Abstract
This paper analyzes the findings of [1] regarding user privacy in Android apps. Mobile applications have come under scrutiny for allegations of data breaches and leaks, such as usernames, email IDs, and locations. Subsequent documented instances of these violations have led to the Federal Trade Commission (FTC) imposing severe penalties on the app developers. Recently, apps such as TikTok and BabyBus were sanctioned and fined for flouting privacy regulations. To ensure the safety of young users, the Children's Online Privacy Protection Act (COPPA) was enacted to monitor the data usage of apps dedicated to children. Hence, it is imperative that children's apps adhere to COPPA. Towards this end, [1] proposes COPPA Tracking by Checking Hardware-level Activity (COPPTCHA), a Hardware Performance Counter-based (HPC) approach to validate COPPA-compliance of Android apps. The HPC data is used to train a Machine Learning classifier, which predicts COPPA violations with 99% accuracy. This paper summarizes the benefits and pitfalls of using HPCs for detecting COPPA violations.
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