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Graduate Projects


Project ID: 452
Author: Saikumar Reddy Katkoori
Project Title: Malware Alert System for Online Social Networks- Case Study Selected is Twitter
Semester: 2 2015
Committe Chair: Dr. Mario Garcia
Committee Member 1: Dr. David Thomas
Project Description: Online social networks (OSNs), such as Facebook and Twitter, allow users to tweet or post short update messages reporting on their daily activities. The proposed system provides a platform to alarm against the spread of new malware attacks such as viruses, worms, or Trojan horses using the OSNs. Currently, network administrators and operators use manual and traditional ways of communication, such as phones and e-mails to warn each other against such attacks. Instead, a prototype system is proposed that mines Twitter posts to provide real-time alerts of malware propagation (Twitter is taken as our target to implement this system). The system is composed of four important modules: a) Data extracting where system continually and periodically queries Topsy’s APIs (mechanism to get twitter logs) for specific keywords such as Malware, backdoor, and cyber-attack then returns the results in JSON format. b) Data filtering system that extracts the tweets that contain one of the following phrases: computer security, new, discovers, hit, infect, warn, and watch out. c) Smoothing the data implement “Exponentially Weighted Moving Average (EWMA) algorithm and Exponentially Weighted Moving Variance (EWMV)”, which identifies threshold based on time intervals associated with the keywords. d) Finally, a malware alert is triggered when the actual number of tweets in a given interval exceeds the threshold value.
Project URL:   452.pdf