Distributed deep neural-network-based middleware for cyber-attacks detection in smart IoT ecosystem: A novel framework and performance evaluation approach
Cyberattacks always remain the major threats and challenging issues in the modern digital
world. With the increase in the number of internet of things (IoT) devices, security challenges …
world. With the increase in the number of internet of things (IoT) devices, security challenges …
IIoT malware detection using edge computing and deep learning for cybersecurity in smart factories
H Kim, K Lee - Applied Sciences, 2022 - mdpi.com
The smart factory environment has been transformed into an Industrial Internet of Things
(IIoT) environment, which is an interconnected and open approach. This has made smart …
(IIoT) environment, which is an interconnected and open approach. This has made smart …
A hybrid DL-based detection mechanism for cyber threats in secure networks
The astonishing growth of sophisticated ever-evolving cyber threats and attacks throws the
entire Internet-of-Things (IoT) infrastructure into chaos. As the IoT belongs to the …
entire Internet-of-Things (IoT) infrastructure into chaos. As the IoT belongs to the …
Stacked deep learning framework for edge-based intelligent threat detection in IoT network
D Santhadevi, B Janet - The Journal of Supercomputing, 2023 - Springer
Cyber-attacks on Internet of Things (IoT) devices are becoming increasingly common due to
the rapidly growing number of connected devices and the lack of security measures in many …
the rapidly growing number of connected devices and the lack of security measures in many …
Detecting botnet attacks in IoT environments: An optimized machine learning approach
MN Injadat, A Moubayed… - 2020 32nd International …, 2020 - ieeexplore.ieee.org
The increased reliance on the Internet and the corresponding surge in connectivity demand
has led to a significant growth in Internet-of-Things (IoT) devices. The continued deployment …
has led to a significant growth in Internet-of-Things (IoT) devices. The continued deployment …
Exploring lightweight deep learning solution for malware detection in IoT constraint environment
The present era is facing the industrial revolution. Machine-to-Machine (M2M)
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
An ensemble of deep recurrent neural networks for detecting IoT cyber attacks using network traffic
M Saharkhizan, A Azmoodeh… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) devices and systems will be increasingly targeted by cybercriminals
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
Malware detection in internet of things (IoT) devices using deep learning
Internet of Things (IoT) devices usage is increasing exponentially with the spread of the
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
Deep-learning based detection for cyber-attacks in IoT networks: A distributed attack detection framework
The widespread use of smart devices and the numerous security weaknesses of networks
has dramatically increased the number of cyber-attacks in the internet of things (IoT) …
has dramatically increased the number of cyber-attacks in the internet of things (IoT) …
A novel detection and multi-classification approach for IoT-malware using random forest voting of fine-tuning convolutional neural networks
The Internet of Things (IoT) is prone to malware assaults due to its simple installation and
autonomous operating qualities. IoT devices have become the most tempting targets of …
autonomous operating qualities. IoT devices have become the most tempting targets of …