Users -

: A paper presented at USENIX SOUPS that uses static code analysis to help identify privacy profiles for managing permissions based on the actual purpose of data requests. User Modeling & Artificial Intelligence

: Explores the use of personas specifically for library user experiences to better understand diverse audience characteristics and goals. Privacy & Behavior : A paper presented at USENIX SOUPS that

: A NIST research document that challenges the "users are the weakest link" narrative in security, focusing instead on "security fatigue" and usability challenges. : A systematic literature review analyzing the gap

: A systematic literature review analyzing the gap between users' high concern for privacy and their actual behavior, which often includes minimal steps to protect data. : A paper presented at USENIX SOUPS that

Users are not stupid: Six cyber security pitfalls overturned

: A short paper from researchers at UC Berkeley investigating whether past user decisions can predict future responses to location access prompts on mobile apps.

: Provides a historical overview of how AI systems—like Recommender Systems—construct user representations from interaction data.