Session-VC: Machine Learning for Sys, Networks, and Security
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Instructor: Varun Chandrasekaran (varunc@illinois.edu)
TA: TBD
Time/Location: Tuesdays & Thursdays 12:30 – 1:45 PM, Siebel Center for Comp Sci Room 0218
Office Hour: By Appointment
Announcement
01/20/2026: Enrolled students will be added/invited to CS 562 Campuswire before the first week of the class. If you registered during/after the first week and did not get the Campuswire invitation, please email the instructor (varunc@illinois.edu) for the invitation code, or better yet, click on the Campuswire tab at the top of the page.
Class Description
This course is a research-focused survey of security, robustness, and governance challenges in modern machine learning, with an emphasis on adversarial interactions with learning systems. The course covers both established and emerging threat models, examining how machine learning systems can be attacked, audited, manipulated, and modified.
Topics include evasion and poisoning attacks, jailbreaking and safety training, membership inference and model extraction, and the limits of explanations and interpretability under adversarial pressure. A substantial portion of the course also focuses on challenges unique to foundation models and large language models, including LLM poisoning, watermarking and detection, attacks on LLM watermarks, machine unlearning, and copyright and data provenance. The course also examines emerging issues around agentic systems and models that interact with external tools or environments.
Students will read, present, and critically evaluate recent research papers, write structured paper summaries in response to instructor-provided questions, and complete a semester-long team project selected from instructor-provided topics.
Expected Work
Reading: Students are expected to read the assigned papers before each class meeting and submit a short response to instructor-provided guiding questions via the following Google Form: https://forms.gle/cpRkxyc43pCG2Nwi8. You must be signed into Google using your Illinois (@illinois.edu) account in order to submit the form.
The response should be at most one page long and written clearly and concisely. If mathematical expressions, equations, or formal notation are needed, the response should be rendered appropriately using LaTeX. Submissions must be uploaded as a single PDF file; the form will only accept PDFs of size less than 1 MB, so students should plan formatting and figures accordingly. Responses are due at 11:59 PM (CT) on the day before class.
Use of AI tools (e.g., large language models) is permitted for editing, polishing, or clarifying written responses, but the content must reflect the student’s own understanding of the paper. Students are responsible for the correctness and originality of all submitted material; AI tools should not be used to generate responses without genuine engagement with the reading.
In-Class Quizzes: Short, handwritten quizzes will be administered at the beginning of some class meetings to assess basic engagement with the assigned readings. These quizzes will be based directly on the paper(s) assigned for that class and are intended to take no more than 5–10 minutes.
Quizzes are graded very leniently and are designed to encourage preparation and careful reading rather than memorization, or technical mastery, and to deter AI usage in the reading process.
Participation and Attendance: Students are expected to attend all classes and actively participate in discussion.
Paper Presentation(s): Students will present one or more papers during the semester to help lead class discussion. Presenters are expected to prepare their own slides and discussion prompts; use of the authors’ original slides is not permitted.
Team Project: Students will form teams of 3–5 students to work on a single semester-long research project. All projects must be selected from the instructor-provided list of project topics (see the Project link above). Teams will submit a ranked list of three project preferences, ordered from most to least preferred, by January 27, 2026, by email to the instructor. Each preference should be accompanied by a brief written justification describing the team’s interest and preparedness.
Project deliverables include:
(i) a project proposal,
(ii) a mid-semester progress presentation (15-25 minutes per team),
(iii) regular progress updates (including a biweekly 30-minute update with the instructor/TA,
(iv) a final in-class presentation (15-25 minutes per team), and
(v) a final written project report.Participation and accountability: For the class project, active participation from all team members is expected. Students will provide peer feedback on individual contributions, which will be factored into project grading.
Compute and Resources: Teams are responsible for securing the compute required for their projects. Projects are designed to be predominantly inference-only where possible. Available resources include DeltaAI at Illinois (for which the instructor can provide a letter of support) and Google Colab. The instructor has applied for Tinker credits and will distribute credits to the class if and when they become available.
Class Schedule
| Date | Week | Topic | Papers |
|---|---|---|---|
| 01/20 | 1 | Intro Week | |
| 01/22 | 1 | Intro Week (How to read a paper) | |
| 01/27 | 2 | Evasion | Main Supplementary |
| 01/29 | 2 | Poisoning | Main Supplementary |
| 02/03 | 3 | Jailbreaking (LLMs) | Main Supplementary |
| 02/05 | 3 | Poisoning (LLMs) | Main Supplementary |
| 02/10 | 4 | Adversarial Training | Main Supplementary |
| 02/12 | 4 | Safety Training (LLMs) | Main Supplementary |
| 02/17 | 5 | Membership Inference | Main Supplementary |
| 02/19 | 5 | Model Extraction | Main Supplementary |
| 02/24 | 6 | Membership Inference (LLMs) | Main Supplementary |
| 02/26 | 6 | Model Extraction (LLMs) | Main Supplementary |
| 03/03 | 7 | Explanations | Main Supplementary |
| 03/05 | 7 | Watermarking | Main Supplementary |
| 03/10 | 8 | Mid-term Project Update | |
| 03/12 | 8 | Mid-term Project Update | |
| 03/17 | 9 | Spring Break (no class) | |
| 03/19 | 9 | Spring Break (no class) | |
| 03/24 | 10 | Explanations (LLMs) | Main Supplementary |
| 03/26 | 10 | Watermarking (LLMs) | Main Supplementary |
| 03/31 | 11 | Faithfulness of Explanations | Main Supplementary |
| 04/02 | 11 | Attacks on Watermarks (LLMs) | Main Supplementary |
| 04/07 | 12 | Copyright | Main Supplementary |
| 04/09 | 12 | Unlearning | Main Supplementary |
| 04/14 | 13 | Copyright (LLMs) | Main Supplementary |
| 04/16 | 13 | Unlearning (LLMs) | Main Supplementary |
| 04/21 | 14 | Unlearning Evaluations | Main Supplementary |
| 04/23 | 14 | Agents | Main Supplementary |
| 04/28 | 15 | Final Project Update | |
| 04/30 | 15 | Final Project Update | |
| 05/05 | Last day of class (no class) |
Grading
- Project (proposal, progress updates, final presentation, final report):
45% - Paper presentation(s):
25% - Paper summaries:
15% - In-class Quiz:
10% - Attendance and participation:
5%
Policies
Late Policy
All deadlines are hard deadlines. For paper summaries and project-related assignments, submissions after the deadline receive half the credit. Late submissions are not accepted for the final project report.
Academic Integrity
Students must follow the University of Illinois guidelines on academic conduct (link). This course has a zero-tolerance policy for plagiarism. All submitted work may be subjected to automated plagiarism detection. When in doubt, consult the instructor.
When presenting papers, students may not use the authors’ slides directly.
Fairness and Respect
This course is committed to providing a respectful learning environment for all students. Discrimination, harassment, or exclusionary behavior is not tolerated.
Special Accommodations
Students requiring accommodations should contact the instructor during the first week of class.
Diminished Mental Health
The University of Illinois provides confidential counseling and mental health services.
- Counseling Center: 217-333-3704, 610 East John Street Champaign, IL 61820
- McKinley Health Center: 217-333-2700, 1109 South Lincoln Avenue Urbana, IL 61801