USENIX Security2021Top-tier venue
Can Systems Explain Permissions Better? Understanding Users' Misperceptions under Smartphone Runtime Permission Model
Bingyu Shen, Lili Wei, Chengcheng Xiang, Yudong Wu, Mingyao Shen, Yuanyuan Zhou, Xinxin Jin
Abstract
Current smartphone operating systems enable users to manage permissions according to their personal preferences with a runtime permission model. Nonetheless, the systems provide very limited information when requesting permissions, making it difficult for users to understand permissions' capabilities and potentially induced risks. In this paper, we first investigated to what extent current system-provided information can help users understand the scope of permissions and their potential risks. We took a mixed-methods approach by collecting real permission settings from 4,636 Android users, an interview study of 20 participants, and large-scale Internet surveys of 1559 users. Our study identified several common misunderstandings on the runtime permission model among users. We found that only a very small percentage (6.1%) of users can infer the scope of permission groups accurately from the system-provided information. This indicates that the information provided by current systems is far from sufficient. We thereby explored what extra information that systems can provide to help users make more informed permission decisions. By surveying users' common concerns on apps' permission requests, we identified five types of information (i.e., decision factors) that are helpful for users' decisions. We further studied the impact and helpfulness of the factors to users' permission decisions with both positive and negative messages. Our study shows that the background access factor helps most while the grant rate helps the least. Based on the findings, we provide suggestions for system designers to enhance future systems with more permission information.
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Cited by top-tier papers16
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