MRFE: A Deep Learning Based Multidimensional Radio Frequency Fingerprinting Enhancement Approach for IoT Device Identification

Q Lu, Z Yang, H Zhang, F Chen… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Nowadays, wireless networks have been widely deployed in our daily lives, providing
people with convenient Internet of Things services in healthcare, smart cities, transportation …

Learning-Based RF Fingerprinting for Device Identification using Amplitude-Phase Spectrograms

A Mohammad, M Ashraf, M Valkama… - 2023 IEEE 98th …, 2023 - ieeexplore.ieee.org
Radio frequency fingerprinting (RFF), a technique based on specific transmitter hardware
impairments, has emerged as an effective solution for wireless device identification. In this …

Deep learning-powered radio frequency fingerprint identification: Methodology and case study

G Shen, J Zhang, A Marshall - IEEE Communications Magazine, 2023 - ieeexplore.ieee.org
Radio frequency fingerprint identification (RFFI) is an authentication technique that identifies
wireless devices by analyzing the characteristics of the received physical layer signals. In …

A Low-Latency Approach for RFF Identification in Open-Set Scenarios

B Zhang, T Zhang, Y Ma, Z Xi, C He, Y Wang, Z Lv - Electronics, 2024 - mdpi.com
Radio frequency fingerprint (RFF) identification represents a promising technique for
lightweight device authentication. However, current research on RFF primarily focuses on …

Active eavesdropping detection: a novel physical layer security in wireless IoT

M Li, Z Dou - EURASIP Journal on Advances in Signal Processing, 2023 - Springer
Considering the variety of Internet of Things (IoT) device types and access methods, it
remains necessary to address the security challenges we currently encounter. Physical layer …

Zero-bias deep learning for accurate identification of Internet-of-Things (IoT) devices

Y Liu, J Wang, J Li, H Song, T Yang… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) provides applications and services that would otherwise not be
possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats …

Eliminating Rogue Access Point Attacks in IoT: A Deep Learning Approach With Physical-Layer Feature Purification and Device Identification

Z Yang, Q Lu, H Zhang, F Chen… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Wi-Fi plays an essential role in various emerging Internet of Things (IoT) services and
applications in smart cities and communities, such as IoT access, data transmission, and …

Exploiting CSI-MIMO for accurate and efficient device identification

LN Kandel, Z Zhang, S Yu - 2019 IEEE Global Communications …, 2019 - ieeexplore.ieee.org
Due to the inherent broadcast nature of the wireless medium, Wireless Local Area Networks
(WLANs) are targets of a variety of malicious attacks, for example, MAC identity spoofing …

Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection with Deep Learning

YE Sagduyu, T Erpek - MILCOM 2023-2023 IEEE Military …, 2023 - ieeexplore.ieee.org
Low-Power Wide-Area Network (LPWAN) technologies, such as LoRa, have gained
significant attention for their ability to enable long-range, low-power communication for …

Machine-learning PUF-based detection of RF anomalies in a cluttered RF environment

J Lu, T Morehouse, J Yuan… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
With the emergence of software defined radio (SDR) where a computer program defines
transceivers' physical layer functions, waveforms can change dynamically. SDR benefits …