An approach for detecting profile cloning in online social networks

Online social networks (OSNs) are websites that allow users to build connections and relationships to other Internet users. Social networks store information remotely, rather than on a user´s personal computer. They can be used to keep in touch with friends, make new contacts and find people with similar interests and ideas. Nowadays the popularity of online social networks is growing rapidly. Many people besides friends and acquaintances are interested in the information people post on social networks. Identity thieves, scam artists, debt collectors, stalkers, and corporations looking for a market advantage are using social networks to gather information about consumers. Companies that operate social networks are themselves collecting a variety of data about their users, both to personalize the services for the users and to sell to advertisers. The concern of leakage of privacy and security is extremely growing in social networks in these days .The identity theft attacks (ICAs) by creating clone identities in OSNs try to steal users´ personal information and nowadays it is very important in cyberspace. If no protection mechanism is applied it effects on users´ activity, trust and reliance relations that establish with other users. In this paper, first profile cloning and identity theft attack are introduced, and then a framework for detection suspicious identity is proposed. This approach is based on attribute similarity and friend network similarity. According to similarity measures which are computed in each step and by having predetermined threshold, it will be decided which profile is clone which one is genuine.