A step to achieve personalized human centric privacy policy summary

Online users continuously come across privacy policies for the service they use. Due to the complexity and verbosity of policies, majority of the users skip the tedious task of reading the policy and accept it. Without reading and evaluating the document users risk giving up all kinds of rights to their personal data and for the most part, are unaware of the data sharing and handling process. Efforts have been made to address the complex and lengthy structure of privacy policies by creating a standardized machine-readable format of privacy policies for the web browsers to process it automatically, a repository of crowdsourced summarized versions of some privacy policies, or by using natural language processing to summarize the policies. PirvacyInterpreter is one unique tool that acknowledges human-centric factors while summarising the policy. Thus, it generates a personalised summary of the privacy policy for the user providing relevant information to appease their privacy concerns. This paper presents the conceptualization of PrivacyInterpreter and implements a proof-of-concept model using configured RoBERTa(base) model to classify a privacy policy and produce a summary based on privacy aspects that reflect users' privacy concerns.