Nowhere to hide: Anonymous User Recognition Based on Multidimensional Trajectory Set

Abstract

Abstract Anonymous user identification is one of the core issues in the field of information security and e-commerce applications. Accurately identifying the implicit characteristics of users’ online behavior and the unique identity is important, it has theoretical significance and commercial application value. Based on Massive online clickstream data, this paper proposed AUI algorithms and multidimensional trajectory set model (MTS) to verify the feasibility anonymous user identification. Through the AUI algorithm and vectorization method, a unique multidimensional trajectory set is created for each user. Experiments show that compared with the decision tree and user document methods, the multidimensional trajectory set based on the click data stream has improved the accuracy of recognition and provides an effective solution for user recognition.