Y Liu, J Wang, J Li, S Niu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a variety of emerging services and applications. However, the presence of rogue IoT devices …
L Xie, L Peng, J Zhang, A Hu - Security and Safety, 2024 - sands.edpsciences.org
Radio frequency fingerprint (RFF) identification is a promising technique for identifying Internet of Things (IoT) devices. This paper presents a comprehensive survey on RFF …
Recent advancements in radio frequency machine learning (RFML) have demonstrated the use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks. Yet …
JM McGinthy, LJ Wong… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Trust is a prominent concern with the continued expansion of the Internet of Things (IoT). As new devices enter the market, device security must be a design pillar. In order to trust these …
We design a network to classify individual wireless devices based on their radio frequency (RF) fingerprints imparted on transmitted signals. The network combines a stack of dilated …
The Internet of Things (IoT) is here and has permeated every aspect of our lives. A disturbing fact is that the majority of all IoT devices employ weak or no encryption at all. This coupled …
Internet of Things (IoT) deployments are expected to reach 75.4 billion by 2025. Roughly 70% of all IoT devices employ weak or no encryption, thus putting them and their connected …
Wireless communications has greatly benefited in recent years from advances in machine learning. A new subfield, commonly termed Radio Frequency Machine Learning (RFML) …
Transfer learning has allowed for more widespread adaptation and expanded use of deep learning models in fields such as computer vision and speech recognition. The radio …