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  4. Supporting privacy impact assessment by model-based privacy analysis
 
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2018
Conference Paper
Title

Supporting privacy impact assessment by model-based privacy analysis

Abstract
According to Article 35 of the General Data Protection Regulation (GDPR), data controllers are obligated to conduct a privacy impact assessment (PIA) to ensure the protection of sensitive data. Failure to properly protect sensitive data may affect data subjects negatively, and damage the reputation of data processors. Existing PIA approaches cannot be easily conducted, since they are mainly abstract or imprecise. Moreover, they lack a methodology to conduct the assessment concerning the design of IT systems. We propose a novel methodology to support PIA by performing model-based privacy and security analyses in the early phases of the system development. In our methodology, the design of a system is analyzed and, where necessary, appropriate security and privacy controls are suggested to improve the design. Hence, this methodology facilitates privacy by design as prescribed in Article 25 of the GDPR. We evaluated our methodology based on three industrial case studies and a quality-based comparison to the state of the art.
Author(s)
Ahmadian, Amir Shayan
Strüber, Daniel
Riediger, Volker
Jürjens, Jan  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Mainwork
SAC '18, 33rd ACM/SIGAPP Symposium On Applied Computing. Proceedings  
Conference
Symposium on Applied Computing (SAC) 2018  
DOI
10.1145/3167132.3167288
Language
English
Fraunhofer-Institut für Software- und Systemtechnik ISST  
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