Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals

Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals

Machine learning (ML) has been successfully applied to classification tasks in many domains, including computer vision, cybersecurity, and communications. Although highly accurate classifiers have been developed, research shows that these classifiers are, in general, vulnerable to adversarial machin...

Full description

Saved in:
Bibliographic Details
Main Authors: Wenhan Zhang, Marwan Krunz, Gregory Ditzler
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Deep learning
signal classification
adversarial machine learning
shared spectrum
wireless security
Online Access:https://ieeexplore.ieee.org/document/10436107/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10436107/

Similar Items