Statistical Authentication Technique for Facebook using Social Network Analysis

Abstract

People spend the majority of their browsing time on social networking sites (SNS) like Facebook, Twitter, WhatsApp, and others in the modern world, which increases the magnitude of sensitive personal information that is shared online and spreads quickly. One among the many threats that internet criminals bring about that must be avoided is the development of fictitious Facebook profiles. The human brain has the most powerful capacity for forming decisions based on social contact, visual signals, contextual information, and spatiotemporal data. To enhance the functionality of the current biometric system, an automated intelligent biometric system is built in this research considering the social behavioral traces found on online social networks (OSNs). These traces are dependent on human thinking ability. This technique is employed to establish unique Facebook accounts. Results from an experiment using the Facebook database showed a genuine acceptance rate (GAR) of 99% and a false acceptance rate (FAR) of 1.6% with 99% accuracy.