Application of Machine Learning and Crowdsourcing to Detection of Cybersecurity Threats

We are applying machine learning and crowdsourcing to cybersecurity, with the purpose to develop a toolkit for detection of complex cyber threats, which are often undetectable by traditional tools. It will serve as an “extra layer of armor” that supplements the standard defenses. The initial results include (1) an architecture for sharing security warnings among users and (2) machine learning techniques for identifying malicious websites. The public release of the developed system is available at http://cyberpsa.com. This project is part of the work on advanced data analysis at the CCICADA Center of Excellence.