In the past two decades, most research on anomaly detection has focused on improving the
accuracy of the detection, while largely ignoring the explainability of the corresponding …

Performance diagnosis systems are defined as detecting abnormal performance
phenomena and play a crucial role in cloud applications. An effective performance …

As a key resource for diagnosing and identifying problems, network syslog contains vast
quantities of information. And it is the main source of data for anomaly detection of systems …

Anomaly detection has a wide range of real-world applications, such as bank fraud detection
and cyber intrusion detection. In the past decade, a variety of anomaly detection models …

Sequential anomaly detection has received more and more attention because of its wide
applications in various domains, such as debugging system failures via logs. Researchers …

Abnormal event detection, which refers to mining unusual interactions among involved
entities, plays an important role in many real applications. Previous works mostly …

System logs are essential for detecting anomalies, querying faults, and tracing attacks.
Because of the time-consuming and labor-intensive nature of manual system …

As production system estates become larger and more complex, ensuring stability through
traditional monitoring approaches becomes more challenging. Rule-based monitoring is …

Anomaly detection on discrete sequential data has been investigated for a long time
because of its potential in various applications, such as detecting novel attacks or abnormal …

In large-scale distributed systems with multiple interconnected modules, failure of even a
single module might have a cascading effect and might result in overall system failure …