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This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT (IIoT) systems, combining ResNet-1D, BiGRU, and Multi-Head Attention (MHA) for effective spatial-temporal feature extraction and attention-based…
The rapid expansion of Internet of Things (IoT) devices has increased the risk of cyber-attacks, making effective detection essential for securing IoT networks. This work introduces a novel approach combining Self-Organizing Maps (SOMs),…
Internet of Things (IoT) has brought along immense benefits to our daily lives encompassing a diverse range of application domains that we regularly interact with, ranging from healthcare automation to transport and smart environments.…
With the rise in the number of IoT devices and its users, security in IoT has become a big concern to ensure the protection from harmful security attacks. In the recent years, different variants of DDoS attacks have been on the rise in IoT…
. As Supervisory Control and Data Acquisition (SCADA) systems control several critical infrastructures, they have connected to the internet. Consequently, SCADA systems face different sophisticated types of cyber adversaries. This paper…
Internet of things (IoT) connects all items to the Internet through information-sensing devices to exchange information for intelligent identification and management. Sybil attack is a famous and crippling attack in IoT. Most of the…
Cross-domain intrusion detection remains a critical challenge due to significant variability in network traffic characteristics and feature distributions across environments. This study evaluates the transferability of three widely used…
The Internet of Things (IoT) has been introduced as a breakthrough technology that integrates intelligence into everyday objects, enabling high levels of connectivity between them. As the IoT networks grow and expand, they become more…
Since the advent of the Internet of Things (IoT), exchanging vast amounts of information has increased the number of security threats in networks. As a result, intrusion detection based on deep learning (DL) has been developed to achieve…
The rapid expansion of Internet of Things (IoT) systems across various domains such as industry, smart cities, healthcare, manufacturing, and government services has led to a significant increase in security risks, threatening data…
Maintaining security in IoT systems depends on intrusion detection since these networks' sensitivity to cyber-attacks is growing. Based on the IoT23 dataset, this study explores the use of several Machine Learning (ML) and Deep Learning…
The rapid growth of the Internet of Things (IoT) has revolutionized industries, enabling unprecedented connectivity and functionality. However, this expansion also increases vulnerabilities, exposing IoT networks to increasingly…
IoT botnet detection has advanced, yet most published systems are validated on a single dataset and rarely generalise across environments. Heterogeneous feature spaces make multi-dataset training practically impossible without discarding…
Cyberattacks in an Internet of Things (IoT) environment can have significant impacts because of the interconnected nature of devices and systems. An attacker uses a network of compromised IoT devices in a botnet attack to carry out various…
As the Internet of Things (IoT) continues to expand across critical infrastructure, smart environments, and consumer devices, securing them against cyber threats has become increasingly vital. Traditional intrusion detection models often…
The rapid expansion of the industrial Internet of things (IIoT) has introduced new challenges in securing critical infrastructures against sophisticated cyberthreats. This study presents the development and evaluation of an advanced…
We propose a novel hierarchical online intrusion detection system (HOIDS) for supervisory control and data acquisition (SCADA) networks based on machine learning algorithms. By utilizing the server-client topology while keeping clients…
The Internet of Things (IoT) is expanding at an accelerated pace, making it critical to have secure networks to mitigate a variety of cyber threats. This study addresses the limitation of multi-class attack detection of IoT devices and…
The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to…
In this paper, we propose a robust and reinforcement-learning-enhanced network intrusion detection system (NIDS) designed for class-imbalanced and few-shot attack scenarios in Industrial Internet of Things (IIoT) environments. Our model…