This course will focus on how human factors, such as human behavior, goals, and needs, both shape

and are shaped by, the security and privacy of digital systems. For instance, how human behavior

can lead to insecure systems and how digital systems can threaten users’ safety. We will explore

various topics in usable security and privacy and digital safety such as authentication, mental

models of encryption, scams, online hate and harassment, and technology-facilitated interpersonal

abuse. We will learn and apply human-centered and empirical research methods in the context of

these topics, and discuss best practices of human-centered and empirical research in computer security.

This course will focus on how human factors, such as human behavior, goals, and needs, both shape

and are shaped by, the security and privacy of digital systems. For instance, how human behavior

can lead to insecure systems and how digital systems can threaten users’ safety. We will explore

various topics in usable security and privacy and digital safety such as authentication, mental

models of encryption, scams, online hate and harassment, and technology-facilitated interpersonal

abuse. We will learn and apply human-centered and empirical research methods in the context of

these topics, and discuss best practices of human-centered and empirical research in computer security.

This course will introduce recent tools for programmable cryptography, such as zero-knowledge

proofs, multi-party computation, fully homomorphic encryption, private information retrieval,

differential privacy, and trusted execution environments. These tools take as input a computation,

and execute it securely and privately over some data, for different definitions of secure and private.

We will learn what these different tools can do, learn how they work internally, learn how to prove

security for some of them, and also write some code to use and implement them.

This course will introduce recent tools for programmable cryptography, such as zero-knowledge

proofs, multi-party computation, fully homomorphic encryption, private information retrieval,

differential privacy, and trusted execution environments. These tools take as input a computation,

and execute it securely and privately over some data, for different definitions of secure and private.

We will learn what these different tools can do, learn how they work internally, learn how to prove

security for some of them, and also write some code to use and implement them.

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Final project for students completing a master's degree in the College of Computing. Repeatable for multi-semester projects.

Small-group or individual investigation of advanced topics in computing. Guided study and research.

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