Overview

"What are the classic and recent research in computer security?"

If you ever asked this question at least once in your life, this course is for you.

This is a graduate course, designed to provide a comprehensive overview of the classic and recent research in computer security. The course will also cover the following topics:

• Network/Internet security
• Computer systems security
• Isolation and (software-induced) breaks
• Software/web security
• Trustworthy ML

The course activities are organized to achieve the following learning objectives:

• [Security] To learn how to think like an adversary.
• [Research] To learn emerging attacks and defenses.
• [Research] To learn how to pursue a research problem and communicate your research findings with others.
• [Practice] To have hands-on experience by implementing security mechanisms.

Latest Announcements

• 09/23/26: The first class (Wed. 09/23) is ONLINE. Please check the Zoom link on Canvas before the first class.
• 09/23/26: You MUST form a team and sign up for the in-class presentation on the Google Sheet [link] by 09/30.
• [Active] 09/23/26: All Wed. sessions are online (Zoom; link on Canvas); Final term-project presentations (12/02) will be in person.
• 09/23/26: Welcome to CS 578 Cyber-Security (Fall 2026)!

Course Policy

The University's Code of Academic Integrity applies, modified as follows:

[Dont's]

• Do NOT share your code or write-up with others.
• Do NOT copy and paste someone else's code or write-up in yours.
• Do NOT ask for the solutions on the Internet.

[Do's]

• Brainstorm your ideas with other students.
• Discuss and explain your solutions with other students.
• Discuss the problems and concepts for the team project.
• Collaborate with your team-members to run experiments for the team project.

Must: Please write down the students' names if you received any help from them. It won't affect the scores for your critiques or projects. But, you will learn from this practice how to credit others for their services. It is an essential skill when you collaborate with others in the future.

AI Policy

The default in this course is that you do not use generative AI, and you must be able to explain and defend anything you submit.

• Critiques: do NOT use AI to read, summarize, or write them. Polishing grammar in writing that is already yours is fine. Idea-level use—the summary, contributions, strengths and weaknesses, or opinions—earns 0 pts and is reported to the School of EECS.
• Final exam and term project: do NOT use AI. You are responsible for what you submit—"the AI produced it" is no defense if the text, code, or results are wrong or fabricated.
• Disclosure: if you used AI at all, you MUST say so in your submission: the tool, the interactions, and what portion of the work it contributed to. Undisclosed use earns 0 pts for that component and is reported to the School of EECS.

Unauthorized AI use may constitute plagiarism, cheating, and/or falsification under the University's Code of Student Conduct. If you are unsure whether a use is allowed, ask before you use it.