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Software applications have become an omnipresent part of modern society. Theconsequent privacy policies of these applications play a significant role ininforming customers how their personal information is collected, stored, andused. However, customers rarely read and often fail to understand privacypolicies because of the ``Privacy Policy Reading Phobia'' (PPRP). To tacklethis emerging challenge, we propose the first framework that can automaticallygenerate privacy nutrition labels from privacy policies. Based on our groundtruth applications about the Data Safety Report from the Google Play app store,our framework achieves a 0.75 F1-score on generating first-party datacollection practices and an average of 0.93 F1-score on general securitypractices. We also analyse the inconsistencies between ground truth and curatedprivacy nutrition labels on the market, and our framework can detect 90.1%under-claim issues. Our framework demonstrates decent generalizability acrossdifferent privacy nutrition label formats, such as Google's Data Safety Reportand Apple's App Privacy Details.

Toward the Cure of Privacy Policy Reading Phobia: Automated Generation of Privacy Nutrition Labels From Privacy Policies