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Advances in machine learning-driven cognitive radio for wireless networks: A survey
NA Khalek, DH Tashman… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The next frontier in wireless connectivity lies at the intersection of cognitive radio (CR)
technology and machine learning (ML), where intelligent networks can provide pervasive …
technology and machine learning (ML), where intelligent networks can provide pervasive …
Adversarial machine learning in wireless communications using RF data: A review
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Channel-aware adversarial attacks against deep learning-based wireless signal classifiers
This paper presents channel-aware adversarial attacks against deep learning-based
wireless signal classifiers. There is a transmitter that transmits signals with different …
wireless signal classifiers. There is a transmitter that transmits signals with different …
[HTML][HTML] A comprehensive study on IoT privacy and security challenges with focus on spectrum sharing in Next-Generation networks (5G/6G/beyond)
The emergence of the Internet of Things (IoT) has triggered a massive digital transformation
across numerous sectors. This transformation requires efficient wireless communication and …
across numerous sectors. This transformation requires efficient wireless communication and …
Membership inference attack and defense for wireless signal classifiers with deep learning
An over-the-air membership inference attack (MIA) is presented to leak private information
from a wireless signal classifier. Machine learning (ML) provides powerful means to classify …
from a wireless signal classifier. Machine learning (ML) provides powerful means to classify …
Adversarial attacks against deep learning based power control in wireless communications
We consider adversarial machine learning based attacks on power allocation where the
base station (BS) allocates its transmit power to multiple orthogonal subcarriers by using a …
base station (BS) allocates its transmit power to multiple orthogonal subcarriers by using a …
Jamming attacks on federated learning in wireless networks
Y Shi, YE Sagduyu - ar** their training data …
Adversarial Attacks Against Shared Knowledge Interpretation in Semantic Communications
Semantic communications (SEMCOM) is a novel communication model that exploits neural
networks or deep learning techniques to convey the semantics of the data and contextual …
networks or deep learning techniques to convey the semantics of the data and contextual …
Data-Driven Next-Generation Wireless Networking: Embracing AI for Performance and Security
New network architectures, such as the Internet of Things (IoT), 5G, and next-generation
(NextG) cellular systems, put forward emerging challenges to the design of future wireless …
(NextG) cellular systems, put forward emerging challenges to the design of future wireless …
Adversarial Machine Learning: A New Threat Paradigm for Next-generation Wireless Communications
The application of machine learning (ML) in the wireless domain, commonly referred to as
radio frequency machine learning (RFML), has grown strongly in recent years to solve …
radio frequency machine learning (RFML), has grown strongly in recent years to solve …