A Survey on Graph Neural Networks for Intrusion Detection Systems: Methods, Trends and Challenges

M Zhong, M Lin, C Zhang, Z Xu - Computers & Security, 2024 - Elsevier
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …

[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 …

Toward Enhanced Attack Detection and Explanation in Intrusion Detection System-Based IoT Environment Data

RW Wardhani, DSC Putranto, U Jo, H Kim - IEEE Access, 2023 - ieeexplore.ieee.org
Securing the Internet of Things (IoT) against cyber threats is a formidable challenge, and
Intrusion Detection Systems (IDS) play a critical role in this effort. However, the lack of …

[HTML][HTML] IoT Intrusion Detection System Based on Machine Learning

B Xu, L Sun, X Mao, R Ding, C Liu - Electronics, 2023 - mdpi.com
With the rapid development of the Internet of Things (IoT), the number of IoT devices is
increasing dramatically, making it increasingly important to identify intrusions on these …

M2VT-IDS: A multi-task multi-view learning architecture for designing IoT intrusion detection system

F Nie, W Liu, G Liu, B Gao - Internet of Things, 2024 - Elsevier
With the rapidly growing frequency of security incidents in the Internet of Things (IoT),
intrusion detection systems (IDS) have gained increasing attention in recent years. They …

Model-agnostic generation-enhanced technology for few-shot intrusion detection

J He, L Yao, X Li, MK Khan, W Niu, X Zhang, F Li - Applied Intelligence, 2024 - Springer
Malicious traffic on the Internet has become an increasingly serious problem, and several
artificial intelligence (AI)-based malicious traffic detection methods have been proposed …

[HTML][HTML] Logistic Regression Ensemble Classifier for Intrusion Detection System in Internet of Things

S Chalichalamala, N Govindan, R Kasarapu - Sensors, 2023 - mdpi.com
The Internet of Things (IoT) is a powerful technology that connect its users worldwide with
everyday objects without any human interference. On the contrary, the utilization of IoT …

Hierarchical multistep approach for intrusion detection and identification in IoT and Fog computing-based environments

CA de Souza, CB Westphall, JDG Valencio… - Ad Hoc Networks, 2024 - Elsevier
Special security techniques, such as intrusion detection mechanisms, are indispensable in
modern computer systems. With the emergence of the Internet of Things they have become …

FEDSA-ResnetV2: An Efficient Intrusion Detection System for Vehicle Road Cooperation Based on Federated Learning

Z Qu, Z Cai - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Federated learning (FL)-based intrusion detection systems (IDSs) for vehicle road
cooperation have attracted significant attention in recent years. However, the non …

A multi-label network attack detection approach based on two-stage model fusion

Y Huang, J Gou, Z Fan, Y Liao, Y Zhuang - Journal of Information Security …, 2024 - Elsevier
The diversification and complexity of network attacks pose a serious challenge to network
security and lead to the phenomenon of overlapping attributes of network attack behaviors …