A survey on space-air-ground-sea integrated network security in 6G
Space-air-ground-sea integrated network (SAGSIN), which integrates satellite
communication networks, aerial networks, terrestrial networks, and marine communication …
communication networks, aerial networks, terrestrial networks, and marine communication …
Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …
there is a great need to deliberate on the future of the cities worth living. In particular, as …
Backdoor learning: A survey
Backdoor attack intends to embed hidden backdoors into deep neural networks (DNNs), so
that the attacked models perform well on benign samples, whereas their predictions will be …
that the attacked models perform well on benign samples, whereas their predictions will be …
Backdoor attacks and countermeasures on deep learning: A comprehensive review
This work provides the community with a timely comprehensive review of backdoor attacks
and countermeasures on deep learning. According to the attacker's capability and affected …
and countermeasures on deep learning. According to the attacker's capability and affected …
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 …
Adversarial machine learning: A multilayer review of the state-of-the-art and challenges for wireless and mobile systems
J Liu, M Nogueira, J Fernandes… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Machine Learning (ML) models are susceptible to adversarial samples that appear as
normal samples but have some imperceptible noise added to them with the intention of …
normal samples but have some imperceptible noise added to them with the intention of …
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 …
Over-the-air adversarial attacks on deep learning based modulation classifier over wireless channels
We consider a wireless communication system that consists of a transmitter, a receiver, and
an adversary. The transmitter transmits signals with different modulation types, while the …
an adversary. The transmitter transmits signals with different modulation types, while the …
Design and evaluation of a multi-domain trojan detection method on deep neural networks
Trojan attacks on deep neural networks (DNNs) exploit a backdoor embedded in a DNN
model that can hijack any input with an attacker's chosen signature trigger. Emerging …
model that can hijack any input with an attacker's chosen signature trigger. Emerging …