Jingwen Yan (Clemson University), Mohammed Aldeen (Clemson University), Jalil Harris (Clemson University), Kellen Grossenbacher (Clemson University), Aurore Munyaneza (Texas Tech University), Song Liao (Texas Tech University), Long Cheng (Clemson University)

As the number of mobile applications continues to grow, privacy labels (e.g. Apple’s Privacy Labels and Google’s Data Safety Section) emerge as a potential solution to help users understand how apps collect, use and share their data. However, it remains unclear whether these labels actually enhance user understanding to build trust in app developers or influence their download decisions. In this paper, we investigate user perceptions of privacy labels through a comprehensive analysis of online discussions and a structured user study. We first collect and analyze Reddit posts related to privacy labels, and manually analyze the discussions to understand users’ concerns and suggestions. Our analysis reveals that users are skeptical of self-reported privacy labels provided by developers and they struggle to interpret the terminology used in the labels. Users also expressed a desire for clearer explanations about why specific data is collected and emphasized the importance of third-party verification to ensure the accuracy of privacy labels. To complement our Reddit analysis, we conducted a user study with 50 participants recruited via Amazon Mechanical Turk and Qualtrics. The study revealed that 76% of the participants indicated that privacy labels influence their app download decisions and the amount of data practice in the privacy label is the most significant factor.

View More Papers

Privacy Preserved Integrated Big Data Analytics Framework Using Federated...

Sarah Kaleem (Prince Sultan University, PSU) Awais Ahmad (Imam Mohammad Ibn Saud Islamic University, IMSIU), Muhammad Babar (Prince Sultan University, PSU), Goutham Reddy Alavalapati (University of Illinois, Springfield)

Read More

CCTAG: Configurable and Combinable Tagged Architecture

Zhanpeng Liu (Peking University), Yi Rong (Tsinghua University), Chenyang Li (Peking University), Wende Tan (Tsinghua University), Yuan Li (Zhongguancun Laboratory), Xinhui Han (Peking University), Songtao Yang (Zhongguancun Laboratory), Chao Zhang (Tsinghua University)

Read More

An Experimental Study on Attacking Homogeneous Averaging Processes via...

Olsan Ozbay (Dept. ECE, University of Maryland), Yuntao Liu (ISR, University of Maryland), Ankur Srivastava (Dept. ECE, ISR, University of Maryland)

Read More

Onion Franking: Abuse Reports for Mix-Based Private Messaging

Matthew Gregoire (University of North Carolina at Chapel Hill), Margaret Pierce (University of North Carolina at Chapel Hill), Saba Eskandarian (University of North Carolina at Chapel Hill)

Read More