[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 …
[HTML][HTML] SoK: Realistic adversarial attacks and defenses for intelligent network intrusion detection
Abstract Machine Learning (ML) can be incredibly valuable to automate anomaly detection
and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is …
and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is …
Distribution bias aware collaborative generative adversarial network for imbalanced deep learning in industrial IoT
The impact of Internet of Things (IoT) has become increasingly significant in smart
manufacturing, while deep generative model (DGM) is viewed as a promising learning …
manufacturing, while deep generative model (DGM) is viewed as a promising learning …
Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything
Nowadays, the concept of Internet of Everything (IoE) is becoming a hotly discussed topic,
which is playing an increasingly indispensable role in modern intelligent applications. These …
which is playing an increasingly indispensable role in modern intelligent applications. These …
Fast anomaly identification based on multiaspect data streams for intelligent intrusion detection toward secure industry 4.0
Various cyber attacks often occur in logistics network of the Industry 4.0, which poses a
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
Gtxchain: A secure iot smart blockchain architecture based on graph neural network
With the expansion of scale, the Internet of Things (IoT) suffers more and more security
threats, and vulnerability and sensitivity to attacks are also increasing. As a distributed and …
threats, and vulnerability and sensitivity to attacks are also increasing. As a distributed and …
Uav-assisted task offloading for iot in smart buildings and environment via deep reinforcement learning
J Xu, D Li, W Gu, Y Chen - Building and Environment, 2022 - Elsevier
With the rapid development of Internet of Things (IoT) techniques, IoT devices with sensors
have been widely deployed and used in smart buildings and environment, and the …
have been widely deployed and used in smart buildings and environment, and the …
Security framework for internet-of-things-based software-defined networks using blockchain
Presently, trillions of Internet of Things (IoT) devices are in use, with many more projected to
join IoT networks in the future. These IoT devices create a massive volume of data, which …
join IoT networks in the future. These IoT devices create a massive volume of data, which …
Detection of real-time malicious intrusions and attacks in IoT empowered cybersecurity infrastructures
Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …
Intrusion detection is a key component of network security as an active defence technology …
A knowledge-driven anomaly detection framework for social production system
In the social production system, image data are rapidly generated from almost all fields such
as factories, hospitals, and transportation, promoting higher requirements for image anomaly …
as factories, hospitals, and transportation, promoting higher requirements for image anomaly …