Advance Identification of Cloning Attacks in Online Social Networks

Abstract

Online social networks (OSN) have changed the way individuals collaborate and convey to reconnect with old companions, acquaintances and set up new associations with others considering leisure activities, interests, and fellowship circles. Shockingly, the member's lamentable acknowledgment of reckless conduct in sharing data, often worthless safety efforts from part of the framework heads and, at last, take advantage of the distributed data in Online Social networks as an intriguing objective to attackers. As OSN is becoming increasingly popular and identity cloning attacks (ICA) mechanism designed to fake the identity of users on OSN is becoming one significant growth concerns. This attack has been seriously affected the victims and other users to establish the relationship of trust, if there is no active application defense. In this paper, the first step analyzes the member constraints and characterize the profiles based on their behavior. Then focusing on the categorized profiles of the framework and verify each of them using their area of interests. To detect suspicious identities, two methods are followed based on attribute similarity of profiles and by verifying similar profiles in a cross-site environment by their area of interests.