Privacy Engineering

Data Science
233

3 units

Course Description

This course surveys privacy mechanisms applicable to systems engineering, with a particular focus on the inference threat arising due to advancements in artificial intelligence and machine learning. We will briefly discuss the history of privacy and compare two major examples of general legal frameworks for privacy from the United States and the European Union. We then survey three design frameworks of privacy that may be used to guide the design of privacy-aware information systems. Finally, we survey threat-specific technical privacy frameworks and discuss their applicability in different settings, including statistical privacy with randomized responses, anonymization techniques, semantic privacy models, and technical privacy mechanisms.

Course Designer

Daniel Aranki
Daniel Aranki
Assistant Professor of Practice

Previously listed as DATASCI W233.

Prerequisites

MIDS students only
Last updated: October 6, 2022