How machine learning changes the nature of cyberattacks on IoT networks: A survey
The Internet of Things (IoT) has continued gaining in popularity and importance in everyday
life in recent years. However, this development does not only present advantages. Indeed …
life in recent years. However, this development does not only present advantages. Indeed …
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. To support both attack and …
due to the shared and broadcast nature of wireless medium. To support both attack and …
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 …
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 …
Toward robust networks against adversarial attacks for radio signal modulation classification
Deep learning (DL) is a powerful technique for many real-time applications, but it is
vulnerable to adversarial attacks. Herein, we consider DL-based modulation classification …
vulnerable to adversarial attacks. Herein, we consider DL-based modulation classification …
An Overview of Protocols-Based Security Threats and Countermeasures in WLAN
NK Ojha, E Baray - 2023 4th International Conference for …, 2023 - ieeexplore.ieee.org
WLAN security protocols are the most important section for wireless networks which controls
all the security-related issues by securing the network with some pre-defined rules made by …
all the security-related issues by securing the network with some pre-defined rules made by …
Adversarial machine learning and defense game for NextG signal classification with deep learning
YE Sagduyu - MILCOM 2022-2022 IEEE Military …, 2022 - ieeexplore.ieee.org
This paper presents a game-theoretic framework to study the interactions of attack and
defense for deep learning-based NextG signal classification. NextG systems such as the one …
defense for deep learning-based NextG signal classification. NextG systems such as the one …
Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers
NM Baishya, BR Manoj - arXiv preprint arXiv:2404.15344, 2024 - arxiv.org
Data-driven deep learning (DL) techniques developed for automatic modulation
classification (AMC) of wireless signals are vulnerable to adversarial attacks. This poses a …
classification (AMC) of wireless signals are vulnerable to adversarial attacks. This poses a …
Low-Interception Waveform: To Prevent the Recognition of Spectrum Waveform Modulation via Adversarial Examples
H Xie, J Tan, X Zhang, N Ji, H Liao, Z Yu… - … Symposium of the …, 2021 - ieeexplore.ieee.org
Deep learning is applied to many complex tasks in the field of wireless communication, such
as modulation recognition of spectrum waveforms, because of its convenience and …
as modulation recognition of spectrum waveforms, because of its convenience and …
[图书][B] AI, Machine Learning and Deep Learning: A Security Perspective
Today, Artificial Intelligence (AI) and Machine Learning/Deep Learning (ML/DL) have
become the hottest areas in information technology. In our society, many intelligent devices …
become the hottest areas in information technology. In our society, many intelligent devices …