The risks to privacy when making human subjects data available for research and how to protect against these risks using the formal framework of differential privacy. Methods for attacking statistical data releases, the mathematics of and software implementations of differential privacy, deployed solutions in industry and government. Assignments will include implementation and experimentation on data science tasks.
Course Description: Making data widely available to researchers is good policy. It enables replication and validation of scientific findings and maximizes return on research investment. However, data containing sensitive information about individuals cannot be shared openly without appropriate safeguards. An extensive body of statutes, regulations,...
Meets: Tuesday/Thursday 11:30AM - 1:00PM in MD 119
Course Description: This course will cover topics in cryptography and data privacy drawn from the theoretical computer science research literature with particular focus on differential privacy -- a mathematical framework for privacy-preserving analysis of datasets, which enables aggregate computations while preventing the leakage of individual-level information.
Algorithms to guarantee privacy and authenticity of data during communication and computation. Proofs of security based on precise definitions and assumptions. Topics may include one-way functions, private-key and public-key encryption, digital signatures, pseudorandom generators, zero-knowledge proofs, fully homomorphic encryption, and the role of cryptography in network and systems security.
Prerequisite: Computer Science 121 or Computer Science 124.
What is privacy, and how is it affected by recent developments in computer technology? Course critically examines popular concepts of privacy and uses a rigorous analysis of technologies to understand the policy and ethical issues at play. Case studies: RFID, database anonymity, research ethics, wiretapping. Course relies on some technical material, but is open and accessible to all students, especially those with interest in economics, engineering, political science, computer science, sociology, biology, law, government, philosophy.
How can we enable the analysis of datasets with sensitive information about individuals while protecting the privacy of those individuals?
This question is motivated by the vast amounts of data about individuals that are being collected by companies, researchers, and the government (e.g. census data, genomic databases, web-search logs, GPS readings, social network activity). The sharing and analysis of such data...
This course will focus on language-based information security: using programming language techniques and abstractions to specify, reason about, and enforce, information security. Most of the course will focus on information-flow control: controlling the flow of information within a system to enforce strong security guarantees.