Due to the complexity of the oil and gas station system, the operational data, with various
temporal dependencies and inter-metric dependencies, has the characteristics of diverse …

Anomaly detection of time series has always been a hot topic in academia and industry.
However, many existing multivariant time series methods suffer from common challenges …

Recent studies have shown that an attacker can compromise some of the power grid
measurements to mislead the conventional state estimators (SEs), since the manipulated …

A network provides powerful means of representing complex relationships between entities
by abstracting entities as vertices, and relationships as edges connecting vertices in a …

Robust control and management of the grid relies on accurate data. Both phasor
measurement units and remote terminal units are prone to false data injection attacks. Thus …

Anomaly detection in sentiment analysis refers to detecting users' abnormal opinions,
sentiment patterns or special temporal aspects of such patterns. Users' emotional state …

Determining anomalies in data streams that are collected and transformed from various
types of networks has recently attracted significant research interest. Principal Component …

As cyberattacks become increasingly prevalent globally, there is a need to identify trends in
these cyberattacks and take suitable countermeasures quickly. The darknet, an unused IP …

This paper proposes a new framework for anomaly detection when collectively monitoring
many complex systems. The prerequisite for condition-based monitoring in industrial …

In this study, we propose a human movement model both for myoelectric assistive robot
control and biosignal-sensor-failure detection. We particularly consider an application to …