Investigation of user vulnerability in social networking site

Abstract

The vulnerability of the social network users becomes a social networking problem. A single vulnerable user might place all friends at risk therefore, it is important to know how the security of the social network users can be improved. In this research, we aim to address issues related to user vulnerability to a phishing attack. Short text messages of the social network site users were gathered, cleaned and analyzed. Moreover, phishing messages were build using social engineering methods and sent to the users. K-means and Mini Batch K-means clustering algorithm were evaluated for the user clustering based on their text messages. A special tool was developed to automate the users clustering process and a phishing attack. Analysis of users responses to the phishing messages built using different datasets and social engineering methods was performed, and corresponding conclusions about user vulnerability were made.