  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 extraction model,
appended with a GDPR policy finder and a policy generator. We perform a
comprehensive study to grasp the challenges in extracting privacy-centric
information and generating privacy policies, while exploiting optimizations for
this specific task. With NL2GDPR, we can achieve 92.9%, 95.2%, and 98.4%
accuracy in correctly identifying GDPR policies related to personal data
storage, process, and share types, respectively. To the best of our knowledge,
NL2GDPR is the first tool that allows a developer to automatically generate
GDPR compliant policies, with only the need of entering the natural language
for describing the app features. Note that other non-GDPR-related features
might be integrated with the generated features to build a complex app.

Cryptography and Security;Computation and Language