Publications

Synthia Wang, Sai Teja Peddinti, Nina Taft, Nick Feamster (2026). Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference. CHI'26.

Kurt Thomas, Sai Teja Peddinti, Sarah Meiklejohn, Tara Matthews, Amelia Hassoun, Animesh Srivastava, Jessica McClearn, Patrick Gage Kelley, Sunny Consolvo, Nina Taft (2026). Understanding Help Seeking for Digital Privacy, Safety, and Security. arXiv.

Vijayanta Jain, Sepideh Ghanavati, Sai Teja Peddinti, Collin McMillan (2026). Automated Generation of Accurate Privacy Captions From Android Source Code Using Large Language Models. arXiv.

Taufiq Islam Protick, Sai Teja Peddinti, Nina Taft, Anupam Das (2025). LLM-Powered Analysis of IoT User Reviews: Tracking and Ranking Security and Privacy Concerns. ICWSM.

Rameen Mahmood, Tousif Ahmed, Sai Teja Peddinti, Danny Yuxing Huang (2025). Large Language Models for Real-World IoT Device Identification. arXiv.

Alexandra Klymenko, Stephen Meisenbacher, Patrick Gage Kelley, Sai Teja Peddinti, Kurt Thomas, Florian Matthes (2025). "We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe. SOUPS.

Dinil Mon Divakaran, Sai Teja Peddinti (2024). Large Language Models for Cybersecurity: New Opportunities. IEEE S&P.

Omer Akgul, Sai Teja Peddinti, Nina Taft, Michelle L. Mazurek, Hamza Harkous, Animesh Srivastava, Benoit Seguin (2024). A decade of privacy-relevant Android app reviews: large scale trends. USENIX Security.

Stephen Meisenbacher, Alexandra Klymenko, Patrick Gage Kelley, Sai Teja Peddinti, Kurt Thomas, Florian Matthes (2024). Privacy Risks of General-Purpose AI Systems: A Foundation for Investigating Practitioner Perspectives. SUPA.

Maxwell Prybylo, Sara Haghighi, Sai Teja Peddinti, Sepideh Ghanavati (2024). Evaluating privacy perceptions, experience, and behavior of software development teams. SOUPS.