[HTML][HTML] Open RAN security: Challenges and opportunities
Abstract Open RAN (ORAN, O-RAN) represents a novel industry-level standard for RAN
(Radio Access Network), which defines interfaces that support inter-operation between …
(Radio Access Network), which defines interfaces that support inter-operation between …
Machine learning for wireless communications in the Internet of Things: A comprehensive survey
Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …
wireless communications than ever before. For this reason, techniques such as spectrum …
Machine learning for the detection and identification of Internet of Things devices: A survey
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 …
variety of emerging services and applications. However, the presence of rogue IoT devices …
DNNs as applied to electromagnetics, antennas, and propagation—A review
A review of the most recent advances in deep learning (DL) as applied to electromagnetics
(EM), antennas, and propagation is provided. It is aimed at giving the interested readers and …
(EM), antennas, and propagation is provided. It is aimed at giving the interested readers and …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
RFAL: Adversarial learning for RF transmitter identification and classification
D Roy, T Mukherjee, M Chatterjee… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Recent advances in wireless technologies have led to several autonomous deployments of
such networks. As nodes across distributed networks must co-exist, it is important that all …
such networks. As nodes across distributed networks must co-exist, it is important that all …
Few-shot specific emitter identification using asymmetric masked auto-encoder
Specific emitter identification (SEI) based on radio frequency fingerprint (RFF) characteristics
can be used to identify different transmitters, and the deep learning (DL)-based SEI methods …
can be used to identify different transmitters, and the deep learning (DL)-based SEI methods …
A generalizable model-and-data driven approach for open-set RFF authentication
Radio-frequency fingerprints (RFFs) are promising solutions for realizing low-cost physical
layer authentication. Machine learning-based methods have been proposed for RFF …
layer authentication. Machine learning-based methods have been proposed for RFF …
A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …
efforts focused on machine learning (ML) based performance improvement of wireless …
Domain generalization in machine learning models for wireless communications: Concepts, state-of-the-art, and open issues
Data-driven machine learning (ML) is promoted as one potential technology to be used in
next-generation wireless systems. This led to a large body of research work that applies ML …
next-generation wireless systems. This led to a large body of research work that applies ML …