94 citations · 459 across the 33 of their papers we have counts for
9 papers · 1 filter
"I Thought You Were The Uncensored Place": Norms, Rules, and Moderation in AI-Generated Sexual Content Communities
Lucy Qin, Jaron Mink, Elissa M. Redmiles
As AI-generated sexual content (AIG-SC) is increasingly produced, online communities have emerged to support creators' needs. To understand whether and how community governance att…
Evaluating Concept Filtering Defenses against Child Sexual Abuse Material Generation by Text-to-Image Models
Ana-Maria Cretu, Klim Kireev, Amro Abdalla +5
We evaluate the effectiveness of filtering child images from training datasets of text-to-image models to prevent model misuse to create child sexual abuse material (CSAM). First,…
Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy
Mary Anne Smart, Priyanka Nanayakkara, Rachel Cummings +2
Differential privacy is a popular privacy-enhancing technology that has been deployed both in industry and government agencies. Unfortunately, existing explanations of differential…
The Role of Privacy Guarantees in Voluntary Donation of Private Health Data for Altruistic Goals
Ruizhe Wang, Roberta De Viti, Aarushi Dubey +1
The voluntary donation of private health information for altruistic purposes, such as supporting research advancements, is a common practice. However, concerns about data misuse an…
SoK (or SoLK?): On the Quantitative Study of Sociodemographic Factors and Computer Security Behaviors
Miranda Wei, Jaron Mink, Yael Eiger +3
Researchers are increasingly exploring how gender, culture, and other sociodemographic factors correlate with user computer security and privacy behaviors. To more holistically und…
"Did They F***ing Consent to That?": Safer Digital Intimacy via Proactive Protection Against Image-Based Sexual Abuse
Lucy Qin, Vaughn Hamilton, Sharon Wang +3
As many as 8 in 10 adults share intimate content such as nude or lewd images. Sharing such content has significant benefits for relationship intimacy and body image, and can offer…
What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy
Priyanka Nanayakkara, Mary Anne Smart, Rachel Cummings +2
Differential privacy (DP) is a mathematical privacy notion increasingly deployed across government and industry. With DP, privacy protections are probabilistic: they are bounded by…
User Concerns & Tradeoffs in Technology-Facilitated Contact Tracing
Elissa M. Redmiles
The COVID19 pandemic spread across the world in late 2019 and early 2020. As the pandemic spread, technologists joined forces with public health officials to develop apps to suppor…
"Should I Worry?" A Cross-Cultural Examination of Account Security Incident Response
Elissa M. Redmiles
Digital security technology is able to identify and prevent many threats to users accounts. However, some threats remain that, to provide reliable security, require human intervent…