[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 …

Exploring lightweight deep learning solution for malware detection in IoT constraint environment

AR Khan, A Yasin, SM Usman, S Hussain, S Khalid… - Electronics, 2022 - mdpi.com
The present era is facing the industrial revolution. Machine-to-Machine (M2M)
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …

Artificial intelligence-driven malware detection framework for internet of things environment

S Alsubai, AK Dutta, AM Alnajim, R Ayub… - PeerJ Computer …, 2023 - peerj.com
Abstract The Internet of Things (IoT) environment demands a malware detection (MD)
framework for protecting sensitive data from unauthorized access. The study intends to …

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 …

Convnext-Eesnn: An effective deep learning based malware detection in edge based IIOT

D Maddali - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
A rising number of edge devices, like controllers, sensors, and robots, are crucial for
Industrial Internet of Things (IIoT) networks for collecting data for communication, storage …

[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 …

[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 …

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 …

EIDIMA: edge-based intrusion detection of IoT malware attacks using decision tree-based boosting algorithms

D Santhadevi, B Janet - … Computing and Networking: Select Proceedings of …, 2022 - Springer
With the rise of smart gadgets and technology, anomalous traffic monitoring on the Internet
has become a significant security challenge. Several assaults are causing havoc on the …