Ritik Roongta

dblp:331/2514 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2025
0009-0003-5669-9500ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 2 first-author · 3 since 2021
YearPublicationVenuePosition
2025 Sheep's clothing, wolfish intent: Automated detection and evaluation of problematic 'allowed' advertisements
abstract
The digital advertising ecosystem sustains the free web and drives global innovation, but often at the cost of user privacy through intrusive tracking and non-compliant ads, especially harmful to under-age users. This has led to widespread adoption of privacy tools like adblockers and anti-trackers, which, while disrupting ad revenues, expose users to alternate forms of tracking and fingerprinting. To address this, many adblockers now allow 'non-intrusive' ads by default. In this study, we evaluate Adblock Plus's Acceptable Ads feature and find a 13.6% increase in problematic ads compared to no adblocker use—challenging claims of improved user experience. We also find that ad exchanges on allowlists are more likely to serve problematic content, underscoring the hidden cost privacy-aware users pay when relying on such technologies. While prior work in the domain has been limited by their practical viability, we further propose a methodology to automate the detection of problematic ads using LLMs with zero-shot prompting, achieving substantial agreement with human annotators (IAA score: 0.79). This establishes the efficacy of LLMs in problematic content detection under well-defined environments. As In-browser LLMs emerge, adversaries may exploit problematic ad content to fingerprint privacy-conscious ABP users. At the same time, these advances present new opportunities for adblockers to develop robust defenses, detect malicious exchanges, and uphold both user privacy and the sustainability of the ad-supported web.
Ritik Roongta, Julia Jose, Hussam Habib, Rachel Greenstadt
Proc. Priv. Enhancing Technol.1
2024 From User Insights to Actionable Metrics: A User-Focused Evaluation of Privacy-Preserving Browser Extensions
abstract
The rapid growth of web tracking via advertisements has led to an increased adoption of privacy-preserving browser extensions. These extensions are crucial for blocking trackers and enhancing the overall web browsing experience. The advertising industry is constantly changing, leading to ongoing development and improvements in both new and existing ad-blocking and anti-tracking extensions. Despite this, there is a lack of comprehensive studies exploring the set of user concerns associated with these extensions. Our research addresses this gap by identifying five user concerns and establishing a privacy and usability topics framework, specific to privacy-preserving extensions.
Ritik Roongta, Rachel Greenstadt
AsiaCCS1
2022 Drifuzz: Harvesting Bugs in Device Drivers from Golden Seeds
Zekun Shen, Ritik Roongta, Brendan Dolan-Gavitt
USENIX Security Symposium2