Anomaly detectors are used to distinguish differences between normal and abnormal data, which are usually implemented by evaluating and ranking the anomaly scores of each instance. A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation.
To solve the problem, a research team led by Prof. Zhiwen Yu published their new research on 15 April 2023 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature.