A comprehensive review on deep learning algorithms: Security and privacy issues
Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …
various complicated tasks that begin to modify and improve with experiences. It has become …
The survey and meta-analysis of the attacks, transgressions, countermeasures and security aspects common to the Cloud, Edge and IoT
Cloud computing, edge computing, and Internet-of-Things-these new Internet concepts have
already irreversibly changed and influenced people's lives. The security of the three patterns …
already irreversibly changed and influenced people's lives. The security of the three patterns …
Fog computing-based intrusion detection architecture to protect iot networks
Y Labiod, A Amara Korba, N Ghoualmi - Wireless Personal …, 2022 - Springer
With the deployment of billions of Internet of Things (IoT) devices, more and more cyber
attacks involving or even targeting such devices are rife. Cyberattack vectors are in constant …
attacks involving or even targeting such devices are rife. Cyberattack vectors are in constant …
Iot traffic-based DDoS attacks detection mechanisms: A comprehensive review
Abstract The Internet of Things (IoT) has emerged as an inevitable part of human life, that
includes online learning, smart homes, smart cars, smart grids, smart cities, agriculture, and …
includes online learning, smart homes, smart cars, smart grids, smart cities, agriculture, and …
HH-NIDS: Heterogeneous hardware-based network intrusion detection framework for IoT security
This study proposes a heterogeneous hardware-based framework for network intrusion
detection using lightweight artificial neural network models. With the increase in the volume …
detection using lightweight artificial neural network models. With the increase in the volume …
Cybersecurity of robotic systems: Leading challenges and robotic system design methodology
Recent years have seen a rapid development of the Internet of Things (IoT) and the growth
of autonomous robotic applications which are using network communications. Accordingly …
of autonomous robotic applications which are using network communications. Accordingly …
Unsupervised network traffic anomaly detection with deep autoencoders
Abstract Contemporary Artificial Intelligence methods, especially their subset-deep learning,
are finding their way to successful implementations in the detection and classification of …
are finding their way to successful implementations in the detection and classification of …
FPGA hardware acceleration framework for anomaly-based intrusion detection system in IoT
This study proposes a versatile framework for real-time Internet of Things (IoT) network
intrusion detection using Artificial Neural Network (ANN) on heterogeneous hardware. With …
intrusion detection using Artificial Neural Network (ANN) on heterogeneous hardware. With …
Ocids: An online cnn-based network intrusion detection system for ddos attacks with iot botnets
As the number of IoT devices increases considerably, the need for accurate and fast
malicious traffic detection systems for DDoS attacks with IoT botnet has become apparent …
malicious traffic detection systems for DDoS attacks with IoT botnet has become apparent …
Comparison of Machine Learning Models for IoT Malware Classification
TY Kuek - Proceedings of the International Conference on …, 2023 - books.google.com
The Internet of Things (IoT) is a system where devices and sensors are interconnected to
improve accuracy, efficiency, precision and consistency. It is being developed rapidly as …
improve accuracy, efficiency, precision and consistency. It is being developed rapidly as …