Investigation of Deep Learning architectures and features for Adversarial Machine Learning Attacks in Modulation Classifications

Investigation of Deep Learning architectures and features for Adversarial Machine Learning Attacks in Modulation Classifications

Artificial intelligence (AI), and specifically machine and deep learning, are emerging as essential enabling techniques for the design of future generations of wireless networks for the Internet of Things (IoT). With the exponential increase in IoT devices in recent years, AI methods have become eve...

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Bibliographic Details
Main Authors: Marios Aristodemou, Sangarapillai Lambotharan, Gan Zheng, Leonidas Aristodemou
Format: Default Conference proceeding
Published: 2022
Subjects:
Deep learning
Multidimensional signal processing
Wireless networks
Neural networks
Modulation
Frequency response
Entropy
Online Access:https://hdl.handle.net/2134/20310984.v1
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https://hdl.handle.net/2134/20310984.v1

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