Network social media information leakage detection based on link state awareness
Qi Ding, Guangming Dai · International Journal of Web Based Communities · 2022
Aiming at the problems of low detection accuracy and long detection time in traditional information leakage detection methods, this paper proposes a network social media information leakage detection method based on link state perception. Divide the data stream segments, extract the data features of the divided data stream segments, regard the extracted data features of network social media information as the nodes in the social network link, and obtain the node status information by calculating the loss rate and occupancy rate. The distributed heuristic reasoning method is used to perceive the node state information. Then, the link state is calculated according to the perception results. Finally, the network social media information leakage detection model is constructed. According to the simulation results, compared with the traditional method, the proposed method has higher accuracy and shorter detection time.