CE 40-815: Secure Software Systems

Sunday/Tuesday 900-1030
Room: TBD



TAs:                    Zahra Fazli   
                           Mohammad Haddadian  



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Description:

This graduate-level course on secure software systems is presented in three parts: classical attacks and defensive mechanisms, the impact of AI on vulnerability detection and causal analysis, and recent advancements in AI-driven approaches for securing software systems:

Part 1: Classical Attacks and Defensive Mechanisms
In the first part, the course covers classical attack techniques such as Buffer Overflow, Format String Vulnerabilities, Return-Oriented Programming (ROP), and other related threats. It also explores run-time protection mechanisms like Taint Tracking, Control Flow Integrity (CFI), and Causal Analysis, along with techniques for code analysis, including Static Analysis, Symbolic Execution, and Fuzzing. The initial syllabus for this part draws inspiration from the Secure Software Systems course taught at Carnegie Mellon University (CMU).

Part 2: Part 2: AI in Vulnerability Detection and Causal Analysis
In the second part, the course focuses on how AI is transforming two key areas of vulnerability detection and causal analysis. Topics include AI-driven methods for identifying security vulnerabilities, predictive analytics in threat detection, and enhanced causal analysis through machine learning models. This section highlights the growing role of AI in automating and improving these crucial areas of secure software systems.

Part 3: AI-Driven Advancements in Secure Software Systems
In the third part, the course examines recent research papers published within the past few years, specifically focusing on how AI has contributed to enhancing secure software systems. We will explore AI's role in automated vulnerability detection, software patching, security auditing, and defensive mechanisms tailored to software systems. This part emphasizes state-of-the-art developments in AI-driven techniques that address security challenges in software engineering.


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Course Material:

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