Challenges in the Implementation of Privacy Enhancing Semantic Technologies (PESTs) Supporting GDPR

被引：2
作者：
Saniei, Rana [1 ]
机构：
[1] Univ Politecn Madrid, Ontol Engn Grp, Madrid, Spain
来源：
AI APPROACHES TO THE COMPLEXITY OF LEGAL SYSTEMS XI-XII | 2021年 / 13048卷
基金：
欧盟地平线“2020”;
关键词：
Compliance; Semantic web; Rule-based reasoning; Data Protection Impact Assessment; Privacy Enhancing Technologies; PRINCIPLES; NORMS;
D O I：
10.1007/978-3-030-89811-3_20
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The EU General Data Protection Regulation (GDPR) imposes different requirements for data controllers collecting personal data to protect individuals' privacy. This fact triggered many studies and projects to investigate Privacy Enhancing Technologies (PETs) for the fulfillment of the compliance requirements. In this paper, after reviewing some of the current challenges and gaps in GDPR compliance, we argue the use of Semantic Technologies in PETs in the form of an Intelligent Compliance Agent (ICA) to support data controllers in carrying out a Data Protection Impact Assessment (DPIA). Models and ontologies representing entities involved in the DPIA process can help data controllers determine the risk of their processing activities. Additionally, an inference engine, equipped with a knowledge base of DPIA-related obligations, can effectively assist data controllers in taking specific actions when a legal fact is triggered based on met conditions.
引用
收藏
页码：283 / 297
页数：15
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