Generative adversarial network for wireless signal spoofing
The paper presents a novel approach of spoofing wireless signals by using a general
adversarial network (GAN) to generate and transmit synthetic signals that cannot be reliably …
adversarial network (GAN) to generate and transmit synthetic signals that cannot be reliably …
Generative adversarial network in the air: Deep adversarial learning for wireless signal spoofing
Y Shi, K Davaslioglu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The spoofing attack is critical to bypass physical-layer signal authentication. This paper
presents a deep learning-based spoofing attack to generate synthetic wireless signals that …
presents a deep learning-based spoofing attack to generate synthetic wireless signals that …
GNSS spoofing jamming detection based on generative adversarial network
The GNSS spoofing jamming is generated by transmitting spoofing signals that are identical
or similar to the authentic satellite signals but have a stronger power in order to guide a …
or similar to the authentic satellite signals but have a stronger power in order to guide a …
Spoofing detection with reinforcement learning in wireless networks
L Xiao, Y Li, G Liu, Q Li… - 2015 IEEE Global …, 2015 - ieeexplore.ieee.org
In this paper, we investigate the PHY-layer authentication in wireless networks, which
exploits PHY-layer channel information such as the received signal strength indicators to …
exploits PHY-layer channel information such as the received signal strength indicators to …
Generalized wireless adversarial deep learning
Deep learning techniques can classify spectrum phenomena (eg, waveform modulation)
with accuracy levels that were once thought impossible. Although we have recently seen …
with accuracy levels that were once thought impossible. Although we have recently seen …
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 …
Deep learning for launching and mitigating wireless jamming attacks
An adversarial machine learning approach is introduced to launch jamming attacks on
wireless communications and a defense strategy is presented. A cognitive transmitter uses a …
wireless communications and a defense strategy is presented. A cognitive transmitter uses a …
RFAL: Adversarial learning for RF transmitter identification and classification
Recent advances in wireless technologies have led to several autonomous deployments of
such networks. As nodes across distributed networks must co-exist, it is important that all …
such networks. As nodes across distributed networks must co-exist, it is important that all …
Channel-aware adversarial attacks against deep learning-based wireless signal classifiers
This paper presents channel-aware adversarial attacks against deep learning-based
wireless signal classifiers. There is a transmitter that transmits signals with different …
wireless signal classifiers. There is a transmitter that transmits signals with different …
Machine learning-based spoofing attack detection in mmWave 60GHz IEEE 802.11 ad networks
Spoofing attacks pose a serious threat to wireless communications. Exploiting physical-layer
features to counter spoofing attacks is a promising solution. Although various physical-layer …
features to counter spoofing attacks is a promising solution. Although various physical-layer …