CSC 495 - Privacy

Course Description

This course introduces data privacy in a broad sense, with the aim of providing students interested in pursuing privacy research an overview of challenging research areas and problems regarding privacy. This course will expose students to many of the issues that privacy engineers, program managers, researchers and designers deal with in industry.

There is no textbook for this course. We will use research papers as the main source of information. In each lecture, we will look at an interesting problem, its application areas, and possible solutions. Moreover, we will have case studies to investigate privacy incidents in more detail. Specifically, we will study the following privacy areas:

Web/Online Social Networks Privacy: We will look at growing privacy concerns in online social networks, sharing behaviors of users, common violations and regret scenarios, methods for targeted advertising and how to mitigate those, and k-anonymity for privacy of datasets.
AI for Privacy: We will look at privacy aware autonomous systems, investigate the design and maintenance of such systems using AI techniques such as negotiation and argumentation. We will investigate frameworks for elicitation, modeling, and verification of privacy requirements. We will look at privacy norms and investigate privacy breaches as norm violations.
Usable Privacy: We will look at various designs for usable privacy interfaces, privacy nudges for warning users of potential privacy risks, and semantic analysis of privacy policies.
Privacy Perceptions: We will look at studies and surveys regarding human mental models about privacy concerns, differences among cultures, and longitudinal studies about changes in privacy perceptions.
Misc Topics: We will look at additional topics such as crowdsourcing privacy policies, mobile application privacy, and privacy measurement.

Learning Outcomes: Students who complete this course will be able to

Understand personal identifiable information in databases and techniques to anonymize and protect such information
Describe attacks against anonymized datasets
Understand privacy risks when sharing personal data online and design mechanisms for mitigating such risks
Describe privacy requirements and AI techniques for designing privacy-aware autonomous systems
Design usable privacy interfaces and tools that balance privacy preserving and user functionality
Identify and describe important elements of privacy policies and regulations
Understand human attitudes to and perceptions of privacy

Fall 2017

Hours: MW 11:45AM-1:00PM

Location: EB2 1226

Grading

Assignments for this course include homeworks, case studies analyzed and presented in class, and a group project. There are no midterms or final exam.

30% - Individual homework assignments (4 best grades out of 5 assignments)

20% - One group case study (data collection, analysis, and in class presentation)

50% - One group project (project report and in class presentation)

CSC 495 - Privacy

Course Description

Fall 2017

Grading

Lectures

Course Introduction

Lecture 1: Introduction to Privacy (8/16/17)

Web/Online Social Networks Privacy

Lecture 2: Inference (8/21/17)

Projects (8/23/17)

Lecture 3: Sharing and Disclosure (8/28/17)

Homework 1 (8/30/17)

Lecture 4: Violations and Regret (8/30/17, 9/6/17)

Lecture 5: Targeted Advertising (9/11/17)

Homework 2 (9/12/17)

Lecture 6: K-anonymity (9/13/17, 9/18/17)

Artificial Intelligence for Privacy

Lecture 7: Privacy Requirements (9/20/17, 9/25/17)

Lecture 8: Agents and Reasoning (9/27/17)

Lecture 9: Privacy Norms (9/27/17, 10/2/17)

Homework 3 (9/27/17)

Lecture 10: Privacy Breaches (10/4/17)

Usable Privacy

Lecture 11: Decision Making and Warnings (10/9/17, 10/11/17)

Homework 4 (10/11/17)

Lecture 12: Privacy Policies and Notices (10/16/17, 10/30/17)

Case Study (10/16/17)

Guest Lecture (10/25/17)

Project Collaboration Requirements and Potential Case Study Research Questions (10/30/17)

Privacy Perceptions

Lecture 13: Westin Categories (11/1/17)

Homework 5 (11/1/17)

Lecture 14: Privacy Attitudes (11/6/17, 11/13/17)

Lecture 15: Misc Topics (11/15/17)