The Risk-Based Approach to Data Protection

2020 ◽  
Author(s):  
Raphaël Gellert
Keyword(s):  
Risk Management ◽  
Data Protection ◽  
Personal Data ◽  
Management Tools ◽  
General Data Protection Regulation ◽  
Regulation Theory ◽  
Régulation Theory ◽  
General Data ◽  
Data Protection Law ◽  
The Way

The main goal of this book is to provide an understanding of what is commonly referred to as “the risk-based approach to data protection”. An expression that came to the fore during the overhaul process of the EU’s General Data Protection Regulation (GDPR)—even though it can also be found in other statutes under different acceptations. At its core it consists in endowing the regulated organisation that process personal data with increased responsibility for complying with data protection mandates. Such increased compliance duties are performed through risk management tools. It addresses this topic from various perspectives. In framing the risk-based approach as the latest model of a series of regulation models, the book provides an analysis of data protection law from the perspective of regulation theory as well as risk and risk management literatures, and their mutual interlinkages. Further, it provides an overview of the policy developments that led to the adoption of such an approach, which it discusses in the light of regulation theory. It also includes various discussions pertaining to the risk-based approach’s scope and meaning, to the way it has been uptaken in statutes including key provisions such as accountability and data protection impact assessments, or to its potential and limitations. Finally, it analyses how the risk-based approach can be implemented in practice by providing technical analyses of various data protection risk management methodologies.

The “Riskification” of European Data Protection Law through a two-fold Shift

2017 ◽  
Vol 8 (3) ◽  
pp. 506-540 ◽  
Author(s):  
Milda MACENAITE
Keyword(s):  
Risk Management ◽  
Data Protection ◽  
Personal Data ◽  
Risk Regulation ◽  
General Data Protection Regulation ◽  
Regulation Mechanisms ◽  
General Data ◽  
Data Protection Law ◽  
Practical Level

The importance of the concept of risk and risk management in the data protection field has grown explosively with the adoption of the General Data Protection Regulation (2016/679). The article explores the concept and the role of risk, as well as associated risk regulation mechanisms in EU data protection law. It shows that with the adoption of the General Data Protection Regulation there is evidence of a two-fold shift: first on a practical level, a shift towards risk-based data protection enforcement and compliance, and second a shift towards risk regulation on the broader regulatory level. The article analyses these shifts to enhance the understanding of the changing relationship between risk and EU data protection law. The article also discusses associated potential challenges when trying to manage multiple and heterogeneous risks to the rights and freedoms of individuals resulting from the processing of personal data.

Personal Data in Insolvency Proceedings: The Interface between the New General Data Protection Regulation and (German) Insolvency Law

2019 ◽  
Vol 16 (6) ◽  
pp. 724-745
Author(s):  
Ronny Hauck
Keyword(s):  
Data Protection ◽  
German Law ◽  
Personal Data ◽  
Third Party ◽  
Insolvency Law ◽  
General Data Protection Regulation ◽  
General Data ◽  
Data Protection Law ◽  
Principle Of Proportionality ◽  
Insolvency Proceedings

When the General Data Protection Regulation (henceforth: GDPR) came into force, it quickly became clear that the new data protection law would strongly influence many different areas of law. This article deals with the relationship between data protection law and insolvency law, which was hardly considered before the GDPR was adopted. This relationship is particularly relevant where personal data is to be sold as asset in insolvency proceedings. As will be shown, the new data protection law imposes requirements on such data transfers which are very difficult to fulfil. The main problem is that in German law, personal data is not transferable because it is considered part of a subject’s personality. This situation is comparable to German copyright law, since the copyright itself is a non-transferable good. However, just as usage rights in copyright, the rights to use the personal data can be transferred to a third party provided that the requirements of the GDPR are satisfied. This article will comprehensively analyse under which conditions a transfer of such rights would be possible in insolvency proceedings. To create a balanced relationship between data protection law and insolvency law, the principle of proportionality is of crucial importance in this respect.

scholarly journals Algorithms that Remember: Model Inversion Attacks and Data Protection Law

2018 ◽  
Author(s):  
Michael Veale ◽  
Reuben Binns ◽  
Lilian Edwards
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
Training Data ◽  
Future Directions ◽  
Model Inversion ◽  
General Data Protection Regulation ◽  
General Data ◽  
Inference Attacks ◽  
Data Protection Law ◽  
Use Of Models

Cite as: Michael Veale, Reuben Binns and Lilian Edwards (2018) Algorithms That Remember: Model Inversion Attacks and Data Protection Law. Philosophical Transactions A, forthcoming. doi:10.1098/rsta.2018.0083Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms. The EU's recent General Data Protection Regulation (GDPR) has been seen as a core tool for achieving better governance of this area. While the GDPR does apply to the use of models in some limited situations, most of its provisions relate to the governance of personal data, while models have traditionally been seen as intellectual property. We present recent work from the information security literature around `model inversion' and `membership inference' attacks, which indicate that the process of turning training data into machine learned systems is not one-way, and demonstrate how this could lead some models to be legally classified as personal data. Taking this as a probing experiment, we explore the different rights and obligations this would trigger and their utility, and posit future directions for algorithmic governance and regulation.

The Personal Data Protection Bill, 2018: India’s regulatory journey towards a comprehensive data protection law

2020 ◽  
Vol 28 (1) ◽  
pp. 1-19
Author(s):  
Deva Prasad M ◽  
Suchithra Menon C
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
Legal Framework ◽  
The European Union ◽  
General Data Protection Regulation ◽  
Personal Data Protection ◽  
Supreme Court Of India ◽  
Indian Context ◽  
General Data ◽  
Data Protection Law

Abstract This article analyses the relevance of Personal Data Protection Bill, 2018 for developing a data protection legal framework in India. In this regard, the article attempts to analyse the evolution process of comprehensive personal data protection law in the Indian context. The manner in which the Personal Data Protection Bill, 2018 will revamp and strengthen the existing data protection regulatory framework forms the major edifice of this article. The article also dwells on the significant role played by the fundamental right to privacy judgment (Justice K.S. Puttaswamy v Union of India) of Supreme Court of India, thus preparing the regulatory ground for the evolution of the Personal Data Protection Bill, 2018. The influence of the European Union General Data Protection Regulation in shaping the Indian legal framework is highlighted. The article also discusses pertinent legal concerns that could question the effectiveness of the proposed data protection legal framework in the Indian context.

scholarly journals Certain Issues of Innovations Affecting the Insurance Business in the Light of the GDPR and Hungarian Insurance Law

2021 ◽  
Vol 10 (1) ◽  
pp. 35-53
Author(s):  
Mário Čertický
Keyword(s):  
Risk Management ◽  
Data Protection ◽  
Personal Data ◽  
Continuous Data ◽  
The Internet ◽  
Technological Innovations ◽  
Insurance Law ◽  
General Data Protection Regulation ◽  
General Data ◽  
Insurance Business

Technological innovations affect many sectors of the economy, including the insurance business. Among these innovations, IoT-based (Internet of Things) solutions can be highlighted, the main feature of which is that real-time and continuous data collection is performed using the Internet, thus optimizing the risk management of the insurer. Given that a significant part of the data thus collected constitutes personal data, the rules of the General Data Protection Regulation (GDPR) should apply. The data protection examination of the technologies affecting the insurance institution raises several issues, which, in my view, significantly impede the application of these technological achievements. The study aims to explore these problems and attempts to make proposals to solve them.

scholarly journals Application of Blockchain in Education: GDPR-Compliant and Scalable Certification and Verification of Academic Information

2021 ◽  
Vol 11 (10) ◽  
pp. 4537
Author(s):  
Christian Delgado-von-Eitzen ◽  
Luis Anido-Rifón ◽  
Manuel J. Fernández-Iglesias
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
General Data Protection Regulation ◽  
Certification System ◽  
Proposed Model ◽  
Different Types ◽  
International Regulations ◽  
Innovative Solution ◽  
General Data ◽  
Academic Information

Blockchain technologies are awakening in recent years the interest of different actors in various sectors and, among them, the education field, which is studying the application of these technologies to improve information traceability, accountability, and integrity, while guaranteeing its privacy, transparency, robustness, trustworthiness, and authenticity. Different interesting proposals and projects were launched and are currently being developed. Nevertheless, there are still issues not adequately addressed, such as scalability, privacy, and compliance with international regulations such as the General Data Protection Regulation in Europe. This paper analyzes the application of blockchain technologies and related challenges to issue and verify educational data and proposes an innovative solution to tackle them. The proposed model supports the issuance, storage, and verification of different types of academic information, both formal and informal, and complies with applicable regulations, protecting the privacy of users’ personal data. This proposal also addresses the scalability challenges and paves the way for a global academic certification system.

scholarly journals Algorithms that remember: model inversion attacks and data protection law

2018 ◽  
Vol 376 (2133) ◽  
pp. 20180083 ◽  
Author(s):  
Michael Veale ◽  
Reuben Binns ◽  
Lilian Edwards
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
Training Data ◽  
Theme Issue ◽  
Future Directions ◽  
Model Inversion ◽  
General Data Protection Regulation ◽  
General Data ◽  
Inference Attacks ◽  
Use Of Models

Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms. The EU's recent General Data Protection Regulation (GDPR) has been seen as a core tool for achieving better governance of this area. While the GDPR does apply to the use of models in some limited situations, most of its provisions relate to the governance of personal data, while models have traditionally been seen as intellectual property. We present recent work from the information security literature around ‘model inversion’ and ‘membership inference’ attacks, which indicates that the process of turning training data into machine-learned systems is not one way, and demonstrate how this could lead some models to be legally classified as personal data. Taking this as a probing experiment, we explore the different rights and obligations this would trigger and their utility, and posit future directions for algorithmic governance and regulation. This article is part of the theme issue ‘Governing artificial intelligence: ethical, legal, and technical opportunities and challenges’.

Regulatory Challenges of Data Mining Practices: The Case of the Never-ending Lifecycles of ‘Health Data’

2018 ◽  
Vol 25 (3) ◽  
pp. 284-307
Author(s):  
Giovanni Comandè ◽  
Giulia Schneider
Keyword(s):  
Data Mining ◽  
Data Protection ◽  
Personal Data ◽  
Health Data ◽  
General Level ◽  
General Data Protection Regulation ◽  
The Face ◽  
General Data ◽  
Level Of Analysis

Abstract Health data are the most special of the ‘special categories’ of data under Art. 9 of the General Data Protection Regulation (GDPR). The same Art. 9 GDPR prohibits, with broad exceptions, the processing of ‘data concerning health’. Our thesis is that, through data mining technologies, health data have progressively undergone a process of distancing from the healthcare sphere as far as the generation, the processing and the uses are concerned. The case study aims thus to test the endurance of the ‘special category’ of health data in the face of data mining technologies and the never-ending lifecycles of health data they feed. At a more general level of analysis, the case of health data shows that data mining techniques challenge core data protection notions, such as the distinction between sensitive and non-sensitive personal data, requiring a shift in terms of systemic perspectives that the GDPR only partly addresses.

scholarly journals Data Sharing Under the General Data Protection Regulation

Hypertension ◽  
2021 ◽  
Vol 77 (4) ◽  
pp. 1029-1035
Author(s):  
Antonia Vlahou ◽  
Dara Hallinan ◽  
Rolf Apweiler ◽  
Angel Argiles ◽  
Joachim Beige ◽  
...  
Keyword(s):  
European Union ◽  
Data Protection ◽  
Personal Data ◽  
Research Approach ◽  
The European Union ◽  
General Data Protection Regulation ◽  
Personal Data Protection ◽  
Protection Legislation ◽  
General Data ◽  
Almost All

The General Data Protection Regulation (GDPR) became binding law in the European Union Member States in 2018, as a step toward harmonizing personal data protection legislation in the European Union. The Regulation governs almost all types of personal data processing, hence, also, those pertaining to biomedical research. The purpose of this article is to highlight the main practical issues related to data and biological sample sharing that biomedical researchers face regularly, and to specify how these are addressed in the context of GDPR, after consulting with ethics/legal experts. We identify areas in which clarifications of the GDPR are needed, particularly those related to consent requirements by study participants. Amendments should target the following: (1) restricting exceptions based on national laws and increasing harmonization, (2) confirming the concept of broad consent, and (3) defining a roadmap for secondary use of data. These changes will be achieved by acknowledged learned societies in the field taking the lead in preparing a document giving guidance for the optimal interpretation of the GDPR, which will be finalized following a period of commenting by a broad multistakeholder audience. In parallel, promoting engagement and education of the public in the relevant issues (such as different consent types or residual risk for re-identification), on both local/national and international levels, is considered critical for advancement. We hope that this article will open this broad discussion involving all major stakeholders, toward optimizing the GDPR and allowing a harmonized transnational research approach.

scholarly journals The EU General Data Protection Regulation (GDPR)

2020 ◽  
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
Privacy Regulation ◽  
General Data Protection Regulation ◽  
Data Protection Directive ◽  
Ongoing Work ◽  
Protection Legislation ◽  
Recent Reform ◽  
General Data ◽  
The Eu

This new book provides an article-by-article commentary on the new EU General Data Protection Regulation. Adopted in April 2016 and applicable from May 2018, the GDPR is the centrepiece of the recent reform of the EU regulatory framework for protection of personal data. It replaces the 1995 EU Data Protection Directive and has become the most significant piece of data protection legislation anywhere in the world. This book is edited by three leading authorities and written by a team of expert specialists in the field from around the EU and representing different sectors (including academia, the EU institutions, data protection authorities, and the private sector), thus providing a pan-European analysis of the GDPR. It examines each article of the GDPR in sequential order and explains how its provisions work, thus allowing the reader to easily and quickly elucidate the meaning of individual articles. An introductory chapter provides an overview of the background to the GDPR and its place in the greater structure of EU law and human rights law. Account is also taken of closely linked legal instruments, such as the Directive on Data Protection and Law Enforcement that was adopted concurrently with the GDPR, and of the ongoing work on the proposed new E-Privacy Regulation.

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