Intrusion detection systems: A state-of-the-art taxonomy and survey
M Alkasassbeh, S Al-Haj Baddar - Arabian Journal for Science and …, 2023 - Springer
Abstract Intrusion Detection Systems (IDSs) have become essential to the sound operations
of networks. These systems have the potential to identify and report deviations from normal …
of networks. These systems have the potential to identify and report deviations from normal …
Semisupervised federated-learning-based intrusion detection method for internet of things
Federated learning (FL) has become an increasingly popular solution for intrusion detection
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
[HTML][HTML] A systematic literature review of recent lightweight detection approaches leveraging machine and deep learning mechanisms in Internet of Things networks
GAL Mukhaini, M Anbar, S Manickam… - Journal of King Saud …, 2023 - Elsevier
Abstract The Internet of Things (IoT) connects daily use devices to the Internet, such as
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
Intrusion detection of industrial internet-of-things based on reconstructed graph neural networks
Industrial Internet-of-Things (IIoT) are highly vulnerable to cyber-attacks due to their open
deployment in unattended environments. Intrusion detection is an efficient solution to …
deployment in unattended environments. Intrusion detection is an efficient solution to …
[HTML][HTML] DIDS: A Deep Neural Network based real-time Intrusion detection system for IoT
M Vishwakarma, N Kesswani - Decision Analytics Journal, 2022 - Elsevier
The number of people using the Internet of Things (IoT) devices has exploded in recent
years. The instantaneous development in deploying constrained devices in numerous areas …
years. The instantaneous development in deploying constrained devices in numerous areas …
An automatic and efficient malware traffic classification method for secure Internet of Things
Malware traffic classification (MTC) plays an important role in cyber security and network
resource management for the secure Internet of Things (IoT). Many deep learning (DL) …
resource management for the secure Internet of Things (IoT). Many deep learning (DL) …
Federated learning for iot devices with domain generalization
Federated learning (FL) is a distributed machine learning (ML) technique that allows
numerous Internet of Things (IoT) devices to jointly train an ML model using a centralized …
numerous Internet of Things (IoT) devices to jointly train an ML model using a centralized …
GPU-free specific emitter identification using signal feature embedded broad learning
Emerging wireless networks may suffer severe security threats due to the ubiquitous access
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …
A lightweight IoT intrusion detection model based on improved BERT-of-Theseus
Z Wang, J Li, S Yang, X Luo, D Li… - Expert Systems with …, 2024 - Elsevier
The proliferation of Internet of Things (IoT) technology has resulted in an increase in security
vulnerabilities associated with the interconnectivity of IoT devices. As a result, there is a …
vulnerabilities associated with the interconnectivity of IoT devices. As a result, there is a …
A novel deep supervised learning-based approach for intrusion detection in IoT systems
The Internet of Things (IoT) has become one of the most important concepts in various
aspects of our modern life in recent years. However, the most critical challenge for the world …
aspects of our modern life in recent years. However, the most critical challenge for the world …