Indian Journal of Science and Technology

Abstract

Objectives: To find an effective way to find Suspicious Behavior on Terrorism Using NLP in Social Networks with Single Sign-On in advance and prevent the massive destruction of life and property. Methods/Statistical Analysis: A survey has been made to understand the behavior of people using the social networking. Social networking has seen a massive growth for more than a decade and popular among people. So, taking this into consideration it aim at developing a monitoring system which continuously monitors user activity in the social network to find any suspicious activity regarding terrorism. Natural Language Processing Technique is used for analyzing the text data and Least Significant Bit algorithm is used for Steganographic images. Findings: In our research work, we have considered two social network sites - Gmail and Twitter. We work on real time dataset fetched from Gmail and Twitter. These social networks are continuously monitored for user behavior. The user data from Gmail inbox, sent items, tweets, sent and replied twitter messages are fetched and passed to Natural Language processing to extract the data patterns related to terrorism. Based on the threshold of terrorism related data, the user behavior would be classified as normal, little suspicious and offensive. It considers a single sign on of the user into social network. It has considered the user activity in two social networks to get a precise data. There are existing works analyzing on user sentiments, sarcasm, psychological effects, political, expert advice, and recommendations on user ratings. To my knowledge there is no work done on analyzing user data on more than one social network on text and image data to find their suspicious behavior on terrorism. Application/Improvements: In our application, we are using the real data set of the users from Gmail and Twitter account using single sign on. The work is to analyse both the users text information and image shared via Gmail to find the suspicious behavior on terrorism and categorize them to normal, little suspicious and offensive. This information can be shared with the investigation team, where they can take any precautionary action preventing the world from massive destruction of life and property.

Keywords: NLP, Single Sign on, Social Network, Suspicious Behavior, Terrorism