Abstract

Data confidentiality is an issue of increasing importance. Several authorities and regulatory bodies are creating new laws that control how web services data is handled and shared. With the rapid increase of such regulations, web service providers face challenges in complying with these evolving regulations across jurisdictions. Providers must update their service policies regularly to address the new regulations. The challenge is that regulatory documents are large text documents and require substantial human effort to comprehend and enforce. On the other hand, web service provider privacy policies are relatively short compared to the regulatory texts, so it is hard to determine if an organization’s policy document addresses the regulation’s essential elements. We have developed a framework to automatically compare web service policies with regulatory policies to measure how closely the web service provider complies with a regulation. In this paper, we present our framework’s details along with the results of analyzing a corpus of 3,000 privacy policies against GDPR. Our framework uses BiLSTM multi-class classification and a BERT extractive summarizer. We evaluate the framework’s efficacy by checking the context similarity score between summarized GDPR and web service provider privacy policies.

Highlights

  • Web service providers are increasingly storing their users’ personal information

  • In order to perform text summarization task, we have considered key entities from the predicted General Data Protection Regulation (GDPR) class described in section III-C and extracted the context from the privacy policy document related to these key entities

  • WORK Web service providers need to ensure that their policies comply with regulations like the EU’s GDPR

Read more

Summary

A BERT Based Approach to Measure Web Services Policies Compliance with GDPR

LAVANYA ELLURI1, SAI SREE LAYA CHUKKAPALLI2, KARUNA PANDE JOSHI1, (Member, IEEE), TIM FININ2, (Fellow, IEEE), ANUPAM JOSHI2, (Fellow, IEEE).

INTRODUCTION
RELATED WORK
Prohibitions
MULTI CLASS TEXT CLASSIFICATION FROM PRIVACY POLICIES
TEXT SUMMARIZATION
REFERENCING DOCUMENTS KNOWLEDGE GRAPH
Findings
CONCLUSION AND FUTURE WORK
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call