Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …

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

There is significant enthusiasm for the employment of Deep Neural Networks (DNNs) for
important tasks in major wireless communication systems: channel estimation and decoding …

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Registration Discounts Grant Opportunities Venue, Hotel, and Travel Program Technical …

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 …

Signal classification is a universal problem in adversarial wireless scenarios, especially
when an eavesdropping radio receiver attempts to glean information about a target …

Deep learning techniques can classify spectrum phenomena (eg, waveform modulation)
with accuracy levels that were once thought impossible. Although we have recently seen …

Federated learning (FL) offers a decentralized learning environment so that a group of
clients can collaborate to train a global model at the server, while keeping their training data …

For the modulation classification problems, the deep learning approaches can determine the
unknown modulation formats in high confidence. However, it has been maliciously used by …

对调制识别的对抗样本攻击这一研究热点进行了综述, 首先给出调制识别中对抗样本的的相关
概述和专业术语, 将对抗样本攻击和防御方法的相关研究成果进行梳理回顾 …