56 citations · 483 across the 53 of their papers we have counts for
5 papers · 1 filter
Uncovering the Portability Limitation of Deep Learning-Based Wireless Device Fingerprints
Bechir Hamdaoui, Abdurrahman Elmaghbub
Recent device fingerprinting approaches rely on deep learning to extract device-specific features solely from raw RF signals to identify, classify and authenticate wireless devices…
Tweak: Towards Portable Deep Learning Models for Domain-Agnostic LoRa Device Authentication
Jared Gaskin, Bechir Hamdaoui, Weng-Keen Wong
Deep learning based device fingerprinting has emerged as a key method of identifying and authenticating devices solely via their captured RF transmissions. Conventional approaches…
Deep-Learning-Based Device Fingerprinting for Increased LoRa-IoT Security: Sensitivity to Network Deployment Changes
Bechir Hamdaoui, Abdurrahman Elmaghbub
Deep-learning-based device fingerprinting has recently been recognized as a key enabler for automated network access authentication. Its robustness to impersonation attacks due to…
An Analysis of Complex-Valued CNNs for RF Data-Driven Wireless Device Classification
Jun Chen, Weng-Keen Wong, Bechir Hamdaoui +4
Recent deep neural network-based device classification studies show that complex-valued neural networks (CVNNs) yield higher classification accuracy than real-valued neural network…
Comprehensive RF Dataset Collection and Release: A Deep Learning-Based Device Fingerprinting Use Case
Abdurrahman Elmaghbub, Bechir Hamdaoui
Deep learning-based RF fingerprinting has recently been recognized as a potential solution for enabling newly emerging wireless network applications, such as spectrum access policy…