TY - GEN
T1 - Collect Responsibly But Deliver Arbitrarily?
T2 - 28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022
AU - Li, Shuai
AU - Yang, Zhemin
AU - Hua, Nan
AU - Liu, Peng
AU - Zhang, Xiaohan
AU - Yang, Guangliang
AU - Yang, Min
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/11/7
Y1 - 2022/11/7
N2 - Recent years have witnessed the interesting trend that modern mobile apps perform more and more likely as user-to-user platforms, where app users can be freely and conveniently connected. Upon these platforms, rich and diverse data is often delivered across users, which brings users great conveniences and plentiful services, but also introduces privacy security concerns. While prior work has primarily studied illegitimate personal data collection problems in mobile apps, few paid little attention to the security of this emerging user-to-user platform feature, thus providing a rather limited understanding of the privacy risks in this aspect. In this paper, we focus on the security of the user-to-user platform feature and shed light on its caused insufficiently-studied but critical privacy risk, which is brought forward by cross-user personal data over-delivery (denoted as XPO). For the first time, this paper reveals the landscape of such XPO risk in wild, along with prevalence and severity assessment. To achieve this, we design a novel automated risk detection framework, named XPOChecker, that leverages the advantages of machine learning and program analysis to extensively and precisely identify potential privacy risks during user-to-user connections, and regulate whether the delivered data is legitimate or not. By applying XPOChecker on 13,820 real-world popular Android apps, we find that XPO is prevalent in practice, with 1,902 apps (13.76%) being affected. In addition to the mere exposure of diverse private user data which causes serious and broad privacy infringement, we demonstrate that the XPO exploits can invalidate privacy preservation mechanisms, leak business secrets, and even restore the sensitive membership of victims which potentially poses personal safety threats. Furthermore, we also confirm the existence of XPO risks in iOS apps for the first time. Last, to help understand and prevent XPO, we have responsibly launched two notification campaigns to inform the developers of the affected apps, with the conclusion of five underlying lessons from developers' feedback. We hope our work can make up for the deficiency of the understandings of XPO, help developers avoid XPO, and motivate further researches.
AB - Recent years have witnessed the interesting trend that modern mobile apps perform more and more likely as user-to-user platforms, where app users can be freely and conveniently connected. Upon these platforms, rich and diverse data is often delivered across users, which brings users great conveniences and plentiful services, but also introduces privacy security concerns. While prior work has primarily studied illegitimate personal data collection problems in mobile apps, few paid little attention to the security of this emerging user-to-user platform feature, thus providing a rather limited understanding of the privacy risks in this aspect. In this paper, we focus on the security of the user-to-user platform feature and shed light on its caused insufficiently-studied but critical privacy risk, which is brought forward by cross-user personal data over-delivery (denoted as XPO). For the first time, this paper reveals the landscape of such XPO risk in wild, along with prevalence and severity assessment. To achieve this, we design a novel automated risk detection framework, named XPOChecker, that leverages the advantages of machine learning and program analysis to extensively and precisely identify potential privacy risks during user-to-user connections, and regulate whether the delivered data is legitimate or not. By applying XPOChecker on 13,820 real-world popular Android apps, we find that XPO is prevalent in practice, with 1,902 apps (13.76%) being affected. In addition to the mere exposure of diverse private user data which causes serious and broad privacy infringement, we demonstrate that the XPO exploits can invalidate privacy preservation mechanisms, leak business secrets, and even restore the sensitive membership of victims which potentially poses personal safety threats. Furthermore, we also confirm the existence of XPO risks in iOS apps for the first time. Last, to help understand and prevent XPO, we have responsibly launched two notification campaigns to inform the developers of the affected apps, with the conclusion of five underlying lessons from developers' feedback. We hope our work can make up for the deficiency of the understandings of XPO, help developers avoid XPO, and motivate further researches.
UR - http://www.scopus.com/inward/record.url?scp=85143078587&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85143078587&partnerID=8YFLogxK
U2 - 10.1145/3548606.3559371
DO - 10.1145/3548606.3559371
M3 - Conference contribution
AN - SCOPUS:85143078587
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 1887
EP - 1900
BT - CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery
Y2 - 7 November 2022 through 11 November 2022
ER -