Privacy Technologies and Policy

Name: Privacy Technologies and Policy | 11th Annual Privacy Forum, APF 2023, Lyon, France, June 1-2, 2023, Proceedings
Brand: Springer
Price: 117.69 EUR
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11th Annual Privacy Forum, APF 2023, Lyon, France, June 1-2, 2023, Proceedings

Kai Rannenberg Prokopios Drogkaris Cédric Lauradoux(Herausgeber*in)

Springer (Verlag)

Erschienen am 29. Mai 2024

X, 183 Seiten

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978-3-031-61089-9 (ISBN)

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Beschreibung

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Inhalt

Intro
Preface
Organization
Contents
Emerging Technologies and Protection of Personal Data
A Universal Data Model for Data Sharing Under the European Data Strategy
1 Introduction
2 Background
2.1 The European Data Strategy
2.2 The Data Governance Act and Data Intermediaries
2.3 Digital Markets Act and Market Fairness
3 Related Work
4 Data Model
4.1 Requirements
4.2 Classes and Attributes
5 Illustrating Example
6 Application Areas
7 Discussion and Open Issues
8 Conclusion
References
A Decision-Making Process to Implement the 'Right to Be Forgotten' in Machine Learning
1 Introduction
1.1 Paper Contributions
1.2 Paper Structure
2 Background
2.1 Machine Learning
2.2 Literature Review
3 Decision-Making Flow
3.1 Legal Requirements for Implementing the RTBF
3.2 Machine Learning Techniques for Erasure
4 Conclusion
References
Data Protection Principles and Data Subject Rights
A Data Protection-Compliant Framework for Wi-Fi-Based Location Tracking (in Law Enforcement)
1 Introduction
2 Related Work
3 System and Scenario for a Domestic Wi-Fi Detector
3.1 Limitation of the Perimeter
3.2 Limitation of the Duration of Data Collection and Storage
3.3 Detection of Authorised and Unauthorised Devices
3.4 Lawfulness of Processing
3.5 Information Obligations - A Legal Minefield
3.6 Opt-Out Possibilities
4 Conclusion
References
Past and Present: A Case Study of Twitter's Responses to GDPR Data Requests
1 Introduction
2 Related Work
2.1 General Data Protection Regulation
2.2 Research Approaches Related to GDPR
2.3 Summary
3 Methodology
4 Evaluation of Data Requests
4.1 Past: First Request in 2018
4.2 Present: Second Request in 2023
4.3 From Past to Present
5 Discussion
5.1 Completeness, Accuracy, and Transparency
5.2 Data Minimization
5.3 Understandable vs. Machine-Readable
5.4 Advertisement and Tracking
5.5 Comparison with Twitter's Privacy Statement
6 Conclusion and Outlook
A Definitions
B Comparison of Past and Current Files
References
Modelling Data Protection and Privacy
No Children in the Metaverse? The Privacy and Safety Risks of Virtual Worlds (and How to Deal with Them)
1 Introduction
2 What is the "Metaverse"?
3 Relevance and Risks to Children
4 Overarching Child Privacy and Safeguarding Legal Framework
5 Design of Virtual Reality Devices
6 Design of the Virtual Spaces in the Metaverse
6.1 PETs (and Other 'Privacy by Law' Initiatives)
6.2 DPIA
7 Could Consumer Laws Be the/an Answer?
8 Data Protection Challenges in the Metaverse
8.1 Territorial Scope
8.2 Consent
8.3 Necessity for the Performance of a Contract and Legitimate Interest
8.4 Augmented Privacy Notice
9 Safety of Children in the Metaverse
9.1 Child Exploitation
9.2 Gambling
10 Broader Policy Options
11 Conclusion
References
Home Alone? Exploring the Geographies of Digitally-Mediated Privacy Practices at Home During the COVID-19 Pandemic
1 Introduction
2 Conceptual Discussions
2.1 Privacy is Collective
2.2 Privacy is Contextual
2.3 Privacy is Spatial
2.4 Privacy in the Pandemic
3 Conceptual Framework
4 Methods
4.1 Research Design: Semi-structured Interviews
4.2 Data Analysis: Thematic Analysis
5 Results and Discussion
5.1 The Blurring of the Work-Life Divide
5.2 Collective Dimensions of Privacy in Times of Pandemic
6 Future Research and Conclusions
6.1 Further Research and Practice Recommendations
6.2 Conclusions
A Interview Questions
A.1 Introduction
A.2 Information Disclosure
A.3 Changes in Information Disclosure
A.4 General Privacy Practices
A.5 The Importance of Privacy
A.6 Internet Tools for Fighting COVID-19
A.7 Wrap-Up
B Code Book
C Interview Question Formulation
References
Modelling Perceptions of Privacy
From Dark Patterns to Fair Patterns? Usable Taxonomy to Contribute Solving the Issue with Countermeasures
1 Introduction
2 Current State of Play on Dark Patterns: Prevalence, Evidence of Harms and Legal Framework
2.1 Definitions and Prevalence
2.2 Evidence of Serious Individual and Structural Harms
2.3 Legal Framework
3 Usable Taxonomy to Empower All Stakeholders to Take Action and Fight Against Dark Patterns
3.1 Related Work
3.2 Proposal of a Usable Taxonomy
4 Discussion
5 Conclusion
References
A Singular Approach to Address Privacy Issues by the Data Protection and Privacy Relationships Model (DAPPREMO)
1 Introduction
2 Application of the Set Theory
3 The Relationships Between Objects and Those Between Subassemblies
4 Description of a Complex Multidimensional Model
5 The Model and the Role of the Subjects
6 DAPPREMO's Concrete Applications for Individuals and Institutions, and Future Developments: The Use of Artificial Intelligence
7 Conclusions
References
Author Index

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