[PDF][PDF] IOT-MDEDTL: IoT Malware Detection based on Ensemble Deep Transfer Learning

QK Kadhim, AQAS Al-Sudani, IA Almani… - Majlesi Journal of …, 2022 - journals.iau.ir
The internet of Things (IoT) is a promising expansion of the traditional Internet, which
provides the foundation for millions of devices to interact with each other. IoT enables these …

Transfer learning for image-based malware detection for iot

P Panda, OK CU, S Marappan, S Ma, D Veesani Nandi - Sensors, 2023 - mdpi.com
The tremendous growth in online activity and the Internet of Things (IoT) led to an increase
in cyberattacks. Malware infiltrated at least one device in almost every household. Various …

[PDF][PDF] DLSTM-HHO: Enhanced Deep Learning Framework for Malware Detection at the Edge of the Iot System

D Santhadevi, B Janet - 2021 - scholar.archive.org
Abstract Internet of Things (IoT) technology has a dynamic atmosphere due to incorporating
multiple smart peripherals, which provide autonomous homes, cities, manufacturing …

Malware detection in internet of things (IoT) devices using deep learning

S Riaz, S Latif, SM Usman, SS Ullah, AD Algarni… - Sensors, 2022 - mdpi.com
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 …

[HTML][HTML] A new deep boosted CNN and ensemble learning based IoT malware detection

SH Khan, TJ Alahmadi, W Ullah, J Iqbal, A Rahim… - Computers & …, 2023 - Elsevier
Security issues are threatened in various types of networks, especially in the Internet of
Things (IoT) environment that requires early detection. IoT is the network of real-time devices …

A novel detection and multi-classification approach for IoT-malware using random forest voting of fine-tuning convolutional neural networks

SB Atitallah, M Driss, I Almomani - Sensors, 2022 - mdpi.com
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 …

SIM-FED: Secure IoT malware detection model with federated learning

M Nobakht, R Javidan, A Pourebrahimi - Computers and Electrical …, 2024 - Elsevier
Many IoT devices are presently in use without sufficient security measures. The vulnerability
of these devices to malware highlights the necessity for effective methods to identify …

A Comparative Analysis of IoT Malware Detection Using CNN and Deep Learning

U Garg, SS Rana, DS Bisht, R Rautela… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
The emergence of Internet of Things devices has significantly increased malware attacks on
IoT devices. Therefore, there is a growing need for efficient and reliable malware detection …

DEMD-IoT: a deep ensemble model for IoT malware detection using CNNs and network traffic

M Nobakht, R Javidan, A Pourebrahimi - Evolving Systems, 2023 - Springer
Malware detection has recently emerged as a significant challenge on the Internet of Things
(IoT) security domain. Due to the increasing complexity and variety of malware, the demand …

IoT malware classification based on lightweight convolutional neural networks

B Yuan, J Wang, P Wu, X Qing - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) is hard to deploy adequate security defenses due to the diversity of
architectures as well as the limited computing and storage capabilities, which makes it more …