Prediction of Malware Propagation and Links within Communities in Social Media Based Events

Abstract

This paper is aimed at studying malware propagation on social media and community link prediction. Twitter is taken as the social media platform and data is collected using Twitter4j and MongoDB. A high interaction client honeypot is used to classify benign and malicious URL's. The retweet volume and links between the users are then analyzed. Further to this, the work aims to detect communities that arise from these links between users with the help of BIGClam algorithm.