Course Syllabus

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Course Logistics

Course Numbers

EECS 221 / NETSYS 270
Instructor Athina Markopoulou
Teaching Assistant
 Hao Cui (cuih7@uci.edu)
Lectures

When: Tue, Thu, 11:00AM-12:20PM

Where: SSTR 101 and on Zoom (link provided in Canvas page)

Videos will be recorded and will be posted along with the slides.

Office Hours

Athina: Wed 2-3pm, in person (EH 5428) and on Zoom (see Canvas page)

Hao: Mon 1-2pm on Zoom, Tue 1-2pm in person (ISEB 6400)
Textbook No textbook. Please see Schedule and Modules.
Prerequisites:

Familiarity with networking (e.g. HTTP, web), mobile devices, and data science concepts  would be a plus when picking a project. Willingness to do a PhD-level research project.

 

Course Description

We are moving rapidly towards a highly connected, data-rich world, where people and spaces are continuously monitored and controlled via mobile and IoT devices. Smartphones, with their seamless connectivity and access to sensors and personal data, leave rich digital traces of user activity in the physical and online world. Likewise, smart homes, offices and public spaces are increasingly equipped with IoT devices that communicate among themselves, the cloud and their operators, and they sense/actuate various aspects of the environment. On the positive side, data collected from mobile and IoT devices provide utility: a wide range of services for individuals, value for private companies, and benefits for communities, cities, and the society as a whole. On the downside, collecting sensitive data from these devices and sharing them among different entities poses significant privacy and data transparency challenges that can only be addressed through a combination of technical and policy solutions. 

This course is intended for PhD or MS students, who are interested in doing research in the area of privacy and data protection, with a special focus on data generated by of mobile and IoT devices. 

The course will expose the graduate students to selected advanced topics in this area, including basic concepts in privacy and data transparency, their applications to real-world devices and networks. In particular, we will cover the (1) theoretical frameworks of privacy (2) application domains and (3) privacy and data protection law/policy. The Modules tab provides references per topic (continuously updated). The exact papers to read for the lectures will be a subset of those, as specified in the schedule and modules. Along the way you will get exposed to various tools including: web developer tools, wireshark, and tensorflow, The course will train the students in graduate research: reading and discussing cutting edge  papers; defining and carrying out their own research project that should lead to a workshop-quality paper; communicating through presentations and technical papers. 

Deliverables and Grading

Deliverable What Grade % When
Class Participation in class +10% throughout quarter
Lecture Quiz 20% posted after lecture, due by Fri noon
Exams Module  Mini-Exams 40% at the end of every topic/module 
no final or midterm
Project Project Proposal Presentation 10% 4th week of quarter: Thu 4/27
Project Presentation 10% instead of final, Tue 6/13
Project Writeup 20% by the end of finals week, Fri 6/15

More specifically:

  • Class: In every lecture, we will have typically one main paper assigned, maybe two if we want to contrast them; and a few related (optional) ones.  The instructor (or a guest lecturer) will give the lecture on this topic.
    • Lecture Quizzes (20%): There will be one quiz per lecture, to help you keep up with the pace of the lectures. The quiz will be posted after every lecture and will be due by the end of that week: Friday noon. Correct answers will be released on Friday 12:30pm.
    • In-class participation (+10%): Participate in the discussion during class, or research a topic that comes up.  You are welcome/encouraged to read the main/assigned paper in advance.
  • Module mini-exams (40%): At the end of every topic/module, we will have a mini-exam, which will be taken online and at home, typically over a time period of 1-3 days. This will be more substantial than the quizzes. Think of it as a homework or a take-home exam for that particular module. There will be no final exam.
  • Projects (40%):  You will define and carry out a research project, equivalent to a workshop paper. The instructor will propose a list of projects but you can also suggest your own. You should complete your project in groups of two. Ideally, your paper should be of publishable quality to a workshop, in which case, I will help you submit it and will sponsor your expenses for presenting it.  Project timeline and milestones:
When What To Do about the Project
immediately form team, read references, talk to instructor, define project
Thu 4/27 project proposal (5min) presented in class + proposal (ppt) due
Tue 6/13 final project presentation in class
Fri 6/15 final project report (workshop paper format - 6pp)
throughout the quarter talk to your instructor / TA for feedback

Policies

  • Late policy: 
    • No late or skipped lecture quizzes. 
    • No late take-home mini-exams should be completed within the assigned time only. No late submissions can be accepted, because the solutions will be posted shortly after the deadline. To give you some flexibility, your submission with the lowest grade (including 0 for a missing one) will be dropped. This means that you can skip one module mini-exam without asking permission.
  • Honor Code:
    • You should do your quizzes and mini-exams on your own.  
    • For the projects, you can use publicly available materials as long as you give proper reference. No plagiarism.
    • Students involved in cheating will get 0 grade and will also be subject to the rules of UCI Academic Honesty Policy.
  • Attendance of lectures is encouraged but not mandatory - it is up to you to keep up with the materials. You do All materials, including recordings of the lectures, will be posted online. 

Course Summary:

Date Details Due