An Alert System Based on Shared Score for Online Social Networks

Abstract

In recent years, the usage of Online Social Network's(OSN's) has increased in an unprecedented rate. OSN integrates an enormous number of Third Party Application (TPA)services to provide enhanced service set to the users. When users uses the application for the first time, they have to agree to share their profile content requested by the service providers otherwise, the service would be denied to the user. The users are not aware of the attributes that are really required for the application to function and extent of the personal data that they share with the third party applications. In the virtue of accessing the service, most of the time, the user simply agrees to share the attributes requested by the third party applications. The main focus of the paper is to mark the gap between the user's attitude and user's actual behavior of sharing. We estimate the measure of the sharing score of the user, based on what they actually share and compare it with the users preferred privacy score collected from the user through a questionnaire and intimate the user about the gap in the actual and user preferred share score. The list of applications and a score for each application are presented to the user. The score is calculated based on extent of the data the application accesses. The applications are classified into good, satisfactory and bad. Based on the classification emojis are displayed along with the score to help the users in understanding the reason for their over share.