Detecting anomalies in massive volumes of multivariate time series data, particularly in the
IoT domain, is critical for maintaining stable systems. Existing anomaly detection models …

Based on the cloud platform, the concept and importance of double-precision teaching in
wisdom teaching is analyzed, and the basic framework of online and offline wisdom …

The combination of deep learning and intrusion detection has become a hot topic in today's
network security. In the face of massive, high‐dimensional network traffic with uneven …

As a core tool, anomaly detection based on a generative adversarial network (GAN) is
showing its powerful potential in protecting the safe and stable operation of industrial control …

The exponential growth of the internet and inter-connectivity has resulted in an extensive
increase in network size and the corresponding data, which has led to numerous novel …

To improve the validity of magnetic flux leakage (MFL) multisensor signals, anomaly
detection has become a significant part of MFL signal processing. The anomalies in MFL are …

Recent years have witnessed an increased attack surface of the Industrial Internet of Things
(IIoT), as the deep convergence of the Internet of Things (IoT) and other information and …

Detecting anomalies is an essential task in many industries. Current state-of-the-art methods
rely on a large number of parameters for high accuracy, which may not be suitable for …

The prevalence of Internet of Things (IoT) technologies is on the rise, making the
identification of anomalies in IoT systems crucial for ensuring their security and reliability …

With the growing complexity of modern vehicles in the digital era, ensuring the reliability of
vehicle system becomes a challenge that needs a responsive framework to monitor and …