Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures
Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …
computer vision, natural language processing, and speech recognition by its strong …
Game theory for anti-jamming strategy in multichannel slow fading IoT networks
The open nature of the wireless communication medium renders it vulnerable to jamming
attacks by malicious users. To detect their presence and to avoid such attacks, several …
attacks by malicious users. To detect their presence and to avoid such attacks, several …
A multiple stage deep learning model for NID in MANETs
A MANET is an entirely devoid-of-infrastructure network. This network is made up of nodes
that randomly move around. Since MANET has no central supervision, it can be formed …
that randomly move around. Since MANET has no central supervision, it can be formed …
Cognitive radio jamming attack detection using an autoencoder for CRIoT network
V Nallarasan, K Kottursamy - Wireless Personal Communications, 2022 - Springer
IoT network-connected devices are increasing day by day. It is impossible to allocate a
spectrum for all IoT devices. This spectrum scarcity can be solved by cognitive radio-based …
spectrum for all IoT devices. This spectrum scarcity can be solved by cognitive radio-based …
[HTML][HTML] A survey on cognitive radio network attack mitigation using machine learning and blockchain
IE Ezhilarasi, JC Clement, JM Arul - EURASIP Journal on Wireless …, 2023 - Springer
Cognitive radio network is a promising technology to enhance the spectrum utilization and to
resolve the spectrum scarcity issues. But the malicious users play havoc with the network …
resolve the spectrum scarcity issues. But the malicious users play havoc with the network …
A transfer games actor–critic learning framework for anti-jamming in multi-channel cognitive radio networks
A cognitive radio network (CRN) is a novel solution that promises to solve the spectrum
scarcity problem and enhance spectrum utilization. However, unsecured CRN can easily be …
scarcity problem and enhance spectrum utilization. However, unsecured CRN can easily be …
Intelligent Anti-jamming based on Deep Reinforcement Learning and Transfer Learning
One of the security issues in a wireless network is jamming attacks, where the jammer
causes congestion and significant decrement in the network throughput by obstructing …
causes congestion and significant decrement in the network throughput by obstructing …
Machine learning-based jamming attack classification and effective defense technique
The fourth industrial revolution has resulted in the intelligent Internet of Things being widely
used for home networking applications and smart infrastructure. Consequently, wireless …
used for home networking applications and smart infrastructure. Consequently, wireless …
Folpetti: A novel multi-armed bandit smart attack for wireless networks
Channel hopping provides a defense mechanism against jamming attacks in large scale
Internet of Things (IoT) networks. However, a sufficiently powerful attacker may be able to …
Internet of Things (IoT) networks. However, a sufficiently powerful attacker may be able to …
Dynamic Spectrum Anti-Jamming Access With Fast Convergence: A Labeled Deep Reinforcement Learning Approach
Y Li, Y Xu, G Li, Y Gong, X Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The primary objective of anti-jamming techniques is to ensure that the transmitted data
arrives at the intended receiver without being disturbed or jammed with by any jamming …
arrives at the intended receiver without being disturbed or jammed with by any jamming …