A Meta-Model Driven Method for Establishing Business Process Compliance to GDPR
Name
Eduard Sing
Abstract
In the April 2016, the European Parliament and Council approved the new personal data protection regulation - GDPR (General Data Protection Regulation), which will take effect at the end of the May 2018 in all Member States of European Union (EU). The GDPR is addressing common problems of the protection and the usage of the personal data of EU citizens. According to the new regulation, all organizations that use personal data of EU citizens in their day-to-day activities - have to re-evaluate their business processes and information systems to comply with the new rules and constraints. The punishment for misuse of personal data can be very costly to the company - up to 20 million euros or 4% of the annual global turnover in fines. Nevertheless, there is no technical guidance or clear approach that would help to evaluate business processes of an information system to comply with GDPR. This thesis will address mentioned issue by researching the GDPR legislation text and proposing an actual methodology for analysing business processes of information systems and aligning them with the GDPR. The proposed methodology will also help to map the flow of the personal data between different parties and highlight the problematic places in the business processes suggesting measures to reduce the misuse of personal data. This approach could be used as a reference point for developing the automated tool for analysing the processes of an information system to comply with GDPR.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Raimundas Matulevičius, Jake Tom
Defence year
2018