56 citations · 483 across the 53 of their papers we have counts for
7 papers · 1 filter
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…
On the Impact of the Hardware Warm-Up Time on Deep Learning-Based RF Fingerprinting
Abdurrahman Elmaghbub, Vincent Immler, Bechir Hamdaoui
Deep learning-based RF fingerprinting offers great potential for improving the security robustness of various emerging wireless networks. Although much progress has been done in en…
Deep Learning-Enabled Zero-Touch Device Identification: Mitigating the Impact of Channel Variability Through MIMO Diversity
Bechir Hamdaoui, Nora Basha, Kathiravetpillai Sivanesan
Deep learning-enabled device fingerprinting has proven efficient in enabling automated identification and authentication of transmitting devices. It does so by leveraging the trans…
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…
A Survey on AI/ML-Driven Intrusion and Misbehavior Detection in Networked Autonomous Systems: Techniques, Challenges and Opportunities
Opeyemi Ajibuwa, Bechir Hamdaoui, Attila A. Yavuz
AI/ML-based intrusion detection systems (IDSs) and misbehavior detection systems (MDSs) have shown great potential in identifying anomalies in the network traffic of networked auto…