Abstract. With the arrival of online social networks, the importance of privacy on the Internet has increased dramatically. Thus, it is important to develop mechanisms that will prevent our hidden personal data from unauthorized access and use. In this paper an attempt was made to present a concept of profile cloning detection in Online Social Networks (OSN) using Graph and Networks Theory. By analysing structural similarity of network and value of attributes of user personal profile, we will be able to search for attackers which steal our identity.

The paper presents a method, based on graph and network theory, which allows to detect cloned user profiles on Online Social Networks. Moreover, an idea of similarity containers, which gives an opportunity to incorporate importance and context of data into a model, was introduced. The presented solutions were adapted to the idea of simulation environment, which will allow to detect a profile cloning process before that activity will be completely performed by an attacker. Keywords: Online Social Networks, user profile cloning, violation of privacy on the web.

Due to the emergence of online social networks, the importance of privacy on the Internet has vitally increased. Thus, it is important to develop mechanisms that will prevent our hidden personal data from unauthorized access and use. In this paper an attempt was made to present a concept of profile cloning detection in Online Social Networks (OSN) using Graph and Network Theory. Compering values of attributes of users’ personal profiles and analysing structural similarity of networks, we identify attackers which steal users’ identity.