1 citations · 1 across the 15 of their papers we have counts for
17 papers
VisGuardian: A Lightweight Group-based Privacy Control Technique For Front Camera Data From AR Glasses in Home Environments
Shuning Zhang, Qucheng Zang, Yongquan `Owen' Hu +7
Always-on sensing of AI applications on AR glasses makes traditional permission techniques ill-suited for context-dependent visual data, especially within home environments. The ho…
"Privacy across the boundary": Examining Perceived Privacy Risk Across Data Transmission and Sharing Ranges of Smart Home Personal Assistants
Shuning Zhang, Shixuan Li, Haobin Xing +4
As Smart Home Personal Assistants (SPAs) evolve into social agents, understanding user privacy necessitates interpersonal communication frameworks, such as Privacy Boundary Theory…
Collab: Fostering Critical Identification of Deepfake Videos on Social Media via Synergistic Annotation
Shuning Zhang, Linzhi Wang, Shixuan Li +5
Identifying deepfake videos on social media platforms is challenged by dynamic spatio-temporal artifacts and inadequate user tools. This hinders both critical viewing by users and…
A Scoping Review and Guidelines on Privacy Policy's Visualization from an HCI Perspective
Shuning Zhang, Eve He, Sixing Tao +5
Privacy Policies are a cornerstone of informed consent, yet a persistent gap exists between their legal intent and practical efficacy. Despite decades of Human-Computer Interaction…
SoK: Synthesizing Smart Home Privacy Protection Mechanisms Across Academic Proposals and Commercial Documentations
Shuning Zhang, Yijing Liu, Yuyu Liu +5
Pervasive data collection by Smart Home Devices (SHDs) demands robust Privacy Protection Mechanisms (PPMs). The effectiveness of many PPMs, particularly user-facing controls, depen…
"Power of Words": Stealthy and Adaptive Private Information Elicitation via LLM Communication Strategies
Shuning Zhang, Jiaqi Bai, Linzhi Wang +3
While communication strategies of Large Language Models (LLMs) are crucial for human-LLM interactions, they can also be weaponized to elicit private information, yet such stealthy…