Privacy And Data Protection Challenges In The Distributed Era
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| Author | : Eugenia Politou |
| Publisher | : Springer Nature |
| Total Pages | : 195 |
| Release | : 2021-10-22 |
| Genre | : Technology & Engineering |
| ISBN | : 3030854434 |
This book examines the conflicts arising from the implementation of privacy principles enshrined in the GDPR, and most particularly of the ``Right to be Forgotten'', on a wide range of contemporary organizational processes, business practices, and emerging computing platforms and decentralized technologies. Among others, we study two ground-breaking innovations of our distributed era: the ubiquitous mobile computing and the decentralized p2p networks such as the blockchain and the IPFS, and we explore their risks to privacy in relation to the principles stipulated by the GDPR. In that context, we identify major inconsistencies between these state-of-the-art technologies with the GDPR and we propose efficient solutions to mitigate their conflicts while safeguarding the privacy and data protection rights. Last but not least, we analyse the security and privacy challenges arising from the COVID-19 pandemic during which digital technologies are extensively utilized to surveil people’s lives.
| Author | : Edward Curry |
| Publisher | : Springer Nature |
| Total Pages | : 399 |
| Release | : 2021-08-01 |
| Genre | : Computers |
| ISBN | : 3030681769 |
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
| Author | : Abbas Moallem |
| Publisher | : Springer Nature |
| Total Pages | : 336 |
| Release | : |
| Genre | : |
| ISBN | : 3031613791 |
| Author | : Isak Karabegović |
| Publisher | : Springer Nature |
| Total Pages | : 1151 |
| Release | : 2022-05-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3031052307 |
This book features papers focusing on the implementation of new and future technologies, which were presented at the International Conference on New Technologies, Development and Application, held at the Academy of Science and Arts of Bosnia and Herzegovina in Sarajevo on 23rd–25th June 2022. It covers a wide range of future technologies and technical disciplines, including complex systems such as industry 4.0; patents in industry 4.0; robotics; mechatronics systems; automation; manufacturing; cyber-physical and autonomous systems; sensors; networks; control, energy, renewable energy sources; automotive and biological systems; vehicular networking and connected vehicles; intelligent transport, effectiveness and logistics systems, smart grids, nonlinear systems, power, social and economic systems, education, IoT. The book New Technologies, Development and Application V is oriented towards Fourth Industrial Revolution “Industry 4.0”, in which implementation will improve many aspects of human life in all segments and lead to changes in business paradigms and production models. Further, new business methods are emerging, transforming production systems, transport, delivery and consumption, which need to be monitored and implemented by every company involved in the global market.
| Author | : George A. Tsihrintzis |
| Publisher | : Springer Nature |
| Total Pages | : 439 |
| Release | : |
| Genre | : |
| ISBN | : 3031623169 |
| Author | : Maria Virvou |
| Publisher | : Springer Nature |
| Total Pages | : 219 |
| Release | : 2023-02-17 |
| Genre | : Technology & Engineering |
| ISBN | : 3031175832 |
This book contains extended versions of the works and new research results presented at the 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022). JCKBSE2022 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it to be rescheduled as an online conference. JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence on Software Engineering. The 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022) was organized by the Department of Informatics of the University of Piraeus, Greece. This book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering. It is also valuable to general readers in the fields of artificial and computational intelligence and, more generally, computer science, wishing to learn more about the exciting field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each chapter helps readers to probe deeper into the application areas of interest to them.
| Author | : Kai Rannenberg |
| Publisher | : Springer Nature |
| Total Pages | : 187 |
| Release | : |
| Genre | : |
| ISBN | : 303161089X |
| Author | : Maria Virvou |
| Publisher | : Springer Nature |
| Total Pages | : 209 |
| Release | : 2022-10-17 |
| Genre | : Technology & Engineering |
| ISBN | : 3031076508 |
Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions, lead current research toward the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. The book at hand, devoted to Smart Software Applications in Cyber-Physical Systems, constitutes the second volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in Smart Software Applications in (i) Scientific Document Processing, (ii) Enterprise Modeling, (iii) Education, (iv) Health care and Medicine, and (v) Infrastructure Monitoring. Professors, researchers, scientists, engineers, and students in artificial intelligence, software engineering, and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.
| Author | : J.L. Hernández Ramos |
| Publisher | : IOS Press |
| Total Pages | : 204 |
| Release | : 2020-03-12 |
| Genre | : Computers |
| ISBN | : 1643680536 |
The Internet of Things (IoT) can be defined as any network of things capable of generating, storing and exchanging data, and in some cases acting on it. This new form of seamless connectivity has many applications: smart cities, smart grids for energy management, intelligent transport, environmental monitoring, healthcare systems, etc. and EU policymakers were quick to realize that machine-to-machine communication and the IoT were going to be vital to economic development. It was also clear that the security of such systems would be of paramount importance and, following the European Commission’s Cybersecurity Strategy of the European Union in 2013, the EU’s Horizon 2020 programme was set up to explore available options and possible approaches to addressing the security and privacy issues of the IoT. This book presents 10 papers which have emerged from the research of the Horizon 2020 and CHIST-ERA programmes, and which address a wide cross-section of projects ranging from the secure management of personal data and the specific challenges of the IoT with respect to the GDPR, through access control within a highly dynamic IoT environment and increasing trust with distributed ledger technologies, to new cryptographic approaches as a counter-measure for side-channel attacks and the vulnerabilities of IoT-based ambient assisted living systems. The security and safety of the Internet of Things will remain high on the agenda of policymakers for the foreseeable future, and this book provides an overview for all those with an interest in the field.
| Author | : Ruth, J. Anitha |
| Publisher | : IGI Global |
| Total Pages | : 557 |
| Release | : 2024-05-31 |
| Genre | : Computers |
| ISBN | : |
In the relentless battle against escalating cyber threats, data security faces a critical challenge the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.
