Jiangrong Wu (Sun Yat-sen University), Yuhong Nan (Sun Yat-sen University), Luyi Xing (Indiana University Bloomington), Jiatao Cheng (Sun Yat-sen University), Zimin Lin (Alibaba Group), Zibin Zheng (Sun Yat-sen University), Min Yang (Fudan University)

Cross-app content sharing is one of the prominent features widely used in mobile apps. For example, a short video from one app can be shared to another (e.g., a messaging app) and further viewed by other users. In many cases, such Cross-app content sharing activities could have privacy implications for both the sharer and sharee, such as exposing app users' personal interests.

In this paper, we provide the first in-depth study on the privacy implications of Cross-app content sharing (as we call Cracs) activities in the mobile ecosystem. Our research showed that during the sharing process, the adversary can not only track and infer user interests as traditional web trackers but also cause other severe privacy implications to app users. More specifically, due to multiple privacy-intrusive designs and implementations of Cracs, an adversary can easily reveal a user's social relations to an outside party, or unnecessarily expose user identities and her associated personal data (e.g., user accounts in another app). Such privacy implications are indeed a concern for app users, as confirmed by a user study we have performed with 300 participants.

To further evaluate the impact of our identified privacy implications at large, we have designed an automatic pipeline named Shark, combined with static analysis and dynamic analysis to effectively identify whether a given app introduces unnecessary data exposure in Cracs. We analyzed 300 top downloaded apps collected from app stores in both the US and China. The analysis results showed that over 55% of the apps from China and 10% from the US are indeed problematic.

View More Papers

WIP: Savvy: Trustworthy Autonomous Vehicles Architecture

Ali Shoker, Rehana Yasmin, Paulo Esteves-Verissimo (Resilient Computing & Cybersecurity Center (RC3), KAUST)

Read More

Why People Still Fall for Phishing Emails: An Empirical...

Asangi Jayatilaka (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide, School of Computing Technologies, RMIT University), Nalin Asanka Gamagedara Arachchilage (School of Computer Science, The University of Auckland), M. Ali Babar (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide)

Read More

LoRDMA: A New Low-Rate DoS Attack in RDMA Networks

Shicheng Wang (Tsinghua University), Menghao Zhang (Beihang University & Infrawaves), Yuying Du (Information Engineering University), Ziteng Chen (Southeast University), Zhiliang Wang (Tsinghua University & Zhongguancun Laboratory), Mingwei Xu (Tsinghua University & Zhongguancun Laboratory), Renjie Xie (Tsinghua University), Jiahai Yang (Tsinghua University & Zhongguancun Laboratory)

Read More

Work-in-Progress: A Large-Scale Long-term Analysis of Online Fraud across...

Yi Han, Shujiang Wu, Mengmeng Li, Zixi Wang, and Pengfei Sun (F5)

Read More