Search Results for author:
Found 4 papers, 0 papers with code
The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications
While deep machine learning technologies are now pervasive in state-of-the-art image recognition and natural language processing applications, only in recent years have these technologies started to sufficiently mature in applications related to wireless communications.
Effects of Forward Error Correction on Communications Aware Evasion Attacks
Recent work has shown the impact of adversarial machine learning on deep neural networks (DNNs) developed for Radio Frequency Machine Learning (RFML) applications.
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions
Wireless systems are vulnerable to various attacks such as jamming and eavesdropping due to the shared and broadcast nature of wireless medium.
Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications
Recent advancements in radio frequency machine learning (RFML) have demonstrated the use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
