Privacy | Sai Teja Peddinti

Understanding Help Seeking for Digital Privacy, Safety, and Security

Mon, 19 Jul 2027 00:00:00 +0000

HelpBench: Assessing the Ability of LLMs to Provide Privacy, Safety, and Security Advice

Sun, 06 Dec 2026 00:00:00 +0000

Verity: A Framework to Generate Privacy Captions from Android Source Code using LLMs

Mon, 14 Sep 2026 00:00:00 +0000

This paper won the Distinguished Paper Award at the conference.

Preprint and an earlier version is available on arXiv.

Nudging Developers Toward Privacy: Evaluating the Impact of Personalized App Review Reports

Sun, 23 Aug 2026 03:00:00 +0000

Understanding U.S. Users' Security and Privacy Transparency Needs for Consumer-Facing Generative AI

Sun, 23 Aug 2026 01:00:00 +0000

Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference

Mon, 13 Apr 2026 00:00:00 +0000

Preprint and an earlier version is available on arXiv.

A decade of privacy-relevant Android app reviews: large scale trends

Wed, 14 Aug 2024 00:00:00 +0000

An extended version of this work is available on arXiv.

Evaluating privacy perceptions, experience, and behavior of software development teams

Sat, 10 Aug 2024 00:00:00 +0000

Towards Fine-Grained Localization of Privacy Behaviors

Mon, 03 Jul 2023 00:00:00 +0000

A preprint version of this paper is available on arXiv.

Hark: A Deep Learning System for Navigating Privacy Feedback at Scale

Mon, 23 May 2022 00:00:00 +0000

PAcT: Detecting and Classifying Privacy Behavior of Android Applications

Mon, 16 May 2022 00:00:00 +0000

Analyzing user perspectives on mobile app privacy at scale

Sun, 08 May 2022 00:00:00 +0000

A Large Scale Study of User Behavior, Expectations and Engagement with Android Permissions

Sun, 01 Aug 2021 00:00:00 +0000

PriGen: Towards Automated Translation of Android Applications' Code to Privacy Captions

Tue, 11 May 2021 00:00:00 +0000

A preprint of this paper is available on arXiv

Exploring decision making with android's runtime permission dialogs using in-context surveys

Wed, 12 Jul 2017 00:00:00 +0000

This paper won the IAPP SOUPS Privacy Award at the conference.

User Anonymity on Twitter

Mon, 01 May 2017 00:00:00 +0000

This article is based on two prior publications: COSN 2014 and ICWSM 2016, and an arXiv draft.

Finding Sensitive Accounts on Twitter: An Automated Approach Based on Follower Anonymity

Tue, 17 May 2016 00:00:00 +0000

Perceived Frequency of Advertising Practices

Wed, 22 Jul 2015 00:00:00 +0000

Understanding Sensitivity by Analyzing Anonymity

Sun, 01 Mar 2015 00:00:00 +0000

This is a popularized version of our paper Cloak and Swagger: Understanding Data Sensitivity Through the Lens of User Anonymity, which appeared in IEEE Symposium on Security & Privacy (S&P), 2014.

Stalking Beijing from Timbuktu: A Generic Measurement Approach for Exploiting Location-Based Social Discovery

Fri, 07 Nov 2014 00:00:00 +0000

\"On the internet, nobody knows you're a dog\": a twitter case study of anonymity in social networks

Wed, 01 Oct 2014 00:00:00 +0000

Cloak and Swagger: Understanding Data Sensitivity through the Lens of User Anonymity

Sun, 18 May 2014 00:00:00 +0000

Cover locations: availing location-based services without revealing the location

Mon, 17 Oct 2011 00:00:00 +0000

On the limitations of query obfuscation techniques for location privacy

Sat, 17 Sep 2011 00:00:00 +0000