PTPDroid: Detecting Violated User Privacy Disclosures to Third-Parties of Android Apps
Zeya Tan, Wei Song
Abstract
Android apps frequently access personal information to provide customized services. Since such information is sensitive in general, regulators require Android app vendors to publish privacy policies that describe what information is collected and why it is collected. Existing work mainly focuses on the types of the collected data but seldom considers the entities that collect user privacy, which could falsely classify problematic declarations about user privacy collected by third-parties into clear disclosures. To address this problem, we propose PTPDroid, a flow-to-policy consistency checking approach and an automated tool, to comprehensively uncover from the privacy policy the violated disclosures to third-parties. Our experiments on real-world apps demonstrate the effectiveness and superiority of PTPDroid, and our empirical study on 1,000 popular real-world apps reveals that violated user privacy disclosures to third-parties are prevalent in practice.
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