Anomaly detection plays a critical role in various domains, including cybersecurity, finance,
healthcare, and industrial monitoring by identifying unusual patterns or events that deviate …

Anomaly mining finds high-stakes applications in various real-world domains such as
cybersecurity, finance, environmental monitoring, to name a few. Therefore, it has been …

In this tutorial we aim to present a comprehensive survey of the advances in deep learning
techniques specifically designed for anomaly detection (deep anomaly detection for short) …

Anomaly detection is a critical task in ensuring the security and safety of infrastructure and
individuals in smart environments. This paper provides a comprehensive analysis of recent …

Anomalies in complex systems pose significant challenges to operational efficiency, safety,
and security. This research introduces a pioneering approach leveraging artificial …

Although deep learning has been applied to successfully address many data mining
problems, relatively limited work has been done on deep learning for anomaly detection …

In supervised learning it has been shown that a collection of weak classifiers can result in a
strong classifier with error rates similar to those of more sophisticated methods. In …

Anomaly detection has been a long-standing security approach with versatile applications,
ranging from securing server programs in critical environments, to detecting insider threats …

Finding Data Anomalies You Didn't Know to Look For Anomaly detection is the detective
work of machine learning: finding the unusual, catching the fraud, discovering strange …

Anomaly detection has been widely studied and used in diverse applications. Building an
effective anomaly detection system requires the researchers/developers to learn the …