Information Leakage Tracking Algorithms in Online Social Networks

Abstract

Aim: In order to explore the study on information leakage tracking algorithms in online social networks, solve the problem of information leakage in the current online social network. a deterministic leaker tracking algorithm based on digital fingerprints is proposed Background: : First, the basic working principle of the algorithm is that the platform uses plug-ins to embed a unique user-identifying information before users try to obtain digital media such as images and videos shared by others on the platform. Objective: Secondly, 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 to 100,000 nodes, the Hamming distance threshold d is set to be 3, and the length of the hash code and the binary random sequence code are both 64 bits. Results: Compared with the traditional linear search, the proposed digital fingerprint fast detection scheme has better performance Conclusion: It is proved that an index table based on hash code and user ID is established and combines with community structure, to improve the detection efficiency of digital fingerprints