Traffic abnormality detection system based on grey LOF (Live Object Framework), and detection method thereof

The invention relates to the technical field of traffic abnormality detection, and particularly relates to a traffic abnormality detection system based on grey LOF, and a detection method thereof. The traffic abnormality detection system based on grey LOF collects an original data traffic package by an information collection module; the data is preprocessed by a data cleaning technology; a high-associated field of each traffic data package is extracted and concluded as a detection data source; by adoption of a grey level theory, the data provided by the information collection module is analyzed and prejudged through a grey distinction module, so as to greatly reduce the data computing scale, reduce the time complexity of an LOF algorithm, and improve the timeliness; the abnormality degree of the data traffic package is computed through an LOF analysis module; and, based on the density, a separation degree between each traffic package and a nearby traffic package is detected and computed. By adoption of the sy