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This book constitutes the refereed proceedings of the 33rd Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2019, held in Charleston, SC, USA, in July 2018. The 21 full papers presented were carefully reviewed and selected from 52 submissions. The papers present high-quality original research from academia, industry, and government on theoretical and practical aspects of information security. They are organized in topical sections on attacks, mobile and Web security, privacy, security protocol practices, distributed systems, source code security, and malware.
This book constitutes the refereed proceedings of the Third International Conference on HCI for Cybersecurity, Privacy and Trust, HCI-CPT 2021, held as part of the 23rd International Conference, HCI International 2021, which took place virtually in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. HCI-CPT 2021 includes a total of 30 papers; they were organized in topical sections named: usable security; security and privacy by design; user behavior analysis in cybersecurity; and security and privacy awareness.
The Digital Marketing and eCommerce Conference aims to bring together leading researchers and research scholars to exchange and share their experiences and research results on any aspects of ecommerce and digital marketing. This volume presents the proceedings of the 2023 edition in a collection of contributions with many original approaches. They address diverse areas of application such as online brand communities, channel design, online retailing, cryptocurrencies, user-generated content, TikTok, among others. A wide variety of theoretical and methodological approaches have been used.
These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS and machine learning. This thirty-third issue contains 9 selected papers which present new findings and innovative methodologies as well as discuss issues and challenges in the field of collective intelligence from big data and networking paradigms while addressing security, privacy, reliability and optimality to achieve QoS to the benefit of final users.
Conspiracy Theory Discourses addresses a crucial phenomenon in the current political and communicative context: conspiracy theories. The social impact of conspiracy theories is wide-ranging and their influence on the political life of many nations is increasing. Conspiracy Theory Discourses bridges an important gap by bringing discourse-based insights to existing knowledge about conspiracy theories, which has so far developed in research areas other than Linguistics and Discourse Studies. The chapters in this volume call attention to conspiracist discourses as deeply ingrained ways to interpret reality and construct social identities. They are based on multiple, partly overlapping analytical frameworks, including Critical Discourse Analysis, rhetoric, metaphor studies, multimodality, and corpus-based, quali-quantitative approaches. These approaches are an entry point to further explore the environments which enable the proliferation of conspiracy theories, and the paramount role of discourse in furthering conspiracist interpretations of reality.
The technology of information modelling and knowledge bases addresses the complexities of modelling in digital transformation and digital innovation, reaching beyond the traditional borders of information systems and academic research in computer science. This book presents 21 papers from the 31st International conference on Information Modeling and Knowledge Bases (EJC 2021), hosted by the Department Informatik of the University of Applied Sciences in Hamburg, Germany, and held as a virtual event from 7 to 9 September 2021 due to restrictions caused by the Corona virus. The conference provides a research forum for academics and practitioners dealing with information and knowledge to exchange scientific results and experiences, and EJC 2021 covered a wide range of themes extending knowledge discovery through conceptual modeling, knowledge and information modeling and discovery, linguistic modeling, cross-cultural communication and social computing, environmental modeling and engineering, and multimedia data modeling and systems. As always, the conference was open to new topics related to its main themes, meaning the content emphasis of the EJC conferences is always able to adapt to the changes taking place in the research field, and the 21 papers included here after rigorous review, selection and upgrading are the result of presentations, comments, and discussions during the conference. Providing an up to the minute overview of the technology of information modeling and knowledge bases, the book will be of interest to all those working in the field.
This is the first book to provide an in-depth coverage of all the developments, issues and challenges in secure databases and applications. It provides directions for data and application security, including securing emerging applications such as bioinformatics, stream information processing and peer-to-peer computing. Divided into eight sections,
Data has revolutionized the digital ecosystem. Readily available large datasets foster AI and machine learning automated solutions. The data generated from diverse and varied sources including IoT, social platforms, healthcare, system logs, bio-informatics, etc. contribute to and define the ethos of Big Data which is volume, velocity and variety. Data lakes formed by the amalgamation of data from these sources requires powerful, scalable and resilient storage and processing platforms to reveal the true value hidden inside this data mine. Data formats and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart cars, power grids etc., but also highlight the security and privacy issues in this age of big data. Security and privacy in big data is facing many challenges, such as generative adversary networks, efficient encryption and decryption algorithms, encrypted information retrieval, attribute-based encryption, attacks on availability, and reliability. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas. The book provides timely and comprehensive information for researchers and industry partners in communications and networking domains to review the latest results in security and privacy related work of Big Data. It will serve computer science and cybersecurity communities including researchers, academicians, students, and practitioners who have interest in big data trust privacy and security aspects. It is a comprehensive work on the most recent developments in security of datasets from varied sources including IoT, cyber physical domains, big data architectures, studies for trustworthy computing, and approaches for distributed systems and big data security solutions etc.
With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 33rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include distributed massive data streams, storage systems, scientific workflow scheduling, cost optimization of data flows, and fusion strategies.