Robust system detector for identity clone attack on Facebook platform

We are living in the age of social networks where folks are connected through social media. Examples of social media include Twitter Facebook LinkedIn and Myspace. Sometimes social media is not used in the intended way which puts user data on security risks. This research thesis discusses a detection system for a special kind of security attack in which a fake user represents himself as a valid user and leaks other users’ personal information. This kind of attack is known as Identity Clone Attack (ICA). We have introduced a novel technique of Clone Profiles Detection (CPD) that is a three steps approach which is based on similarity measure IP address checking and behavioural model detection. This technique alerts a user and his friends in case of an identity clone attack and decreases the vulnerabilities of identity clone attack. Facebook graph APIs have been used for accessing Facebook users’ profile for experimentation purposes. Experimental tests produced promising results.