Data Analytics for Cybersecurity

Catalog description

Credits 3. 3 Lecture Hours. Theoretical foundations, algorithms and methods of data analytics for cybersecurity; study of data analytics including cluster analysis, supervised machine learning, anomaly detection, and visualization applied to cyber attacks, anomaly detection, vulnerability analysis, strategic manipulation, propaganda and other topics. Prerequisites: Grade of C or better in CSCE 221 ; grade of C or better in ECEN 303 , STAT 211 , STAT 301 , STAT 302 , or STAT 303 .