Video traffic identification method and system based on Burst features, electronic equipment and storage medium

The invention provides a video traffic identification method and system based on Burst features, electronic equipment and a storage medium, and belongs to the technical field of log anomaly detection. Comprising the following steps: step 1, capturing video traffic, and preprocessing the video traffic; step 2, acquiring a Burst feature of the preprocessed video traffic and a time sequence feature corresponding to a Burst sequence; and step 3, taking data after Burst feature and time sequence feature extraction as fingerprints of a single video, and classifying the data so as to identify video traffic. According to the method, video identification is mainly carried out on a video stream transmitted by a video platform constructed based on a DASH protocol, secondary feature extraction is carried out through unique Burst features of each video, and time sequence features in a Brst sequence are analyzed. And a Light GBM model is created to identify the time sequence characteristics of a single video. The technical