06457nam 22004213 450 991079923570332120240202080215.03-031-44939-8(CKB)29527072000041(MiAaPQ)EBC31093944(Au-PeEL)EBL31093944(EXLCZ)992952707200004120240202d2024 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierPrivacy Symposium 2023 Data Protection Law International Convergence and Compliance with Innovative Technologies (DPLICIT)1st ed.Cham :Springer International Publishing AG,2024.©2023.1 online resource (169 pages)9783031449383 Intro -- Foreword -- Comments on Specific Papers -- Conclusion -- Preface -- Organization -- Executive Committee -- Steering Committee -- Program Committee -- Additional Referees -- Contents -- 1 A Methodology for the Assessment of the Impact of Data Protection Risks in the Context of Big Data Analytics: A Delphi Study -- 1.1 Introduction -- 1.2 Background -- 1.3 Overview of the Delphi Study -- 1.3.1 Delphi First Round -- 1.3.2 Delphi Second Round -- 1.4 Conclusions -- A.1 Appendix -- A.1.1 Level of Agreement -- A.1.2 PTP (1) Unclear Data Controllership -- A.1.3 Level of Importance -- A.1.4 DPIA Methodologies -- References -- 2 Introducing the Concept of Data Subject Rights as a Service under the GDPR -- 2.1 Introduction -- 2.2 Data Subject Rights -- 2.3 Related Work -- 2.4 Data Subject Rights as a Service -- 2.4.1 Goals -- 2.4.2 Services -- 2.4.2.1 Data Subject Right Enforcement -- 2.4.2.2 Authentication -- 2.4.2.3 Data Model -- 2.4.2.4 Data Logbook -- 2.4.2.5 Consulting -- 2.4.3 Interfaces -- 2.5 DSRaaS in the Context of the European Data Strategy -- 2.6 Discussion -- 2.7 Conclusion -- References -- 3 Technical and Legal Aspects Relating to the (Re)Use of Health Data When Repurposing Machine Learning Models in the EU -- 3.1 Introduction -- 3.2 Machine Learning Model Repurposing -- 3.3 Data Leakage in Machine Learning Models -- 3.4 Legal Analysis of Repurposing Machine Learning Models -- 3.4.1 General Data Protection Regulation -- 3.4.2 Data Governance Act -- 3.4.3 European Health Data Space Proposal -- 3.5 Scholarly Opinions -- 3.6 Discussion -- 3.7 Conclusion -- References -- 4 "We Are the Makers of Manners": A Grounded Approach to Data Ethics for the Built Environment -- 4.1 Introduction -- 4.1.1 The RED Foundation -- 4.2 The Real Estate Sector: The Landscape, Data, and PropTech -- 4.2.1 The Property Landscape -- 4.2.2 Real Estate Data.4.2.3 Technologies Within the Real Estate Sector -- 4.2.4 Data Regulations Within the Real Estate Sector -- 4.3 Data and Data Protection Challenges in the Real Estate Sector -- 4.3.1 Smart Homes and the Internet of Things: Consumer Data Within the Sector -- 4.3.2 Smart Cities and Sensing: Citizen Data in the Built Environment -- 4.3.3 The Occupier Perspective: The Service Provider Versus the Customer -- 4.3.4 Summary -- 4.4 Overcoming Data and Data Protection Challenges in Practice -- 4.4.1 Good Practices in the Absence of Central Regulation -- 4.4.2 The RED Foundation Data Ethics Playbook -- 4.4.3 Future Work -- 4.5 Conclusion -- References -- 5 How the Charter of Trust Can Support the Data Protection -- 5.1 Introduction -- 5.2 Recent Landscape in Cybersecurity: EU Cybersecurity, Strategy Prime Threats, and Investments -- 5.2.1 The EU Cybersecurity Strategy -- 5.2.2 Prime Threats in the 2021-2022 -- 5.2.3 The ENISA NIS Investments 2022 Report -- 5.3 The Charter of Trust -- 5.4 How the Charter of Trust Supports Data Protection -- 5.4.1 The "Default" Concept and the Charter of Trust 03 Principle: Security by Default -- 5.4.2 A User-Centricity Approach -- 5.4.3 Education -- 5.4.4 Transparency and Response -- 5.5 Conclusion -- References -- 6 Operationalizing the European Essential Guarantees in Cross-Border Personal Data Transfers: The Case Studies of China and India -- 6.1 Introduction -- 6.2 The European Essential Guarantees for Surveillance Measures -- 6.3 Legal Analysis of Government Access to Personal Data in China and India -- 6.3.1 Government Access to Personal Data in China -- 6.3.1.1 Secondary Legislation Analysis in China: Government Access, Oversight, and Data Subject Rights -- 6.3.1.2 Assessment of the Chinese Legal Framework Against the European Essential Guarantees.6.3.1.3 Chinese Personal Information Protection Law: New Regime for the Legality, Oversight Mechanism, Redress, and Data Subject Rights for the Government Data Access? -- 6.3.2 Government Access to Personal Data in India -- 6.3.2.1 Secondary Legislation Analysis in India: Government Access, Oversight, and Data Subject Rights -- 6.3.2.2 Assessment of the Indian Legal Framework Against the European Essential Guarantees -- 6.4 Conclusion -- 6.5 Tables of Relevant Chinese and Indian Laws -- 7 Enabling Versatile Privacy Interfaces Using Machine-Readable Transparency Information -- 7.1 Introduction -- 7.2 Background and Related Work -- 7.3 General Model for Providing Transparency Information -- 7.4 Implementation -- 7.4.1 Layered Privacy Dashboard Including Privacy Icons -- 7.4.2 Interactive Privacy Chatbot and Voice Assistant Through Conversational AI -- 7.5 Preliminary Evaluation -- 7.5.1 Layered Privacy Dashboard -- 7.5.2 Interactive Privacy Chatbot and Voice Assistant -- 7.6 Discussion, Conclusion, and Outlook -- References -- 8 Processing of Data Relating to Criminal Convictions and Offenses in the Context of Labor Relations in Spain -- 8.1 Introduction -- 8.2 The Legal Regime Applicable in Spain to the Processing of Personal Data in the Field of Employment -- 8.3 The Effects of the Special Nature of Data Concerning Criminal Convictions and Offenses with Respect to Its Processing by Employers in Spain -- 8.4 The Processing of Personal Data Relating to Criminal Convictions and Offenses by Employers in Other Member States -- 8.5 Conclusions -- References -- Index.342.0858Schiffner Stefan1588190Ziegler Sébastien1262935Jensen Meiko1588191MiAaPQMiAaPQMiAaPQBOOK9910799235703321Privacy Symposium 20233877533UNINA