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A survey on graph neural networks for intrusion detection systems: methods, trends and challenges
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …
increasing sophistication of cyber attack methods, traditional detection approaches are …
[HTML][HTML] Deep learning for cyber threat detection in IoT networks: A review
Abstract The Internet of Things (IoT) has revolutionized modern tech with interconnected
smart devices. While these innovations offer unprecedented opportunities, they also …
smart devices. While these innovations offer unprecedented opportunities, they also …
A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
Deep learning-enabled anomaly detection for IoT systems
Abstract Internet of Things (IoT) systems have become an intrinsic technology in various
industries and government services. Unfortunately, IoT devices and networks are known to …
industries and government services. Unfortunately, IoT devices and networks are known to …
A deep learning approach for intrusion detection in Internet of Things using focal loss function
Abstract Internet of Things (IoT) is likely to revolutionize healthcare, energy, education,
transportation, manufacturing, military, agriculture, and other industries. However, for the …
transportation, manufacturing, military, agriculture, and other industries. However, for the …
Deep Q-network-based heuristic intrusion detection against edge-based SIoT zero-day attacks
How to process and classify zero-day attacks due to their huge damage to social Internet of
Things (SIoT) systems has become a hot research issue. To solve this issue, we propose a …
Things (SIoT) systems has become a hot research issue. To solve this issue, we propose a …
A survey on explainable artificial intelligence for cybersecurity
The “black-box” nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …
[HTML][HTML] TNN-IDS: Transformer neural network-based intrusion detection system for MQTT-enabled IoT Networks
Abstract The Internet of Things (IoT) is a global network that connects a large number of
smart devices. MQTT is a de facto standard, lightweight, and reliable protocol for machine-to …
smart devices. MQTT is a de facto standard, lightweight, and reliable protocol for machine-to …
Recent endeavors in machine learning-powered intrusion detection systems for the internet of things
The significant advancements in sensors and other resource-constrained devices, capable
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
Federated learning for reliable model updates in network-based intrusion detection
Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
adopted in the scientific literature. Besides being highly variable, network traffic behavior …