Imagen de Portada

Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Qiu, Wenjun, Lie, David, Austin, Lisa
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Cryptography and Security Human-Computer Interaction Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Deep Active Learning with Crowdsourcing Data for Privacy Policy Classification
por: Qiu, Wenjun, et al.
Publicado: (2020)

Maximizing Information Gain in Privacy-Aware Active Learning of Email Anomalies
por: Chung, Mu-Huan Miles, et al.
Publicado: (2024)

Federated Learning in Offline and Online EMG Decoding: A Privacy and Performance Perspective
por: Malcolm, Kai, et al.
Publicado: (2025)

Evaluating the Usability of LLMs in Threat Intelligence Enrichment
por: Srikanth, Sanchana, et al.
Publicado: (2024)

Health App Reviews for Privacy & Trust (HARPT): A Corpus for Analyzing Patient Privacy Concerns, Trust in Providers and Trust in Applications
por: Kelly, Timoteo, et al.
Publicado: (2025)

Jaco: An Offline Running Privacy-aware Voice Assistant
por: Bermuth, Daniel, et al.
Publicado: (2022)

Matcha: An IDE Plugin for Creating Accurate Privacy Nutrition Labels
por: Li, Tianshi, et al.
Publicado: (2024)

The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections
por: Chen, Chaoran, et al.
Publicado: (2025)

A Security Risk Taxonomy for Prompt-Based Interaction With Large Language Models
por: Derner, Erik, et al.
Publicado: (2023)

Can LLM-Generated Misinformation Be Detected?
por: Chen, Canyu, et al.
Publicado: (2023)

A Human-Centered Privacy Approach (HCP) to AI
por: Sun, Luyi, et al.
Publicado: (2026)

User-wise Perturbations for User Identity Protection in EEG-Based BCIs
por: Chen, Xiaoqing, et al.
Publicado: (2024)

Neural Fuzzy Extractors: A Secure Way to Use Artificial Neural Networks for Biometric User Authentication
por: Jana, Abhishek, et al.
Publicado: (2020)

Stochastic Modeling of Human-Machine Authentication Channels under Partial Information Leakage
por: Chakraborty, Nilesh, et al.
Publicado: (2026)

AdaptAuth: Multi-Layered Behavioral and Credential Analysis for a Secure and Adaptive Authentication Framework for Password Security
por: Ghosh, Tonmoy
Publicado: (2025)

Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges
por: Bozkir, Efe, et al.
Publicado: (2023)

Beyond SSO: Mobile Money Authentication for Inclusive e-Government in Sub-Saharan Africa
por: Adewusi, Oluwole, et al.
Publicado: (2025)

Centering Policy and Practice: Research Gaps around Usable Differential Privacy
por: Cummings, Rachel, et al.
Publicado: (2024)

Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy
por: Smart, Mary Anne, et al.
Publicado: (2024)

JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
por: Feng, Yingchaojie, et al.
Publicado: (2024)

Test Security in Remote Testing Age: Perspectives from Process Data Analytics and AI
por: Hao, Jiangang, et al.
Publicado: (2024)

Human-in-the-Loop Generation of Adversarial Texts: A Case Study on Tibetan Script
por: Cao, Xi, et al.
Publicado: (2024)

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
por: Shanmugarasa, Yashothara, et al.
Publicado: (2025)

Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents
por: Chen, Chaoran, et al.
Publicado: (2025)

Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming
por: Inie, Nanna, et al.
Publicado: (2023)

PrivacyAssist: A User-Centric Agent Framework for Detecting Privacy Inconsistencies in Android Apps
por: Nguyen, Tran Thanh Lam, et al.
Publicado: (2026)

Privacy Law Enforcement Under Centralized Governance: A Qualitative Analysis of Four Years' Special Privacy Rectification Campaigns
por: Jing, Tao, et al.
Publicado: (2025)

SoK: Usability Studies in Differential Privacy
por: Dibia, Onyinye, et al.
Publicado: (2024)

Distinguishing Scams and Fraud with Ensemble Learning
por: Chadalavada, Isha, et al.
Publicado: (2024)

Adversarial Attacks on Machine Learning-Aided Visualizations
por: Fujiwara, Takanori, et al.
Publicado: (2024)

Privacy-preserving Scanpath Comparison for Pervasive Eye Tracking
por: Ozdel, Suleyman, et al.
Publicado: (2024)

Understanding User Privacy Perceptions of GenAI Smartphones
por: Jin, Ran, et al.
Publicado: (2026)

Unveiling Privacy and Security Gaps in Female Health Apps
por: Hassan, Muhammad, et al.
Publicado: (2025)

Evaluating the Usability of Differential Privacy Tools with Data Practitioners
por: Ngong, Ivoline C., et al.
Publicado: (2023)

VBIT: Towards Enhancing Privacy Control Over IoT Devices
por: Aaraj, Jad Al, et al.
Publicado: (2024)

Characterizing Security and Privacy Teaching Standards for Schools in the United States
por: Limes, Katherine, et al.
Publicado: (2025)

Towards Privacy-preserving Photorealistic Self-avatars in Mixed Reality
por: Wilson, Ethan, et al.
Publicado: (2025)

Exploring the Effectiveness of Google Play Store's Privacy Transparency Channels
por: Xiang, Anhao, et al.
Publicado: (2025)

In Pursuit of Privacy: The Value-Centered Privacy Assistant
por: Carter, Sarah E., et al.
Publicado: (2023)

Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions
por: Gumusel, Ece
Publicado: (2025)