With the development of blockchain, artificial intelligence, and data mining technology,
abnormal network traffic data has become easy to obtain. The traffic detection model detects …

Context: The increasingly complex and diverse network environment has increased traffic
intrusion behaviors, but the traditional machine learning-based model has the problems of …

Network intrusion detection plays a very important role in network security. Although current
deep learning-based intrusion detection algorithms have achieved good detection …

Abstract The Internet of Things (IoT) environment demands a malware detection (MD)
framework for protecting sensitive data from unauthorized access. The study intends to …

Smart city situational awareness has recently emerged as a hot topic in research societies,
industries, and governments because of its potential to integrate cutting-edge information …

The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …

The increasingly frequent network intrusions have brought serious impacts to the production
and life, thus malicious network traffic detection has received more and more attention in …

Deep learning-based network traffic anomaly detection methods have been the mainstream
approaches to enhancing the accuracy performance of Network Intrusion Detection Systems …

An enterprise's private cloud may be attacked by attackers when communicating with the
public cloud. Although traffic detection methods based on deep learning have been widely …

智慧城市态势感知近年来成为学术圈, 产业界及政府部门关注的热门话题.
其整合尖端信息技术的潜力可望解决现代城市面临的诸多挑战. 在最近一期五年规划中 …