A Comprehensive Detection Framework That Protects End Users from Fake News

2020-2021
In partnership with

Team Members

Dr. Anwar Haque
Dr. Anwar Haque PI
Evangelos Makris
Evangelos Makris

Summary

With the constant advancements in technology, more consumers are turning to the internet for news consumption. This in turn has come with the rise of Fake News on the internet. Sources flood the internet with fake media everyday which poses a potentially dangerous security risk to consumers who a can’t differentiate fake and real news. Our research objective is to design a comprehensive semi-automated framework that can help a user detect Fake News and protect themselves from it. The framework should be designed with deployment on end systems in mind. The ideas underlying the research is how Fake News is developed and distributed, how the threat of it poses a risk to consumers, and how a consumer may want to use a framework to help identify Fake News. We will analyze the efficacy of current Fake News detection systems in order to develop an effective framework which can detect Fake News on end users’ systems. The research will look at current Fake News events including the COVID-19 pandemic.

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