43 citations · 66 across the 12 of their papers we have counts for
9 papers
Domain-Adaptive Device Fingerprints for Network Access Authentication Through Multifractal Dimension Representation
Benjamin Johnson, Bechir Hamdaoui
RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a potential solution for automated network access authentication. Traditional approac…
EPS: Distinguishable IQ Data Representation for Domain-Adaptation Learning of Device Fingerprints
Abdurrahman Elmaghbub, Bechir Hamdaoui
Deep learning (DL)-based RF fingerprinting (RFFP) technology has emerged as a powerful physical-layer security mechanism, enabling device identification and authentication based on…
HiNoVa: A Novel Open-Set Detection Method for Automating RF Device Authentication
Luke Puppo, Weng-Keen Wong, Bechir Hamdaoui +1
New capabilities in wireless network security have been enabled by deep learning, which leverages patterns in radio frequency (RF) data to identify and authenticate devices. Open-s…
ADL-ID: Adversarial Disentanglement Learning for Wireless Device Fingerprinting Temporal Domain Adaptation
Abdurrahman Elmaghbub, Bechir Hamdaoui, Weng-Keen Wong
As the journey of 5G standardization is coming to an end, academia and industry have already begun to consider the sixth-generation (6G) wireless networks, with an aim to meet the…
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…