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 …
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 …
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 …
Facial emotion recognition in verbal communication based on deep learning
MF Alsharekh - Sensors, 2022 - mdpi.com
Facial emotion recognition from facial images is considered a challenging task due to the
unpredictable nature of human facial expressions. The current literature on emotion …
unpredictable nature of human facial expressions. The current literature on emotion …
Trojan attacks on wireless signal classification with adversarial machine learning
K Davaslioglu, YE Sagduyu - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
We present a Trojan (backdoor or trapdoor) attack that targets deep learning applications in
wireless communications. A deep learning classifier is considered to classify wireless …
wireless communications. A deep learning classifier is considered to classify wireless …
3D convolutional neural networks based automatic modulation classification in the presence of channel noise
Automatic modulation classification is a task that is essentially required in many intelligent
communication systems such as fibre‐optic, next‐generation 5G or 6G systems, cognitive …
communication systems such as fibre‐optic, next‐generation 5G or 6G systems, cognitive …
Fast initial access with deep learning for beam prediction in 5G mmWave networks
We present DeepIA, a deep learning solution for a fast, reliable and secure initial access (IA)
in directional networks such as the mmWave networks in 5G systems. By utilizing only a …
in directional networks such as the mmWave networks in 5G systems. By utilizing only a …
An rfml ecosystem: Considerations for the application of deep learning to spectrum situational awareness
While deep learning (DL) technologies are now pervasive in state-of-the-art Computer
Vision (CV) and Natural Language Processing (NLP) applications, only in recent years have …
Vision (CV) and Natural Language Processing (NLP) applications, only in recent years have …
Self-supervised RF signal representation learning for NextG signal classification with deep learning
K Davaslioglu, S Boztaş, MC Ertem… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
Deep learning (DL) finds rich applications in the wireless domain to improve spectrum
awareness. Typically, DL models are either randomly initialized following a statistical …
awareness. Typically, DL models are either randomly initialized following a statistical …
Deep learning for fast and reliable initial access in AI-driven 6G mm wave networks
We present DeepIA, a deep neural network (DNN) framework for fast and reliable initial
access (IA) for artificial intelligence (AI)-driven 6G millimeter wave (mmWave) networks …
access (IA) for artificial intelligence (AI)-driven 6G millimeter wave (mmWave) networks …