Anomaly detection is a method of detecting patterns in data that do not conform to expected behavior, often indicating unusual or suspicious activity. This research area involves developing algorithms and techniques to identify anomalies in various types of data, such as network traffic, financial transactions, or sensor readings. Anomaly detection is commonly used in fraud detection, cybersecurity, and predictive maintenance to identify potential threats or malfunctions. Researchers in this area work to improve the accuracy and efficiency of anomaly detection systems to effectively detect and respond to abnormal behavior in real-time.