A collaborative V2X data correction method for road safety

L Zhao, H Chai, Y Han, K Yu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Driving safety is one of the most important points to concern on the road. Vehicles constantly
generate messages under vehicle-to-everything (V2X) assisted driving. Especially, in dense …

A survey on device fingerprinting approach for resource-constraint IoT devices: comparative study and research challenges

RR Chowdhury, PE Abas - Internet of Things, 2022 - Elsevier
Modernization and technological advancement have made smart and convenient living
environments, including smart houses and smart cities, possible, by combining the Internet …

[HTML][HTML] Adversarial attacks and defenses for digital communication signals identification

Q Tian, S Zhang, S Mao, Y Lin - Digital Communications and Networks, 2022 - Elsevier
As modern communication technology advances apace, the digital communication signals
identification plays an important role in cognitive radio networks, the communication …

Overcoming data limitations: a few-shot specific emitter identification method using self-supervised learning and adversarial augmentation

C Liu, X Fu, Y Wang, L Guo, Y Liu, Y Lin… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Specific emitter identification (SEI) based on radio frequency fingerprinting (RFF) is a
physical layer authentication method in the field of wireless network security. RFFs are …

Few-shot specific emitter identification via deep metric ensemble learning

Y Wang, G Gui, Y Lin, HC Wu, C Yuen… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Specific emitter identification (SEI) is a highly potential technology for physical-layer
authentication that is one of the most critical supplements for the upper-layer authentication …

NAS-AMR: Neural architecture search-based automatic modulation recognition for integrated sensing and communication systems

X Zhang, H Zhao, H Zhu, B Adebisi… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) technique plays an important role in the
identification of modulation types of unknown signal of integrated sensing and …

Semi-supervised specific emitter identification method using metric-adversarial training

X Fu, Y Peng, Y Liu, Y Lin, G Gui… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Specific emitter identification (SEI) plays an increasingly crucial and potential role in both
military and civilian scenarios. It refers to a process to discriminate individual emitters from …

GLR-SEI: green and low resource specific emitter identification based on complex networks and fisher pruning

Y Lin, H Zha, Y Tu, S Zhang, W Yan… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Better neural networks, more powerful computer hardware and signal Big Data make deep
learning increasingly important in Specific Emitter Identification (SEI). However, its …

Toward next-generation signal intelligence: A hybrid knowledge and data-driven deep learning framework for radio signal classification

S Zheng, X Zhou, L Zhang, P Qi, K Qiu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Automatic modulation classification (AMC) can generally be divided into knowledge-based
methods and data-driven methods. In this paper, we explore combining the knowledge …

GPU-free specific emitter identification using signal feature embedded broad learning

Y Zhang, Y Peng, J Sun, G Gui, Y Lin… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Emerging wireless networks may suffer severe security threats due to the ubiquitous access
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …