Adversarial machine learning for 5G communications security
Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …
spectrum and support better understanding of spectrum resources and their efficient …
Adversarial deep learning for over-the-air spectrum poisoning attacks
An adversarial deep learning approach is presented to launch over-the-air spectrum
poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to …
poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to …
Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Evaluating adversarial evasion attacks in the context of wireless communications
B Flowers, RM Buehrer… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
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. Yet …
use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks. Yet …
Adversarial deep learning for cognitive radio security: Jamming attack and defense strategies
This paper presents an adversarial machine learning approach to launch jamming attacks
on wireless communications and introduces a defense strategy. In a cognitive radio network …
on wireless communications and introduces a defense strategy. In a cognitive radio network …
On the limitations of targeted adversarial evasion attacks against deep learning enabled modulation recognition
Wireless communications has greatly benefited in recent years from advances in machine
learning. A new subfield, commonly termed Radio Frequency Machine Learning (RFML) …
learning. A new subfield, commonly termed Radio Frequency Machine Learning (RFML) …
Adversarial jamming attacks on deep reinforcement learning based dynamic multichannel access
Adversarial attack strategies have been widely studied in machine learning applications,
and now are increasingly attracting interest in wireless communications as the application of …
and now are increasingly attracting interest in wireless communications as the application of …
Wild networks: Exposure of 5G network infrastructures to adversarial examples
G Apruzzese, R Vladimirov… - … on Network and …, 2022 - ieeexplore.ieee.org
Fifth Generation (5G) networks must support billions of heterogeneous devices while
guaranteeing optimal Quality of Service (QoS). Such requirements are impossible to meet …
guaranteeing optimal Quality of Service (QoS). Such requirements are impossible to meet …
IoT network security from the perspective of adversarial deep learning
Machine learning finds rich applications in Internet of Things (IoT) networks such as
information retrieval, traffic management, spectrum sensing, and signal authentication. While …
information retrieval, traffic management, spectrum sensing, and signal authentication. While …
Deep learning for wireless communications
Existing communication systems exhibit inherent limitations in translating theory to practice
when handling the complexity of optimization for emerging wireless applications with high …
when handling the complexity of optimization for emerging wireless applications with high …