Class Times: Mon&Wed 4:00-5:15pm

Classroom: Lind Hall 303

3 credits, A-F only

Overview

This course covers the state of the art (sometimes, basics) in computer security and privacy. Lectures are mainly based on recent research papers, which cover threads, attacks, and mitigations in computer security and privacy. While offering research advances in systems security, this course will also provide students with practical solutions to certain security and privacy issues. In addition, students are expected to conduct a course project related to the covered topics.

The course is designed to be student-driven and interactive. The classes would be based on student presentations of selected research papers with an emphasis on class discussion. Students will also be given assignments (e.g., writing paper critiques). In addition, there would be a semester-long course project to be done in groups of 1-2 students, with multiple milestones along with a final report and presentation.

The covered topics include: software security, OS security, malware, cloud security, mobile security, IoT security, hardware security, web security, social engineering, diffeerntial privacy, blockchains, and machine-learning security.

Textbook

No required textbook; the course material would be based on recent research publications in top security and privacy conferences, workshops, and journals, as well as technical articles and blogs. However, one recommended book (free online) is:

Ross Anderson's Security Engineering, Second Edition (John Wiley & Sons, 2008 or online at the author's web page)

Prerequisite

C or C++ programming, operating systems (e.g., CSCI 5103 or 4061), networks (e.g., CSCI 5211)

Office hours

  • Office hours: MW 5:20-6:20pm at Keller Hall 5-217
  • No TA

Who should take this class?

This class is primarily intended for PhD students (motivated seniors and MS students are also welcome!) who want to learn about the latest research advances in computer security and privacy.

Grading policy

The course does not have exames. Grading is based on the following components.

Note: late submissions are not allowed in this course

  • Paper presentation, writing critiques, and discussion (40%)
    • Reading: answers and critiques (10%)
    • Class attendance and discussion (10%)
    • In-class paper presentations (20%)
  • Course project (60%)
    • Proposal (5%)
    • Demo & presentations (20%)
    • Write-up & code (35%)
  • We follow the cheating policy (read UMN's STUDENT CONDUCT CODE).