Tool-Supported Privacy Analysis of Smart Parking
Name
Sander Truu
Abstract
Organisations today deal with a lot of data processing which introduces new risks
such as data theft, data manipulation or sensitive information exposure. Implementing additional security features requires extra resources from organisations like additional personnel, time and money. General Data Protection Regulation (GDPR) regulates data processing and sets the requirements for companies to follow in the European Union (EU). It has been around for 8 years yet there are no certain procedures or frameworks for organisations to follow that could be used for privacy analysis of business processes. To support organisations with the problem we demonstrate the tool-supported privacy
analysis method, which uses the DPO Tool and Pleak tool on smart parking business processes to identify privacy violations during data processing. This thesis validates the proposed method for analysing business processes’ privacy issues. It gives an overview of the tools on a real-life scenario, enabling the method to be used in the future. We provide privacy-enhanced business process models along with a detailed privacy analysis which demonstrates the readiness of the method. As a result, the thesis provides a tool-supported analysis of smart parking, demonstrating the use of the selected tools in adding privacy-preserving measures to business processes. Through this process we validate the usability of the method and propose privacy-preserving smart parking process redesign options. The method used can be employed by companies to conduct privacy analysis.
such as data theft, data manipulation or sensitive information exposure. Implementing additional security features requires extra resources from organisations like additional personnel, time and money. General Data Protection Regulation (GDPR) regulates data processing and sets the requirements for companies to follow in the European Union (EU). It has been around for 8 years yet there are no certain procedures or frameworks for organisations to follow that could be used for privacy analysis of business processes. To support organisations with the problem we demonstrate the tool-supported privacy
analysis method, which uses the DPO Tool and Pleak tool on smart parking business processes to identify privacy violations during data processing. This thesis validates the proposed method for analysing business processes’ privacy issues. It gives an overview of the tools on a real-life scenario, enabling the method to be used in the future. We provide privacy-enhanced business process models along with a detailed privacy analysis which demonstrates the readiness of the method. As a result, the thesis provides a tool-supported analysis of smart parking, demonstrating the use of the selected tools in adding privacy-preserving measures to business processes. Through this process we validate the usability of the method and propose privacy-preserving smart parking process redesign options. The method used can be employed by companies to conduct privacy analysis.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Mariia Bakhtina, Raimundas Matulevičius
Defence year
2024