tasks in 5G and beyond such as beam selection for initial access (IA) in mmWave …
tasks in 5G and beyond such as beam selection for initial access (IA) in mmWave …
How to Attack and Defend NextG Radio Access Network Slicing with Reinforcement Learning
In this paper, reinforcement learning (RL) for network slicing is considered in NextG radio
access networks, where the base station (gNodeB) allocates resource blocks (RBs) to the …
access networks, where the base station (gNodeB) allocates resource blocks (RBs) to the …
A review of techniques and policies on cybersecurity using artificial intelligence and reinforcement learning algorithms
Cybersecurity is a critical process that safeguards networks, systems, and applications
against cyber-attacks, wherein digital information is targeted for unauthorized access …
against cyber-attacks, wherein digital information is targeted for unauthorized access …