Image de couverture de livre

Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agent

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Zhiping, Guo, Bingcan, Li, Tianshi
Format:	Preprint
Publié:	2024
Sujets:	Human-Computer Interaction Artificial Intelligence Cryptography and Security
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Human-Centered Privacy Research in the Age of Large Language Models
par: Li, Tianshi, et autres
Publié: (2024)

Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents
par: Zhang, Zhiping, et autres
Publié: (2025)

Not My Agent, Not My Boundary? Elicitation of Personal Privacy Boundaries in AI-Delegated Information Sharing
par: Guo, Bingcan, et autres
Publié: (2025)

"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agents
par: Zhang, Zhiping, et autres
Publié: (2023)

PrivateXR: Defending Privacy Attacks in Extended Reality Through Explainable AI-Guided Differential Privacy
par: Kundu, Ripan Kumar, et autres
Publié: (2025)

A Human-Centered Privacy Approach (HCP) to AI
par: Sun, Luyi, et autres
Publié: (2026)

An Empirical Study of Privacy Leakage Chains via Prompt Injection in Black-Box Chatbot Environments
par: Yang, Hongjang, et autres
Publié: (2026)

Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents
par: Chen, Chaoran, et autres
Publié: (2025)

Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents
par: Sun, Bolun, et autres
Publié: (2024)

From Perception to Protection: A Developer-Centered Study of Security and Privacy Threats in Extended Reality (XR)
par: Cai, Kunlin, et autres
Publié: (2025)

Matcha: An IDE Plugin for Creating Accurate Privacy Nutrition Labels
par: Li, Tianshi, et autres
Publié: (2024)

Rescriber: Smaller-LLM-Powered User-Led Data Minimization for LLM-Based Chatbots
par: Zhou, Jijie, et autres
Publié: (2024)

The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections
par: Chen, Chaoran, et autres
Publié: (2025)

What Security and Privacy Transparency Users Need from Consumer-Facing Generative AI
par: Cao, Jiaxun, et autres
Publié: (2026)

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
par: Tang, Jingyu, et autres
Publié: (2025)

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
par: Shanmugarasa, Yashothara, et autres
Publié: (2025)

PrivacyAssist: A User-Centric Agent Framework for Detecting Privacy Inconsistencies in Android Apps
par: Nguyen, Tran Thanh Lam, et autres
Publié: (2026)

Cyri: A Conversational AI-based Assistant for Supporting the Human User in Detecting and Responding to Phishing Attacks
par: La Torre, Antonio, et autres
Publié: (2025)

Device-Native Autonomous Agents for Privacy-Preserving Negotiations
par: Roy, Joyjit, et autres
Publié: (2026)

Human-AI Collaboration in Cloud Security: Cognitive Hierarchy-Driven Deep Reinforcement Learning
par: Aref, Zahra, et autres
Publié: (2025)

Human-Centered Explainability in AI-Enhanced UI Security Interfaces: Designing Trustworthy Copilots for Cybersecurity Analysts
par: Rajhans, Mona
Publié: (2026)

Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy
par: Smart, Mary Anne, et autres
Publié: (2024)

Privacy is All You Need: Revolutionizing Wearable Health Data with Advanced PETs
par: Barma, Karthik
Publié: (2025)

InjectLab: A Tactical Framework for Adversarial Threat Modeling Against Large Language Models
par: Howard, Austin
Publié: (2025)

Understanding User Privacy Perceptions of GenAI Smartphones
par: Jin, Ran, et autres
Publié: (2026)

SECURE: Benchmarking Large Language Models for Cybersecurity
par: Bhusal, Dipkamal, et autres
Publié: (2024)

SoK: Usability Studies in Differential Privacy
par: Dibia, Onyinye, et autres
Publié: (2024)

Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges
par: Bozkir, Efe, et autres
Publié: (2023)

Privacy Law Enforcement Under Centralized Governance: A Qualitative Analysis of Four Years' Special Privacy Rectification Campaigns
par: Jing, Tao, et autres
Publié: (2025)

NLP Privacy Risk Identification in Social Media (NLP-PRISM): A Survey
par: Goswami, Dhiman, et autres
Publié: (2026)

Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
par: Zarlenga, Mateo Espinosa, et autres
Publié: (2025)

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

RLHFPoison: Reward Poisoning Attack for Reinforcement Learning with Human Feedback in Large Language Models
par: Wang, Jiongxiao, et autres
Publié: (2023)

Current state of LLM Risks and AI Guardrails
par: Ayyamperumal, Suriya Ganesh, et autres
Publié: (2024)

BounTCHA: A CAPTCHA Utilizing Boundary Identification in Guided Generative AI-extended Videos
par: Lin, Lehao, et autres
Publié: (2025)

From Assistants to Adversaries: Exploring the Security Risks of Mobile LLM Agents
par: Wu, Liangxuan, et autres
Publié: (2025)

Towards Automating Data Access Permissions in AI Agents
par: Wu, Yuhao, et autres
Publié: (2025)

"Impressively Scary:" Exploring User Perceptions and Reactions to Unraveling Machine Learning Models in Social Media Applications
par: West, Jack, et autres
Publié: (2025)

From Theory to Comprehension: A Comparative Study of Differential Privacy and $k$-Anonymity
par: von Voigt, Saskia Nuñez, et autres
Publié: (2024)

"Think First, Verify Always": Training Humans to Face AI Risks
par: Aydin, Yuksel
Publié: (2025)