[HTML][HTML] Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models

F Alwahedi, A Aldhaheri, MA Ferrag, A Battah… - Internet of Things and …, 2024 - Elsevier
Despite providing unparalleled connectivity and convenience, the exponential growth of the
Internet of Things (IoT) ecosystem has triggered significant cybersecurity concerns. These …

[HTML][HTML] FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge–Fog–Cloud computing environments

SM Rajagopal, M Supriya, R Buyya - Internet of Things, 2023 - Elsevier
Massive data collection in modern systems has paved the way for data-driven machine
learning, a promising technique for creating reliable and robust statistical models. By …

[HTML][HTML] Enhancing IoT network security through deep learning-powered Intrusion Detection System

SA Bakhsh, MA Khan, F Ahmed, MS Alshehri, H Ali… - Internet of Things, 2023 - Elsevier
The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …

A comparative analysis of various machine learning methods for anomaly detection in cyber attacks on IoT networks

MM Inuwa, R Das - Internet of Things, 2024 - Elsevier
This study explores the growing challenges of cybersecurity in the context of rapidly adopted
Internet of Things (IoT) technologies, which have become increasingly susceptible to cyber …

Deep learning enabled intrusion detection system for Industrial IOT environment

H Nandanwar, R Katarya - Expert Systems with Applications, 2024 - Elsevier
The prevalence of security vulnerabilities in Internet of Things (IoT) applications poses a
serious threat to enterprise systems, necessitating sophisticated and reliable defense …

[HTML][HTML] Improved bacterial foraging optimization with deep learning based anomaly detection in smart cities

MM Khayyat - Alexandria Engineering Journal, 2023 - Elsevier
Abstract The Internet of Things (IoT) contains many smart devices that collect, store,
communicate, and process data. IoT implementation has performed novel opportunities in …

[HTML][HTML] Hybrid Deep Learning Techniques for Securing Bioluminescent Interfaces in Internet of Bio Nano Things

T Bakhshi, S Zafar - Sensors, 2023 - mdpi.com
The Internet of bio-nano things (IoBNT) is an emerging paradigm employing nanoscale (~ 1–
100 nm) biological transceivers to collect in vivo signaling information from the human body …

An explainable multi-modal model for advanced cyber-attack detection in industrial control systems

S Bahadoripour, H Karimipour, AN Jahromi, A Islam - Internet of Things, 2024 - Elsevier
Abstract The convergence of Industrial Control Systems (ICS) and intelligent Internet of
Things (IoT) technologies has rendered ICS more vulnerable to a growing range of cyber …

Securing the digital supply chain cyber threats and vulnerabilities

SR Sindiramutty, NZ Jhanjhi, CE Tan… - … Measures for Logistics …, 2024 - igi-global.com
The digital supply chain has become an integral part of modern business operations,
enabling efficient and streamlined processes. However, with the rapid advancement of …

[HTML][HTML] Machine learning and deep learning techniques for internet of things network anomaly detection—current research trends

SH Rafique, A Abdallah, NS Musa, T Murugan - Sensors, 2024 - mdpi.com
With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels
of connectivity and data. Anomaly detection is a security feature that identifies instances in …