Privacy Technologies and Policy
7th Annual Privacy Forum, APF 2019, Rome, Italy, June 13-14, 2019, Proceedings
Published on 7. June 2019
XII, 211 pages
978-3-030-21752-5 (ISBN)
Description
This book constitutes the refereed conference proceedings of the 7th Annual Privacy Forum, APF 2019, held in Rome,
Italy, in June 2019.
The 11 revised full papers were carefully reviewed and selected from 49 submissions. The papers present original work on the themes of data protection and privacy and their repercussions on technology, business, government, law, society, policy and law enforcement bridging the gap between research, business models, and policy. They are organized in topical sections on transparency, users' rights, risk assessment, and applications.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
XII, 211 p. 45 illus., 27 illus. in color.
File size
9,87 MB
ISBN-13
978-3-030-21752-5 (9783030217525)
DOI
10.1007/978-3-030-21752-5
Schweitzer Classification
Other editions
Additional editions
Maurizio Naldi | Giuseppe F. Italiano | Kai Rannenberg
Privacy Technologies and Policy
7th Annual Privacy Forum, APF 2019, Rome, Italy, June 13-14, 2019, Proceedings
Book
06/2019
Springer
€53.49
Shipment within 7-9 days
Content
- Intro
- Preface
- Organization
- Contents
- Transparency
- Towards Real-Time Web Tracking Detection with T.EX - The Transparency EXtension
- 1 Introduction
- 2 Objectives and Requirements
- 3 Limitations
- 4 Related Work
- 5 Implementation
- 5.1 HTTP and HTTPS Traffic Logging and Recording
- 5.2 Persistent Storage of Records
- 5.3 Encryption and Decryption of Chunks
- 5.4 Data Visualization
- 6 Evaluation
- 7 Conclusion and Outlook
- References
- Towards Transparency in Email Tracking
- 1 Introduction
- 2 Related Work
- 3 System Overview
- 3.1 Adding a Service
- 3.2 Analyzing Emails
- 3.3 Providing Transparency
- 3.4 Challenges
- 4 Preliminary Results
- 4.1 Case Study 1: Individual Service Analysis
- 4.2 Case Study 2: A/B Testing
- 4.3 Case Study 3: Link Personalization
- 5 Future Work
- 6 Conclusion
- References
- Sharing Cyber Threat Intelligence Under the General Data Protection Regulation
- Abstract
- 1 Introduction
- 2 Methodology
- 2.1 Defining DataTags Related to Cybersecurity Information Sharing
- 2.2 Policy Space
- 2.3 Decision Graph
- 3 Use Cases
- 4 Related Work
- 5 Conclusion and Future Work
- Acknowledgment
- References
- Users' Rights
- Fight to Be Forgotten: Exploring the Efficacy of Data Erasure in Popular Operating Systems
- 1 Introduction
- 2 Background
- 2.1 Personal Data Hygiene
- 2.2 Delete and Erase Functions
- 3 Methodology
- 3.1 Forensic Analysis
- 4 Results
- 4.1 macOS 10.14
- 4.2 Windows 10
- 4.3 Results of Forensic Analysis
- 5 Discussion
- 5.1 Default Options
- 5.2 Incorrect Terminology
- 5.3 Insufficient Guidance and Cues
- 5.4 OS-Independent Implications
- 6 Limitations
- 7 Conclusion
- References
- Privacy Beyond Confidentiality, Data Science Beyond Spying: From Movement Data and Data Privacy Towards a Wider Fundamental Rights Discourse
- 1 Introduction
- 2 Case Study 1: New York City Tax Rides Dataset
- 3 Case Study 2: AIS Data for Describing Migrant Rescue Operations
- 4 Towards a Comparative Analysis
- 5 Conclusion
- References
- Making Machine Learning Forget
- 1 Introduction
- 2 The ``Right-to-be-Forgotten
- 3 Privacy Leakage in Machine Learning Systems
- 4 Implementing ``Right-to-be-Forgotten'' in Machine Learning Models
- 4.1 Influence Functions
- 4.2 Differential Privacy
- 4.3 Machine Unlearning
- 5 Discussion and Conclusions
- References
- Risk Assessment
- A Multilateral Privacy Impact Analysis Method for Android Apps
- 1 Introduction
- 2 Data Acquisition Methodology
- 2.1 Permission Manifest Analysis (A1)
- 2.2 Privacy Policy Analysis (A2)
- 2.3 Permission Usage Analysis (A3)
- 2.4 User Reviews Analysis (A4)
- 3 Multilateral Analysis
- 3.1 Step A1: Permission Manifest Analysis
- 3.2 Step A2: Privacy Policy Analysis
- 3.3 Step A3: Permission Usage Analysis
- 3.4 Step A4: User Reviews Analysis
- 3.5 Synthesis of Analysis
- 4 Related Work
- 5 Conclusions and Future Work
- References
- Re-using Personal Data for Statistical and Research Purposes in the Context of Big Data and Artificial Intelligence
- Abstract
- 1 Introduction
- 2 The Purpose Limitation Principle in the Context of Big Data/AI
- 2.1 The Principle of Purpose Limitation
- 2.2 Challenges to the Purpose Limitation Principle in a World of Big Data/AI
- 3 The Research and Statistical Exemption Under GDPR
- 3.1 Scope of Application
- 3.2 Safeguards for Data Subjects' Rights and Freedoms
- 3.2.1 Principle of Data Minimization
- 3.2.2 Use of Techniques Such as Anonymization or Pseudonymization
- 3.2.3 Other Safeguards for Data Subjects' Rights and Freedoms
- 3.2.4 Big Data and AI Ethics
- 3.2.5 Derogations from Other GDPR Obligations
- 4 Privacy "Regulatory Sandboxes" to Enable Innovation Under GDPR
- 4.1 Benefits and Opportunities
- 4.2 Challenges and Risks
- 4.3 Addressing the Challenges and the Practicalities of the Set-up
- 5 Conclusion
- Bibliography
- Legalislation
- International Conventions
- European Union Legislation
- National Legislation
- Official Non-bidning Documents: Official EU Documents
- Official International Documents
- Official National Documents
- Articles
- IoT Security and Privacy Labels
- 1 Introduction
- 2 Related Work
- 3 Design of Security and Privacy Labels
- 3.1 Device Factors
- 3.2 Visual Layouts
- 3.3 Implementation
- 4 Case Study - TVT DVR
- 5 Discussion
- 6 Conclusion
- References
- Applications
- Digital Forensics and Privacy-by-Design: Example in a Blockchain-Based Dynamic Navigation System
- Abstract
- 1 Introduction
- 2 Related and Previous Work
- 3 Forensic Capabilities
- 3.1 HACIT Project
- 3.2 Hurdles on the Way
- 3.3 Forensic Investigation
- 3.4 Forensic Insurance
- 4 Conclusion and Future Works
- References
- A Data Protection by Design Model for Privacy Management in Electronic Health Records
- 1 Introduction
- 2 The Approach of Privacy by Design
- 2.1 The Origins of PbD and Its International Recognition
- 2.2 A Critical Perspective on Privacy by Design
- 2.3 Data Protection by Design
- 3 Electronic Health Records and Data Protection Law
- 3.1 The EU Legal Framework for EHRs
- 4 A DPbD Model for Privacy Management for the EHRs
- 4.1 Technical Measures for EHR
- 4.2 The Creation of the EHR
- 4.3 The Use of the EHR
- 4.4 Organisational Measures for EHR
- 5 Concluding Remarks
- References
- Security Analysis of Subject Access Request Procedures
- 1 Introduction
- 2 Threats to SAR Authentication and Recommendations of the DPAs
- 2.1 Threat Model
- 2.2 Recommendations of the EU Data Protection Authorities
- 3 Practical Evaluation of Websites and Third Party Trackers
- 3.1 Evaluation of Popular Websites
- 3.2 Evaluation of Third Party Trackers
- 4 Recommendations and Observations
- 4.1 Problem of Authentication
- 4.2 Problem of Validating Eligibility
- 5 Related Work
- 6 Conclusion
- References
- Author Index
