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

As modern communication technology advances apace, the digital communication signals
identification plays an important role in cognitive radio networks, the communication …

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 …

Predicting students' performance is very important in matters related to higher education as
well as with regard to deep learning and its relationship to educational data. Prediction of …

Deep learning has great potential for automatic modulation classification (AMC). However,
its performance largely hinges upon the availability of sufficient high-quality labeled data. In …

Deep learning-based automatic modulation classification (AMC) models are susceptible to
adversarial attacks. Such attacks inject specifically crafted wireless interference into …

Advances in adversarial attack and defense technologies will enhance the reliability of deep
learning (DL) systems spirally. Most existing adversarial attack methods make overly ideal …

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 …

Adversarial examples refer to the malicious inputs that can mislead deep neural networks
(DNNs) to falsely classify them. In practice, some adversarial examples are transferable and …