Cloud computing and personal data processing: sorting-out legal requirements

2017 ◽  
pp. 219-242
Author(s):  
Ioulia Konstantinou ◽  
Irene Kamara
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Personal Data ◽  
Legal Requirements

scholarly journals Ochrona tajemnicy adwokackiej a usługi świadczone w chmurze obliczeniowej

2017 ◽  
pp. 153-173
Author(s):  
Marcin Rojszczak
Keyword(s):  
Cloud Computing ◽  
Personal Data ◽  
Public Cloud ◽  
Legal Requirements ◽  
The Public ◽  
Eu Member States ◽  
Cross Border ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Area Of Protection

The article presents most important issues related to cross-border processing of lawyers data containing professional secrets, including the processing of personal data. Author discusses risks associated with the lack of standardization in the area of protection of legal priviledge in cloud computing services in different jurisdictions, also between EU Member States. Article is supplemented by an analysis of terms of service and privacy policies of the largest providers of services in the public cloud (Google, Microsoft) in the context of the fulfillment of the legal requirements for the protection of personal data and the professional secrecy.

scholarly journals Record linkage of routine data with cohorts’ data of infants under European and Portuguese law

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Doetsch ◽  
I Lopes ◽  
R Redinha ◽  
H Barros
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Protection ◽  
Record Linkage ◽  
Data Science ◽  
Personal Data ◽  
Routine Data ◽  
Cohort Data ◽  
Education Data ◽  
Explicit Consent

Abstract The usage and exchange of “big data” is at the forefront of the data science agenda where Record Linkage plays a prominent role in biomedical research. In an era of ubiquitous data exchange and big data, Record Linkage is almost inevitable, but raises ethical and legal problems, namely personal data and privacy protection. Record Linkage refers to the general merging of data information to consolidate facts about an individual or an event that are not available in a separate record. This article provides an overview of ethical challenges and research opportunities in linking routine data on health and education with cohort data from very preterm (VPT) infants in Portugal. Portuguese, European and International law has been reviewed on data processing, protection and privacy. A three-stage analysis was carried out: i) interplay of threefold law-levelling for Record Linkage at different levels; ii) impact of data protection and privacy rights for data processing, iii) data linkage process' challenges and opportunities for research. A framework to discuss the process and its implications for data protection and privacy was created. The GDPR functions as utmost substantial legal basis for the protection of personal data in Record Linkage, and explicit written consent is considered the appropriate basis for the processing sensitive data. In Portugal, retrospective access to routine data is permitted if anonymised; for health data if it meets data processing requirements declared with an explicit consent; for education data if the data processing rules are complied. Routine health and education data can be linked to cohort data if rights of the data subject and requirements and duties of processors and controllers are respected. A strong ethical context through the application of the GDPR in all phases of research need to be established to achieve Record Linkage between cohort and routine collected records for health and education data of VPT infants in Portugal. Key messages GDPR is the most important legal framework for the protection of personal data, however, its uniform approach granting freedom to its Member states hampers Record Linkage processes among EU countries. The question remains whether the gap between data protection and privacy is adequately balanced at three legal levels to guarantee freedom for research and the improvement of health of data subjects.

scholarly journals Reconciliation of anti-money laundering instruments and European data protection requirements in permissionless blockchain spaces

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Iwona Karasek-Wojciechowicz
Keyword(s):  
Data Processing ◽  
Money Laundering ◽  
Data Protection ◽  
Task Force ◽  
Policy Instruments ◽  
Personal Data ◽  
General Data Protection Regulation ◽  
Terrorist Financing ◽  
The Government ◽  
High Level

AbstractThis article is an attempt to reconcile the requirements of the EU General Data Protection Regulation (GDPR) and anti-money laundering and combat terrorist financing (AML/CFT) instruments used in permissionless ecosystems based on distributed ledger technology (DLT). Usually, analysis is focused only on one of these regulations. Covering by this research the interplay between both regulations reveals their incoherencies in relation to permissionless DLT. The GDPR requirements force permissionless blockchain communities to use anonymization or, at the very least, strong pseudonymization technologies to ensure compliance of data processing with the GDPR. At the same time, instruments of global AML/CFT policy that are presently being implemented in many countries following the recommendations of the Financial Action Task Force, counteract the anonymity-enhanced technologies built into blockchain protocols. Solutions suggested in this article aim to induce the shaping of permissionless DLT-based networks in ways that at the same time would secure the protection of personal data according to the GDPR rules, while also addressing the money laundering and terrorist financing risks created by transactions in anonymous blockchain spaces or those with strong pseudonyms. Searching for new policy instruments is necessary to ensure that governments do not combat the development of all privacy-blockchains so as to enable a high level of privacy protection and GDPR-compliant data processing. This article indicates two AML/CFT tools which may be helpful for shaping privacy-blockchains that can enable the feasibility of such tools. The first tool is exceptional government access to transactional data written on non-transparent ledgers, obfuscated by advanced anonymization cryptography. The tool should be optional for networks as long as another effective AML/CFT measures are accessible for the intermediaries or for the government in relation to a given network. If these other measures are not available and the network does not grant exceptional access, the regulations should allow governments to combat the development of those networks. Effective tools in that scope should target the value of privacy-cryptocurrency, not its users. Such tools could include, as a tool of last resort, state attacks which would undermine the trust of the community in a specific network.

Cloud computing in seismic data processing based on Voronoi diagrams using Google App Engine

2015 ◽  
Vol 51 (5) ◽  
pp. 1041-1048 ◽  
Author(s):  
V. P. Potapov ◽  
V. N. Oparin ◽  
O. L. Giniyatullina ◽  
I. E. Kharlampenkov
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Seismic Data ◽  
Voronoi Diagrams ◽  
Seismic Data Processing

Cloud Data Management Based on Cloud Computing Technology

2014 ◽  
Vol 543-547 ◽  
pp. 3573-3576
Author(s):  
Yuan Jun Zou
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Data Processing ◽  
Development Planning ◽  
Computer Data ◽  
Cloud Data ◽  
Computing Platform ◽  
Convergence Error ◽  
Cloud Computing Platform ◽  
Cloud Data Processing

Cloud computing, networking and other high-end computer data processing technology are the important contents of eleven-five development planning in China. They have developed rapidly in recent years in the field of engineering. In this paper, we combine parallel computing with the collaborative simulation principle, design a cloud computing platform, establish the mathematical model of cloud data processing and parallel computing algorithm, and verify the applicability of algorithm through the numerical simulation. Through numerical calculation, cloud computing platform can be divided into complex grids, and the transmission speed is fast, which is eight times than the finite difference method. The mesh is meticulous, which reaches millions. Convergence error is minimum, only 0.001. The calculation accuracy is up to 98.36%.

scholarly journals Responsible Research on Social Networks

2018 ◽  
pp. 558-576
Author(s):  
Jon Crowcroft ◽  
Hamed Haddadi ◽  
Tristan Henderson
Keyword(s):  
Social Networks ◽  
Interpersonal Communication ◽  
Private Information ◽  
Online Social Networks ◽  
Personal Data ◽  
Legal Requirements ◽  
Pros And Cons ◽  
Conducting Research ◽  
Responsible Research ◽  
Responsible Manner

Researchers have found online social networks a goldmine for research into various aspects of social behavior and interpersonal communication. For example, observing social interaction between individuals and their engagement in conversations, or performing sentiment analysis on these communications, is often carried out for research in a number of disciplines such as health, sociology, or politics. Such studies introduce many challenges for conducting research in a responsible manner. Data may be repurposed or cross-correlated in ways that participants may not have anticipated or desired, private information may be collected, or legal requirements may not be met. This chapter explores some of the challenges and dilemmas faced by industry, academia, regulators, privacy advocates, and ultimately the individuals using these services. It discusses the pros and cons of the collection, analysis, and archiving of personal data for digital research. The chapter concludes by discussing theoretical and practical approaches that target these dilemmas.

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