2 citations · 2 across the 3 of their papers we have counts for
5 papers
Move Fast and Mend Things: Keeping Up with Evolving AI Harms Using Social Media Commentary
Jacqueline Rowe, Animesh Srivastava, Sai Teja Peddinti +2
The rapid deployment of AI systems has created socio-technical, psychological, and operational harms that can elude ex-ante threat modelling and ex-post incident tracking. We intro…
Understanding Help Seeking for Digital Privacy, Safety, and Security
Kurt Thomas, Sai Teja Peddinti, Sarah Meiklejohn +7
The complexity of navigating digital privacy, safety, and security threats often falls directly on users. This leads to users seeking help from family and peers, platforms and advi…
LLM-Powered Analysis of IoT User Reviews: Tracking and Ranking Security and Privacy Concerns
Taufiq Islam Protick, Sai Teja Peddinti, Nina Taft +1
Being able to understand the security and privacy (S&P) concerns of IoT users brings benefits to both developers and users. To learn about users' views, we examine Amazon IoT revie…
Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference
Synthia Wang, Sai Teja Peddinti, Nina Taft +1
Large Language Models (LLMs) such as ChatGPT can infer personal attributes from seemingly innocuous text, raising privacy risks beyond memorized data leakage. While prior work has…
A Decade of Privacy-Relevant Android App Reviews: Large Scale Trends
Omer Akgul, Sai Teja Peddinti, Nina Taft +4
We present an analysis of 12 million instances of privacy-relevant reviews publicly visible on the Google Play Store that span a 10 year period. By leveraging state of the art NLP…