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

On Borrowed Time – Preventing Static Side-Channel Analysis

Robert Dumitru (Ruhr University Bochum and The University of Adelaide), Thorben Moos (UCLouvain), Andrew Wabnitz (Defence Science and Technology Group), Yuval Yarom (Ruhr University Bochum)

Read More

Automatic Library Fuzzing through API Relation Evolvement

Jiayi Lin (The University of Hong Kong), Qingyu Zhang (The University of Hong Kong), Junzhe Li (The University of Hong Kong), Chenxin Sun (The University of Hong Kong), Hao Zhou (The Hong Kong Polytechnic University), Changhua Luo (The University of Hong Kong), Chenxiong Qian (The University of Hong Kong)

Read More

ICSQuartz: Scan Cycle-Aware and Vendor-Agnostic Fuzzing for Industrial Control...

Corban Villa (New York University Abu Dhabi), Constantine Doumanidis (New York University Abu Dhabi), Hithem Lamri (New York University Abu Dhabi), Prashant Hari Narayan Rajput (InterSystems), Michail Maniatakos (New York University Abu Dhabi)

Read More