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Privacy Technologies and Policy : 12th Annual Privacy Forum, APF 2024, Karlstad, Sweden, September 4–5, 2024, Proceedings / / edited by Meiko Jensen, Cédric Lauradoux, Kai Rannenberg
Privacy Technologies and Policy : 12th Annual Privacy Forum, APF 2024, Karlstad, Sweden, September 4–5, 2024, Proceedings / / edited by Meiko Jensen, Cédric Lauradoux, Kai Rannenberg
Autore Jensen Meiko
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (262 pages)
Disciplina 303.4834
Altri autori (Persone) LauradouxCédric
RannenbergKai
Collana Lecture Notes in Computer Science
Soggetto topico Computers and civilization
Application software
Computer networks
Computer systems
Cryptography
Data encryption (Computer science)
Data protection
Computers and Society
Computer and Information Systems Applications
Computer Communication Networks
Computer System Implementation
Cryptology
Data and Information Security
ISBN 3-031-68024-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -- Implications of age assurance on privacy and data protection: A systematic threat model. -- Access Your Data... If You Can: An Analysis of Dark Patterns Against the Right of Access on Popular Websites. -- AI Cards: Towards an Applied Framework for Machine-Readable AI and Risk Documentation Inspired by the EU AI Act. -- Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage. -- Addressing Privacy Concerns in Joint Communication and Sensing for 6G Networks: Challenges and Prospects. -- The lawfulness of re-identification under data protection law. -- How to Drill Into Silos: Creating a Free-to-Use Dataset of Data Subject Access Packages. -- Another Data Dilemma in Smart Cities: the GDPR’s Joint Controllership Tightrope within Public-Private Collaborations. -- Privacy Promise vs. Tracking Reality in Pay-or-Tracking Walls. -- Data Governance and Neutral Data Intermediation: Legal Properties and Potential Semantic Constraints. -- No Transparency for Smart Toys. -- Implementing ISO/IEC TS 27560:2023 Consent Records and Receipts for GDPR and DGA.
Record Nr. UNINA-9910878982403321
Jensen Meiko  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Privacy Technologies and Policy : 11th Annual Privacy Forum, APF 2023, Lyon, France, June 1-2, 2023, Proceedings
Privacy Technologies and Policy : 11th Annual Privacy Forum, APF 2023, Lyon, France, June 1-2, 2023, Proceedings
Autore Rannenberg Kai
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer International Publishing AG, , 2024
Descrizione fisica 1 online resource (187 pages)
Altri autori (Persone) DrogkarisProkopios
LauradouxCédric
Collana Lecture Notes in Computer Science Series
ISBN 3-031-61089-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996601561303316
Rannenberg Kai  
Cham : , : Springer International Publishing AG, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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