Machine learning-based physical layer security: techniques, open challenges, and applications

AK Kamboj, P Jindal, P Verma - Wireless Networks, 2021 - Springer
Wireless physical layer security (WPLS) is a powerful technology for current and emerging
mobile networks. Physical layer authentication (PLA), antenna selection (AS), and relay …

Physical layer spoofing attack detection in MmWave massive MIMO 5G networks

W Li, N Wang, L Jiao, K Zeng - IEEE Access, 2021 - ieeexplore.ieee.org
Identity spoofing attacks pose one of the most serious threats to wireless networks, where
the attacker can masquerade as legitimate users by modifying its own identity. Channel …

Intelligent cyber-security system for iot-aided drones using voting classifier

R Majeed, NA Abdullah, M Faheem Mushtaq, M Umer… - Electronics, 2021 - mdpi.com
Developments in drones have opened new trends and opportunities in different fields,
particularly in small drones. Drones provide interlocation services for navigation, and this …

Blind authentication at the physical layer under time-varying fading channels

N Xie, S Zhang - IEEE Journal on Selected Areas in …, 2018 - ieeexplore.ieee.org
Authentication is a key requirement for secure communications in modern wireless systems.
Compared with the conventional authentication at the upper layer using a cryptographic tool …

Physical layer authentication for 5G communications: Opportunities and road ahead

N Wang, W Li, P Wang, A Alipour-Fanid, L Jiao… - IEEE …, 2020 - ieeexplore.ieee.org
Resorting to the exploitation of physical attributes, physical-layer authentication (PLA) is a
promising technology to supplement and enhance current cryptography-based security …

Towards learning-automation IoT attack detection through reinforcement learning

T Gu, A Abhishek, H Fu, H Zhang… - 2020 IEEE 21st …, 2020 - ieeexplore.ieee.org
As a massive number of the Internet of Things (IoT) devices are deployed, the security and
privacy issues in IoT arouse more and more attention. The IoT attacks are causing …

Spatio-temporal network traffic estimation and anomaly detection based on convolutional neural network in vehicular ad-hoc networks

L Nie, Y Li, X Kong - IEEE Access, 2018 - ieeexplore.ieee.org
Over the last decade, vehicular ad-hoc networks (VANETs) have received a greater attention
in academia and industry due to their influence in intelligent transportation systems …

Physical layer security: Detection of active eavesdropping attacks by support vector machines

TM Hoang, TQ Duong, HD Tuan, S Lambotharan… - IEEE …, 2021 - ieeexplore.ieee.org
This article presents a framework for converting wireless signals into structured datasets,
which can be fed into machine learning algorithms for the detection of active eavesdropping …

A learning approach for physical layer authentication using adaptive neural network

X Qiu, J Dai, M Hayes - IEEE Access, 2020 - ieeexplore.ieee.org
In communications, innovative paradigm shifts have emerged in integrating various devices
into the network to provide advanced and intelligent services. However, various security …

On physical-layer authentication via online transfer learning

Y Chen, PH Ho, H Wen, SY Chang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
This article introduces a novel physical-layer (PHY-layer) authentication scheme, called
transfer learning-based PHY-layer authentication (TL-PHA), aiming to achieve fast online …