NL2GDPR: Automatically Develop GDPR Compliant Android Application Features from Natural Language
Faysal Hossain Shezan, Yingjie Lao, Minlong Peng, Xin Wang, Mingming, Sun, Ping Li

TL;DR
NL2GDPR is an innovative tool that automatically generates GDPR-compliant privacy policies for Android apps from natural language descriptions, easing compliance challenges for developers with limited resources.
Contribution
It introduces the first automatic GDPR policy generation tool leveraging information extraction and policy generation techniques from natural language descriptions.
Findings
Achieves over 92% accuracy in identifying GDPR policies related to data storage, processing, and sharing.
Utilizes an information extraction model combined with GDPR policy finding and generation modules.
Demonstrates effectiveness in automatically creating privacy policies from developer-provided natural language.
Abstract
The recent privacy leakage incidences and the more strict policy regulations demand a much higher standard of compliance for companies and mobile apps. However, such obligations also impose significant challenges on app developers for complying with these regulations that contain various perspectives, activities, and roles, especially for small companies and developers who are less experienced in this matter or with limited resources. To address these hurdles, we develop an automatic tool, NL2GDPR, which can generate policies from natural language descriptions from the developer while also ensuring the app's functionalities are compliant with General Data Protection Regulation (GDPR). NL2GDPR is developed by leveraging an information extraction tool, OIA (Open Information Annotation), developed by Baidu Cognitive Computing Lab. At the core, NL2GDPR is a privacy-centric information…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Green IT and Sustainability
