Linking Virtual Identities across Service Domains: An Online Behavior Modeling Approach

Abstract

In the era of the Internet, people are active in multiple online services, and they usually have accounts on more than one online service. Each account is a virtual identity of the user. In order to trace individual's online behavior at any time and any places, linking virtual identities belonging to the same natural person across different online service domains is very important. Existing methods usually tackle this problem by estimating the profile content similarity between identities under two different online services. However, the profile contents in various online services are unreliable or misaligned, and the proposed methods are always limited to services in a specific domain. In this paper, we propose VISD (Virtual Identity linkage cross Service Domain), a novel probability-based model, to link virtual identities across online services in various service domains. It derives several significant attributes from users' online behaviors, such as IP address usage, various fingerprints of terminals, and leverages a supervised classification method to discover the relationship between two identities. By using real-world network traffic collected from a large province of southern China, we evaluate the VISD model and the linkage precision achieves 88.31%. The result demonstrates the effectiveness of our proposed model, which is helpful for social recommendations, information security and privacy protection.