Detection of Identity Theft over Social Medial Networks using Fuzzy Logics

Abstract

Social media networks (SMNs) have become a norm in everyone’s life and significance for the interrelationship amongst people all over the world. This is the reason theft of individuals’ identity has become very common. In order to detect identity theft, my research proposes fuzzy logic-based system and decides based on results if a person is being an identity theft victim. To do so, the natural language and numerical values of each user is considered, with the help of values such as the total frequency of posts, messages, new recipients, and geo locations. Fuzzy logic idea has been proposed before to detect identity theft in SMNs but with no actual implementations and idea was taken forward with limited number of parameters. In our paper the accuracy increased by taking more parameters into consideration.