IS/CS 698 - Human Factors in Security & Privacy - Spring 2024
This course is aimed at graduate students and is offered at the graduate (600) level. However, it may be appropriate for some undergrads with a strong background and motivation. If that is you, please email me, far in advance, with your rationale, and we can explore available options.
Logistics
We will meet Mondays and Thursday, 11:30–12:50, at Faculty Memorial Hall (FMH) 307.
The CRN for the IS section of this course is 15977; for CS it’s 15978.
Peer courses
This course is inspired by courses including:
- UC Berkeley Cybersecurity 215
- Brown University CS 1360
- University of Chicago CMSC 23210/33210
- Carnegie Mellon University 17-334
- Duke COMPSCI 590
- George Washington University CSCI 3907/6907
- University of Illinois Urbana-Champaign CS 598-CAC
- University of Maryland CMSC 732
- UNC Charlotte ITIS 6420/8420
- Pomona College CS181W
- Tufts University COMP 152
Learning outcomes
Students completing this course will:
- Learn concrete instances of security and privacy failures in common technologies
- Be able to explain how human factors contributed to these issues
- Read and understand current research in usable privacy and security
- Learn and practice methodologies for evaluating the usability of systems
- Be able to practice human-centered design for security and privacy systems
Topics overview
This course (and website) are under development. The content may change before the beginning of the course.
The course will cover topics including:
Methods
- Experimental design
- Statistics
- Surveys
- User studies
- Interviews
Security
- Warnings and phishing
- Mobile permissions
- Authentication
- Access control
Privacy
- Definitions of privacy
- Deceptive design patterns
- Privacy policies
- Social media privacy
- Smart home privacy
Special populations
- At-risk users
- Developers
- Children
- Accessibility in security
- Anonymity needs and tools
Prerequisites
Students enrolling in this course are expected to have a background in security and foundational computer science skills. Experience with statistics and user experience research or design is welcome but not required. You can read a more detailed explanation of the course’s prerequisites here.