A large-scale network-oriented traffic real-time monitoring analysis method and system
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI FUHUA NETWORK TECH CO LTD
- Filing Date
- 2026-05-28
- Publication Date
- 2026-07-24
AI Technical Summary
Existing traffic monitoring and analysis methods struggle to accurately identify abnormal traffic events in large-scale networks without relying on prior knowledge of attacks. In particular, they are easily overwhelmed by normal background traffic during periods of low traffic density and short-term sudden abnormal behavior. Furthermore, traditional methods ignore the dependency relationship between the packet length and arrival interval of adjacent data packets within the traffic flow, leading to the failure of abnormal traffic event localization.
By dynamically segmenting time based on the five-tuple information and timestamps of traffic data packets, a state transition code is constructed. The direction of packet length change and the direction of arrival interval change are used to characterize the traffic behavior pattern. Node state deviation analysis is performed by combining the global observation matrix and the historical baseline feature matrix to achieve the location constraint of abnormal traffic events.
Without relying on prior attack knowledge, it can accurately segment traffic behavior fragments, capture hidden abnormal features, enhance the sensitivity of anomaly identification, realize global observation of large-scale networks, reduce the false judgment rate, quickly locate the anomaly initiating node and restore the propagation path, and meet the needs of traffic operation and maintenance.
Smart Images

Figure CN122293501B_ABST