PrivPRISM: Automatically Detecting Discrepancies Between Google Play Data Safety Declarations and Developer Privacy Policies
Bhanuka Silva, Dishanika Denipitiyage, Anirban Mahanti, Aruna Seneviratne, Suranga Seneviratne

TL;DR
PrivPRISM is a framework that automatically detects discrepancies between Google Play's data safety declarations and actual privacy policies, revealing widespread non-compliance and under-disclosure in popular mobile apps.
Contribution
We propose PrivPRISM, a novel language model-based system for scalable, automated comparison of privacy policies and safety declarations to identify inconsistencies.
Findings
53% of popular apps have discrepancies in data disclosures
Privacy policies disclose more sensitive data than safety declarations
Systemic issues like generic policies and vague statements are prevalent
Abstract
End-users seldom read verbose privacy policies, leading app stores like Google Play to mandate simplified data safety declarations as a user-friendly alternative. However, these self-declared disclosures often contradict the full privacy policies, deceiving users about actual data practices and violating regulatory requirements for consistency. To address this, we introduce PrivPRISM, a robust framework that combines encoder and decoder language models to systematically extract and compare fine-grained data practices from privacy policies and to compare against data safety declarations, enabling scalable detection of non-compliance. Evaluating 7,770 popular mobile games uncovers discrepancies in nearly 53% of cases, rising to 61% among 1,711 widely used generic apps. Additionally, static code analysis reveals possible under-disclosures, with privacy policies disclosing just 66.8% of…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Privacy, Security, and Data Protection · Information and Cyber Security
