Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …

With the rapid development of the information technology, the number of devices in the
Internet of Things (IoT) is increasing explosively, which makes device identification a great …

This paper presents channel-aware adversarial attacks against deep learning-based
wireless signal classifiers. There is a transmitter that transmits signals with different …

The spoofing attack is critical to bypass physical-layer signal authentication. This paper
presents a deep learning-based spoofing attack to generate synthetic wireless signals that …

Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …

Although deep learning technologies have been widely exploited in many fields, they are
vulnerable to adversarial attacks by adding small perturbations to legitimate inputs to fool …

Adversarial attacks represent a substantial threat to the security and reliability of machine
learning models employed in wireless sensor networks (WSNs). This study tries to solve this …

Network slicing manages network resources as virtual resource blocks (RBs) for the 5G
Radio Access Network (RAN). Each communication request comes with quality of …

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 …

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 …