CSC 433 - Privacy in the Digital Age
Catalog Description:Privacy is a growing concern in our modern society. We interact and share our personal information with a wide variety of organizations, including financial and healthcare institutions, web service providers and social networks. Many times such personal information is inappropriately collected, used or shared, often without our awareness. This course introduces privacy in a broad sense, with the aim of providing students an overview of the challenging and emerging research topics in privacy. This course will expose students to many of the issues that privacy engineers, program managers, researchers and designers deal with in industry. ST 370 is recommended.
Contact Hours:
- Lecture: 3 hours
Co-requisites: None
Restrictions: None
Coordinator: Dr. Anupam Das
Textbook: None
Course Outcomes:
By the end of this course, students will be able to:
- Distinguish personally identifiable information (PII) in databases
- Apply techniques to anonymize and protect PII in databases
- Differentiate between various online tracking mechanisms and their mitigation techniques
- Explain how anonymous communication networks work and how they help users preserve their online anonymity
- Evaluate the opportunities and implications of using AI/ML in privacy
- Apply side-channel leaks
- Identify and describe important elements of privacy policies and regulations
- Compare and contrast users' attitudes and perceptions of privacy
Topics:
- Introduction and course overview
- Data De-anonymization
- k-anonymity
- l-diversity, t-closeness
- Differential privacy
- Private Information Retrieval (PIR)
- Online tracking: stateful
- Online tracking: stateless
- Privacy tools for web browsing
- Anonymous communication
- Tor network
- Social networks and privacy
- Privacy Attacks on machine learning models
- Privacy perserving machine learning
- Fairness and auditing of automated systems
- Privacy acts and frameworks
- Privacy notices
- Privacy policy compliance
- Westin's privacy index
- Factors influencing privacy attitude
- Modeling users' privacy preferences
- Bitcoin and privacy
- Network-level Inference attacks
- Acoustic and Motion sensor based Inferenc attacks
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