  Privacy Policies are the legal documents that describe the practices that an
organization or company has adopted in the handling of the personal data of its
users. But as policies are a legal document, they are often written in
extensive legal jargon that is difficult to understand. Though work has been
done on privacy policies but none that caters to the problem of verifying if a
given privacy policy adheres to the data protection laws of a given country or
state. We aim to bridge that gap by providing a framework that analyzes privacy
policies in light of various data protection laws, such as the General Data
Protection Regulation (GDPR). To achieve that, firstly we labeled both the
privacy policies and laws. Then a correlation scheme is developed to map the
contents of a privacy policy to the appropriate segments of law that a policy
must conform to. Then we check the compliance of privacy policy's text with the
corresponding text of the law using NLP techniques. By using such a tool, users
would be better equipped to understand how their personal data is managed. For
now, we have provided a mapping for the GDPR and PDPA, but other laws can
easily be incorporated in the already built pipeline.
