Information Leakage Tracking Algorithms in Online Social Networks

Aim: To explore information leakage tracking algorithms in online social networks and solve the problem of information leakage in the current online social network, a deterministic leaker tracking algorithm based on digital fingerprints is proposed. Background: The basic working principle of the algorithm is that the platform uses plug-ins to embed unique user-identifying information before users try to obtain digital media such as images and videos shared by others on the platform. Objective: Because the scale of users in social networks is extremely large and dynamic, while ensuring the uniqueness of digital fingerprints, it is also necessary to ensure the coding efficiency and scalability of digital fingerprint code words. Methods: Simulation experiments show that 10 experiments are performed on 10,000–100,000 nodes, the Hamming distance threshold is set to 3, and the length of the hash code and the binary random sequence code are both 64 bits. Results: The proposed digital fingerprint fast detection scheme exhibits better performance than conventional linear search. Conclusion: An index table based on hash code and user ID is established and combined with community structure to improve the detection efficiency of digital fingerprints.