The paper proposes and evaluates DePRa, a system that democratizes privacy assessment by making everyday users active evaluators of mobile app data access, showing its potential to complement expert a…

The paper addresses the over-reliance on GDPR in digital privacy research by systematically normalizing heterogeneous global data protection laws into a unified, data-lifecycle-aligned abstraction.

The paper introduces GDPRuler, a trusted middleware system that enables verifiable GDPR compliance for key-value stores on untrusted cloud environments without requiring modifications to the core data…

The paper introduces WebPII, a novel, large-scale synthetic benchmark for detecting personally identifiable information (PII) in web screenshots, and demonstrates a model (WebRedact) that significantl…

This study empirically analyzed 41 mobile gaming apps, finding that while device ID disclosures were relatively consistent, location and personal information disclosures showed significant mismatches…

The paper introduces UMBRA, a novel system that detects evolved and subtle dark patterns in cookie consent banners, demonstrating that systematic non-compliance and user autonomy erosion are widesprea…

The paper investigates how users perceive and utilize security and privacy transparency in consumer-facing generative AI, finding that users rely on proxies like popularity and require actionable, tru…

The paper proposes TDPM, a time-aware diffusion model for generative recommendation, which significantly improves recommendation accuracy by explicitly modeling the non-stationary, time-evolving natur…

PolicyGapper is an LLM-based tool that automatically detects inconsistencies and omissions between a mobile app's Google Play Data Safety Section and its official Privacy Policy, identifying thousands…

The paper introduces the PROMPT framework to systematically analyze and mitigate privacy risks in online propaganda detection pipelines, demonstrating that current widely used methods are often non-co…

The paper proposes the User Data Sharing System (UDSS), a hardware-anchored middleware that securely manages PII exchange across diverse consumer electronics devices, significantly reducing onboarding…

The paper evaluates web tracking across ten countries, finding that opt-in jurisdictions (like the EU) generally enforce stronger privacy protections, significantly reducing tracker connections compar…

The study finds exploratory evidence that gender moderates how youth perceive privacy risks and benefits, influencing their protective behavior when using smart voice assistants.

The paper proposes a privacy-preserving visual monitoring system that performs object detection and generates natural language alerts entirely on an edge device, ensuring GDPR compliance by never tran…

This case study systematically measures how placing anonymization at different points (dataset vs. generated answer) within the RAG pipeline affects the privacy-utility trade-off, demonstrating that p…

The paper introduces LLM-CEG, an extended framework that uses membership inference attack success rates and model perplexity to systematically audit and optimize the privacy-utility trade-off when fin…

The paper introduces a novel guardrail orchestration layer that improves the compliance and efficiency of high-stakes multimodal document generation by scoring multiple generated candidates against we…

The paper proposes a robust causal decision framework to measure advertising incrementality despite multiple sources of privacy-induced signal degradation, providing certified decisions on the strengt…

This study proposes a negotiation framework, using composite indices (RBTI and CATI), to explain how youth navigate competing privacy pressures when using smart voice assistants, finding that high usa…

The paper proposes Trajectory Induced Preference Optimization (TIPO) to improve mobile GUI agent personalization by explicitly modeling and optimizing for privacy-related behavioral differences in exe…