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Oct 17, 2026
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2026-2027 University Catalog
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CS 52900 - Security Analytics
Credit Hours: 3.00. This course focuses on the fundamentals at the intersection of security and artificial intelligence (AI), including machine learning (ML) and deep learning models. The first part establishes a principled understanding of key AI algorithms, dataset analysis, and the application of these models within the security domain. This foundation prepares students for the second half of the course, which examines the security implications of AI deployment in real-world systems. It covers attacks against computer systems that use these algorithms, as well as defense techniques to mitigate such attacks. Students will design and apply AI to security tasks, assess threats against AI systems, and gain practical experience with common attacks and defenses. Upon course completion, students will have a broad understanding of AI and information security. The focus is on data analysis, the application of AI algorithms for security tasks, security and privacy attacks, defenses for AI-integrated systems, and the impact of these security issues on real-world systems.
Learning Outcomes
1. Explain foundational artificial intelligence (machine learning and deep learning) paradigms and outline their mathematical principles, strengths, and limitations. 2. Explain the application of such paradigms to complex security problems. 3. Utilize state-of-the-art libraries to construct, deploy, and evaluate models for security tasks. 4. Evaluate the effectiveness and systemic limitations of artificial intelligence approaches in diverse security contexts. 5. Explain security and privacy attacks against AI-integrated systems and taxonomize them according to their threat models. 6. Evaluate defense mechanisms against adversarial attacks and justify the necessity for robust and secure systems.
Credit Hours: 3.00
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