Conceptual Model for Automating GDPR Compliance Verification Using Natural Language Approach

Abstract

Most mobile apps require regular access to sensitive personal information. Regulators are increasingly demanding mobile app makers disclose privacy policies that detail what users’ data is gathered and used. Compliance with data privacy and protection regulations must be monitored to reduce legal penalties that may come from unexpected data breaches. Checking and verifying The General Data Protection Regulation (GDPR) Compliance is quite a challenging issue. In this paper, we propose, an extension to be added to the automated GDPR compliance verification tool. This extension shows how the questions about the compliance of mobile applications might be answered based on GDPR standards. The implementation phases of the extension are explained. It includes query processing, document retrieval, passage retrieval, and answer extraction. This paper provides mobile application developers with a better technique of how to monitor users' compliance with mobile application privacy policies.

Description

Keywords

Natural Language approach, Mobile Applications, Privacy Policies violation, GDPR, Privacy Policies compliance

Citation

Aborujilah, A., Al-Othmani, A.Z., Long, Z.A., Hussien, N.S. and Ghani, D.A. (2022) Conceptual Model for Automating GDPR Compliance Verification Using Natural Language Approach. In: 2022 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE), NewYork: IEEE

Rights

Research Institute

Cyber Technology Institute (CTI)