Yun Shen (NortonLifeLock Research Group), Pierre-Antoine Vervier (NortonLifeLock Research Group), Gianluca Stringhini (Boston University)

Mobile phones enable the collection of a wealth of private information, from unique identifiers (e.g., email addresses), to a user’s location, to their text messages. This information can be harvested by apps and sent to third parties, which can use it for a variety of purposes. In this paper we perform the largest study of private information collection (PIC) on Android to date. Leveraging an anonymized dataset collected from the customers of a popular mobile security product, we analyze the flows of sensitive information generated by 2.1M unique apps installed by 17.3M users over a period of 21 months between 2018 and 2019. We find that 87.2% of all devices send private information to at least five different domains, and that actors active in different regions (e.g., Asia compared to Europe) are interested in collecting different types of information. The United States (62% of the total) and China (7% of total flows) are the countries that collect most private information. Our findings raise issues regarding data regulation, and would encourage policymakers to further regulate how private information is used by and shared among the companies and how accountability can be truly guaranteed.

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OblivSketch: Oblivious Network Measurement as a Cloud Service

Shangqi Lai (Monash University), Xingliang Yuan (Monash University), Joseph K. Liu (Monash University), Xun Yi (RMIT University), Qi Li (Tsinghua University), Dongxi Liu (Data61, CSIRO), Surya Nepal (Data61, CSIRO)

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PHOENIX: Device-Centric Cellular Network Protocol Monitoring using Runtime Verification

Mitziu Echeverria (The University of Iowa), Zeeshan Ahmed (The University of Iowa), Bincheng Wang (The University of Iowa), M. Fareed Arif (The University of Iowa), Syed Rafiul Hussain (Pennsylvania State University), Omar Chowdhury (The University of Iowa)

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To Err.Is Human: Characterizing the Threat of Unintended URLs...

Beliz Kaleli (Boston University), Brian Kondracki (Stony Brook University), Manuel Egele (Boston University), Nick Nikiforakis (Stony Brook University), Gianluca Stringhini (Boston University)

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Hunting the Haunter — Efficient Relational Symbolic Execution for...

Lesly-Ann Daniel (CEA, List, France), Sébastien Bardin (CEA, List, France), Tamara Rezk (Inria, France)

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