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基于语义建模的知情同意的自动化 GDPR 合规验证的数据保护设计工具。

Data Protection by Design Tool for Automated GDPR Compliance Verification Based on Semantically Modeled Informed Consent.

机构信息

Semantic Technology Institute (STI), Department of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria.

The Open Group, Reading, Berkshire RG1 1AX, UK.

出版信息

Sensors (Basel). 2022 Apr 3;22(7):2763. doi: 10.3390/s22072763.

Abstract

The enforcement of the GDPR in May 2018 has led to a paradigm shift in data protection. Organizations face significant challenges, such as demonstrating compliance (or auditability) and automated compliance verification due to the complex and dynamic nature of consent, as well as the scale at which compliance verification must be performed. Furthermore, the GDPR's promotion of data protection by design and industrial interoperability requirements has created new technical challenges, as they require significant changes in the design and implementation of systems that handle personal data. We present a scalable data protection by design tool for automated compliance verification and auditability based on informed consent that is modeled with a knowledge graph. Automated compliance verification is made possible by implementing a regulation-to-code process that translates GDPR regulations into well-defined technical and organizational measures and, ultimately, software code. We demonstrate the effectiveness of the tool in the insurance and smart cities domains. We highlight ways in which our tool can be adapted to other domains.

摘要

2018 年 5 月 GDPR 的实施带来了数据保护的范式转变。由于同意的复杂和动态性质,以及必须进行合规性验证的规模,组织面临着重大挑战,例如证明合规性(或可审计性)和自动化合规性验证。此外,GDPR 通过设计促进数据保护和工业互操作性要求,这带来了新的技术挑战,因为它们需要在处理个人数据的系统的设计和实施方面进行重大更改。我们提出了一种基于知情同意的可扩展设计工具,用于基于知识图建模的自动化合规性验证和可审计性。通过实施将 GDPR 法规转换为明确定义的技术和组织措施,最终转换为软件代码的法规到代码的过程,实现了自动化合规性验证。我们在保险和智能城市领域展示了该工具的有效性。我们强调了我们的工具可以适应其他领域的方式。

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