Attitudes Towards Big Data Practices And The Institutional Framework Of Privacy And Data Protection A Population Survey

In the contemporary information society, organisations increasingly rely on the collection and analysis of large-scale data (popularly called ‘big data’) to make decisions. These processes, which take place largely beyond the individual’s knowledge, produce a cascade of effects that go beyond privacy and data protection. Should we focus on the possibilities of tackling these often negative effects through other areas of law, or maybe even find new solutions to cope with the dark side of big data? This ground-breaking book is the first to address this crucially important question in detail. Among the issues raised in the analysis are such vital elements as the following: − what is meant by ‘big data’; – ‘privacy’ according to the European Court of Human Rights and the Court of Justice of the European Union; – what the European Union legal framework on privacy and data protection consists of and how it functions in the light of big data; – what companies, governments and other organisations are permitted to do with big data under the current regulatory framework; – the central importance of personal autonomy; – circumstances that influence whether or not the right to privacy is triggered; – big data’s possible impact on democracy through, inter alia, potentially limiting freedom of expression; – how governmental or corporate surveillance chills the receiver’s gathering of information and ideas; – selective offering of choices or information, or manipulation of people’s ideas; – procedural aspects that influence the extrapolation of normative concepts of privacy and data protection; and – how discrimination occurs in big data. This book foregrounds a critical scrutiny of commercial uses of big data – its scale, its limited capacity for independent oversight and the expected prevalence of interference with individuals’ rights. The author’s conclusions explore possible legal alternatives to mitigate the negative impact of big data, using legal instruments, case law and legal academic literature in her analysis. Because the amount of digital data keeps growing and the private lives of individuals are increasingly taking place online – and because of the opacity of the big data process, the fundamental values that are at stake, and the speed of technological developments compared to the pace of legal reform – this comprehensive assessment of flaws in the current framework and possible practical solutions will be warmly welcomed by practitioners, policymakers and government officials in all legal fields related to privacy and data protection.

This encyclopedia is the most comprehensive and up-to-date source of reference for sustainability in business and management. It covers both traditional and emerging concepts and terms and is fully international in its scope. More than 700 contributions of internationally renowned experts provide a definitive access to the knowledge in the area of sustainable and responsible management. All actors in the field will find reliable and up to date definitions and explanations of the key terms and concepts of management in this reference work. The Encyclopedia of Sustainable Management represents all aspects of management and business conduct. It takes sustainability as a management concept that gives due credit to the complexity and diverging constraints in which businesses and corporations act today, and it emphasizes and focuses approaches that help ensure that today's management decisions and actions will be the basis for tomorrow's prosperity.

This book brings together an impressive range of academic and intelligence professional perspectives to interrogate the social, ethical and security upheavals in a world increasingly driven by data. Written in a clear and accessible style, it offers fresh insights to the deep reaching implications of Big Data for communication, privacy and organisational decision-making. It seeks to demystify developments around Big Data before evaluating their current and likely future implications for areas as diverse as corporate innovation, law enforcement, data science, journalism, and food security. The contributors call for a rethinking of the legal, ethical and philosophical frameworks that inform the responsibilities and behaviours of state, corporate, institutional and individual actors in a more networked, data-centric society. In doing so, the book addresses the real world risks, opportunities and potentialities of Big Data.

This book offers guidance for US-based IT businesses on both sides of the Atlantic when dealing with big data and government data, since transatlantic data flows are key to the success of these enterprises. It offers practical insights into many of the data-protection challenges US companies in various industries face when seeking to comply with US and EU data-protection laws, and analyses the potential conflicts in the light of their risks and the way in which US-based cloud providers react to the uncertainties of the applicable data-protection rules. The book particularly focuses on the insights derived from a qualitative study conducted in 2016 with various cloud-based IT businesses in the Silicon Valley area, which shows the diversity of views on data protection and the many approaches companies take to this topic. Further, it discusses key data-protection issues in the field of big data and government data.

This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data. It focuses on the results obtained after applying a systematic mapping study and implementation of security in the big data for utilizing in business under the establishment of “Business Intelligence”. The chapters start with the definition of big data, discussions why security is used in business infrastructure and how the security can be improved. In this book, some of the data security and data protection techniques are focused and it presents the challenges and suggestions to meet the requirements of computing, communication and storage capabilities for data mining and analytics applications with large aggregate data in business.

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.