Science of Cyber Security

Catalog description

This course focuses on techniques that approach cyber security problems in a principled manner using concepts from machine learning/artificial intelligence, formal methods, program analysis, and psychology. The intent of this course is to permit students to bridge the divide between real-world cyber threats and formal, scientific foundations of solutions that address such threats. Real-world cyber security issues, such as buffer overflow attacks, privilege escalation attacks, phishing attacks, SQL injection attacks, and DDoS attacks, are used to illustrate how cyber threats can be modeled with abstract representations that are amenable to rigorous analysis and formal reasoning. The course also emphasizes the development of preventive, detective, and deception defense mechanisms that are rooted in scientific foundations. In addition, learning activities may incorporate artificial intelligence or generative AI tools to explore topics such as spam and phishing detection, cyber threat modeling, and the analysis of attack patterns in social networks, helping students connect theoretical concepts with modern cybersecurity practices. Prerequisite: CS 350 and CS 375 or equivalents. Typically offered every semester, at least once every academic year.