Botnet Campaign Detection on Twitter

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Fields, Jeremy
Sengupta, Saumendra; Adviser
White, Joshura; Reviewer
Spetka, Scott; Reviewer
botnet activity , Twitter , Social Media Networks
The goal of this thesis is to investigate and analyze botnet activity on social media networks. We first start by creating an algorithm and scoring method for “likely bots,” and analyze them in conjunction with their neighboring messages to determine whether there is a likely group of bots, or botnet. Chapters 1 & 2 cover the overview of the work, and the previous research done by others. Multiple datasets were collected from Twitter, over different time frames, including random samples, and targeted topics. Chapters 3 & 4 cover the methodology and results of the approach using these datasets. The method is shown to have high accuracy.
Master of Science Thesis in Computer and Information Sciences Department of Computer Sciences, SUNY Polytechnic Institute. Approved and recommended for acceptance as a thesis in partial fulfillment of the requirements for the degree of Master of Science in Computer and Information Sciences.