Anonymization, tokenization, encryption. How to recover unrecoverable data

2018 ◽  
Vol 0 (6/2017) ◽  
pp. 9-13
Author(s):  
Olga Dzięgielewska
Keyword(s):  
Risk Analysis ◽  
Data Protection ◽  
Data Privacy ◽  
Personal Data ◽  
Insider Threat ◽  
General Data Protection Regulation ◽  
Analysis Phase ◽  
Data Layer ◽  
General Data ◽  
Financial Consequences

The data privacy is currently vastly commented topic among all the organizations which process personal data due to the introduction of the European Union’s General Data Protection Regulation. Existing methods of data protection are believed to be sufficient as they meet the risk-based approach requirements in every mature organization, yet the number of publicly known data breaches confirms that this assumption is false. The aftermath of such incidents in countless cases prove that the risk-based approach failed as the reputational and financial consequences by far exceed the original estimations. This paper stressed the importance of the data layer protection from the planning, through design, until maintenance stages in the database lifecycle, as numerous attack vectors originating from the insider threat and targeting the data layer still sneak through unnoticed during the risk analysis phase.

scholarly journals Delegation-Based Personal Data Processing Request Notarization Framework for GDPR Based on Private Blockchain

2021 ◽  
Vol 11 (22) ◽  
pp. 10574
Author(s):  
Sung-Soo Jung ◽  
Sang-Joon Lee ◽  
Ieck-Chae Euom
Keyword(s):  
Data Processing ◽  
Data Protection ◽  
Data Privacy ◽  
Personal Data ◽  
General Data Protection Regulation ◽  
Personal Data Protection ◽  
Compliance Audit ◽  
General Data ◽  
Data Controller ◽  
Data Subject

With the growing awareness regarding the importance of personal data protection, many countries have established laws and regulations to ensure data privacy and are supervising managements to comply with them. Although various studies have suggested compliance methods of the general data protection regulation (GDPR) for personal data, no method exists that can ensure the reliability and integrity of the personal data processing request records of a data subject to enable its utilization as a GDPR compliance audit proof for an auditor. In this paper, we propose a delegation-based personal data processing request notarization framework for GDPR using a private blockchain. The proposed notarization framework allows the data subject to delegate requests to process of personal data; the framework makes the requests to the data controller, which performs the processing. The generated data processing request and processing result data are stored in the blockchain ledger and notarized via a trusted institution of the blockchain network. The Hypderledger Fabric implementation of the framework demonstrates the fulfillment of system requirements and feasibility of implementing a GDPR compliance audit for the processing of personal data. The analysis results with comparisons among the related works indicate that the proposed framework provides better reliability and feasibility for the GDPR audit of personal data processing request than extant methods.

Data Protection Commissioner v. Facebook Ireland Ltd. and Maximillian Schrems (C.J.E.U.)

2021 ◽  
Vol 60 (1) ◽  
pp. 53-98
Author(s):  
Michael S. Aktipis ◽  
Ron B. Katwan
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
Personal Data ◽  
The United States ◽  
Transfer Mechanism ◽  
The European Union ◽  
Privacy Concerns ◽  
General Data Protection Regulation ◽  
General Data ◽  
The Eu

On July 16, 2020, the Court of Justice of the European Union (CJEU) issued its ruling in Data Protection Commissioner v. Facebook Ireland Limited and Maximillian Schrems, commonly known as Schrems II, invalidating the EU–U.S. Privacy Shield as a valid transfer mechanism under the EU's General Data Protection Regulation (GDPR) and creating significant legal uncertainty for the continued availability of another widely used transfer mechanism, Standard Contractual Clauses (SCCs), for transfers of EU personal data from commercial entities in the EU to the United States. The widely anticipated ruling marked the second time in five years that the CJEU had invalidated the legal foundation for such data transfers, which in both cases had been the result of a carefully negotiated compromise balancing European data privacy concerns with statutory and constitutional limitations of the U.S. system (see Schrems I).

scholarly journals Can Visual Design Provide Legal Transparency? The Challenges for Successful Implementation of Icons for Data Protection

Design Issues ◽  
2020 ◽  
Vol 36 (3) ◽  
pp. 82-96
Author(s):  
Arianna Rossi ◽  
Monica Palmirani
Keyword(s):  
Data Protection ◽  
Participatory Design ◽  
Data Privacy ◽  
Personal Data ◽  
Successful Implementation ◽  
The European Union ◽  
General Data Protection Regulation ◽  
General Data ◽  
Legal Ontologies ◽  
Machine Readable

Design is a key player in the future of data privacy and data protection. The General Data Protection Regulation (GDPR) established by the European Union aims to rebalance the information asymmetry between the organizations that process personal data and the individuals to which that data refers. Machine-readable, standardized icons that present a “meaningful overview of the intended processing” are suggested by the law as a tool to enhance the transparency of information addressed to data subjects. However, no specific guidelines have been provided, and studies on privacy iconography are very few. This article describes research conducted on the creation and evaluation of icons representing data protection concepts. First, we introduce the methodology used to design the Data Protection Icon Set (DaPIS): participatory design methods combined with legal ontologies and machine-readable representations. Second, we discuss some of the challenges that have been faced in the development and evaluation of DaPIS and similar icon sets. Third, we provide some tentative responses and indicate a way forward for evaluation of the effectiveness of privacy icons and their widespread adoption.

The Analysis of Risks to Personal Data Security

2020 ◽  
Vol 34 (34) ◽  
pp. 256-267
Author(s):  
Sylwia Kosznik-Biernacka
Keyword(s):  
Risk Analysis ◽  
Data Protection ◽  
Personal Data ◽  
Careful Analysis ◽  
General Data Protection Regulation ◽  
Analysis And Evaluation ◽  
Personal Data Protection ◽  
Analysis Methodology ◽  
General Data ◽  
The Eu

Article 32 of the EU General Data Protection Regulation imposes the obligation to implement appropriate safeguards to protect personal data. It states that the application of adequate measures is to be preceded by a risk analysis and evaluation. In the current paper, as the main risk factors, probability and consequences were assumed that take into account the basic attributes of information, i.e. confidentiality, integrity and availability. Next, a risk analysis methodology based on the risk matrix is proposed. The issue discussed in the publication is currently valid and still requires careful analysis in order to develop universal standards aimed at establishing certification mechanisms as well as quality labels and markings in terms of personal data protection.

Web Data and the Relationship Between the General Data Protection Regulation in Europe and Brazil

2021 ◽  
pp. 222-233
Author(s):  
Moisés Rockembach ◽  
Armando Malheiro da Silva
Keyword(s):  
Business Model ◽  
Data Protection ◽  
Data Privacy ◽  
Ethical Issues ◽  
Personal Data ◽  
Web Data ◽  
General Data Protection Regulation ◽  
Regulatory Instruments ◽  
General Data ◽  
The Relationship

From the consolidation of the application of European data protection regulations and the recent adoption of Brazilian data protection regulations, we are faced with a scenario that crosses borders. In a world marked by companies whose business model is the analysis and commercialization of personal data and of governments that use their citizens' data for control and surveillance, it is imperative to discuss the necessary characteristics to foster a society that respects ethical and legal values regarding data privacy and consented uses there; the authors address concepts and cases that they consider important for the establishment of reflections on the use of web data. They also take into account ethical issues and regulatory instruments in Europe and Brazil, analyzing the strongness and weaknesses in the implementation of data protection and privacy.

scholarly journals Can the GDPR and Freedom of Expression Coexist?

AJIL Unbound ◽  
2020 ◽  
Vol 114 ◽  
pp. 31-34
Author(s):  
Nani Jansen Reventlow
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
Freedom Of Expression ◽  
Personal Information ◽  
Personal Data ◽  
Raw Material ◽  
Individual Data ◽  
General Data Protection Regulation ◽  
General Data ◽  
The Right

The General Data Protection Regulation (GDPR) imposes important transparency and accountability requirements on different actors who process personal data. This is great news for the protection of individual data privacy. However, given that “personal information and human stories are the raw material of journalism,” what does the GDPR mean for freedom of expression and especially for journalistic activity? This essay argues that, although EU states seem to have taken their data protection obligations under the GDPR seriously, efforts to balance this against the right to freedom of expression have been more uneven. The essay concludes that it is of key importance to ensure that the GDPR's safeguards for data privacy do not compromise a free press.

A Layered Approach to Jurisdiction

2017 ◽  
Author(s):  
Dan Jerker B. Svantesson
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
General Data Protection Regulation ◽  
Legal Rules ◽  
Privacy Laws ◽  
Scope Of Application ◽  
General Data ◽  
Layered Approach ◽  
Substantive Law

This chapter observes how it may be inappropriate to apply a single jurisdictional threshold to diverse instruments such as data privacy laws. In the light of this observation, a proposal is outlined for a ‘layered approach’ under which the substantive law rules of such instruments are broken up into different layers, with different jurisdictional thresholds applied to each such layer. This layered approach is discussed primarily as a technique to be utilized in legal drafting, but it may also be applied in the interpretation and application of legal rules. Article 3 of the European Union’s General Data Protection Regulation, which determines that regulation’s scope of application in a territorial sense, provides a particularly useful lens through which to approach this topic and, thus, the discussion is largely centred around that Article.

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.

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’.

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