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This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.

In the modern age of urbanisation, the mass population is becoming progressively reliant on technical infrastructures. These industrial buildings provide integral services to the general public including the delivery of energy, information and communication technologies, and maintenance of transport networks. The safety and security of these structures is crucial as new threats are continually emerging. Safety and Security Issues in Technical Infrastructures is a pivotal reference source that provides vital research on the modernisation of occupational security and safety practices within information technology-driven buildings. While highlighting topics such as explosion process safety, nanotechnology, and infrastructural risk analysis, this publication explores current risks and uncertainties and the raising of comprehensive awareness for experts in this field. This book is ideally designed for security managers, safety personnel, civil engineers, architects, researchers, construction professionals, strategists, educators, material scientists, property owners, and students.

Information modeling plays an important role in every level of the enterprise information system's architecture. Modeling allows organizations to adapt and become more efficient, helping top managers and engineers outline tactics to reach strategic objectives, understand organizational needs, and design information systems that are aligned with business goals. New Perspectives on Information Systems Modeling and Design is an essential reference source that discusses organizational adaptation through the integration of new information technologies into existing processes and underlying supporting applications. Featuring research on topics such as application integration, change management, and mobile process activities, this book is ideally designed for managers, researchers, system developers, entrepreneurs, graduate-level students, business professionals, information system engineers, and academicians seeking coverage on emerging technological developments and practical solutions for system modeling and design.

The Future of Open Data flows from a multi-year Social Sciences and Humanities Research Council (SSHRC) Partnership Grant project that set out to explore open government geospatial data from an interdisciplinary perspective. Researchers on the grant adopted a critical social science perspective grounded in the imperative that the research should be relevant to government and civil society partners in the field. This book builds on the knowledge developed during the course of the grant and asks the question, "What is the future of open data?" The contributors' insights into the future of open data combine observations from five years of research about the Canadian open data community with a critical perspective on what could and should happen as open data efforts evolve. Each of the chapters in this book addresses different issues and each is grounded in distinct disciplinary or interdisciplinary perspectives. The opening chapter reflects on the origins of open data in Canada and how it has progressed to the present date, taking into account how the Indigenous data sovereignty movement intersects with open data. A series of chapters address some of the pitfalls and opportunities of open data and consider how the changing data context may impact sources of open data, limits on open data, and even liability for open data. Another group of chapters considers new landscapes for open data, including open data in the global South, the data priorities of local governments, and the emerging context for rural open data.

The development of new and effective analytical and numerical models is essential to understanding the performance of a variety of structures. As computational methods continue to advance, so too do their applications in structural performance modeling and analysis. Modeling and Simulation Techniques in Structural Engineering presents emerging research on computational techniques and applications within the field of structural engineering. This timely publication features practical applications as well as new research insights and is ideally designed for use by engineers, IT professionals, researchers, and graduate-level students.

Blockchain technology presents numerous advantages that include increased transparency, reduced transaction costs, faster transaction settlement, automation of information, increased traceability, improved customer experience, improved digital identity, better cyber security, and user-controlled networks. These potential applications are widespread and diverse including funds transfer, smart contracts, e-voting, efficient supply chain, and more in nearly every sector of society including finance, healthcare, law, trade, real estate, and other important areas. However, there are challenges and limitations that exist such as high energy consumption, limited scalability, complexity, security, network size, lack of regulations, and other critical issues. Nevertheless, blockchain is an attractive technology and has much to offer to the modern-day industry. Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector investigates blockchain technology's adoption and effectiveness in multiple industries and for the internet of things (IoT)-based applications, presents use cases from industrial and financial sectors as well as from other transaction-based services, and fills a gap in this respect by extending the existing body of knowledge in the suggested field. While highlighting topics such as cybersecurity, use cases, and models for blockchain implementation, this book is ideal for business managers, financial accountants, practitioners, researchers, academicians, and students interested in blockchain technology's role and implementation in IoT and the financial sector.

This book uses machine-learning to identify the causes of conflict from among the top predictors of conflict. This methodology elevates some complex causal pathways that cause civil conflict over others, thus teasing out the complex interrelationships between the most important variables that cause civil conflict. Success in this realm will lead to scientific theories of conflict that will be useful in preventing and ending civil conflict. After setting out a current review of the literature and a case for using machine learning to analyze and predict civil conflict, the authors lay out the data set, important variables, and investigative strategy of their methodology. The authors then investigate institutional causes, economic causes, and sociological causes for civil conflict, and how that feeds into their model. The methodology provides an identifiable pathway for specifying causal models. This book will be of interest to scholars in the areas of economics, political science, sociology, and artificial intelligence who want to learn more about leveraging machine learning technologies to solve problems and who are invested in preventing civil conflict.

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. Renown complexity thinkers and practitioners as well as those who are new to the area of complexity will find interest in this book.

The communication field is evolving rapidly in order to keep up with society's demands. As such, it becomes imperative to research and report recent advancements in computational intelligence as it applies to communication networks. The Handbook of Research on Recent Developments in Intelligent Communication Application is a pivotal reference source for the latest developments on emerging data communication applications. Featuring extensive coverage across a range of relevant perspectives and topics, such as satellite communication, cognitive radio networks, and wireless sensor networks, this book is ideally designed for engineers, professionals, practitioners, upper-level students, and academics seeking current information on emerging communication networking trends.

This book summarizes recent inventions, provides guidelines and recommendations, and demonstrates many practical applications of homomorphic encryption. This collection of papers represents the combined wisdom of the community of leading experts on Homomorphic Encryption. In the past 3 years, a global community consisting of researchers in academia, industry, and government, has been working closely to standardize homomorphic encryption. This is the first publication of whitepapers created by these experts that comprehensively describes the scientific inventions, presents a concrete security analysis, and broadly discusses applicable use scenarios and markets. This book also features a collection of privacy-preserving machine learning applications powered by homomorphic encryption designed by groups of top graduate students worldwide at the Private AI Bootcamp hosted by Microsoft Research. The volume aims to connect non-expert readers with this important new cryptographic technology in an accessible and actionable way. Readers who have heard good things about homomorphic encryption but are not familiar with the details will find this book full of inspiration. Readers who have preconceived biases based on out-of-date knowledge will see the recent progress made by industrial and academic pioneers on optimizing and standardizing this technology. A clear picture of how homomorphic encryption works, how to use it to solve real-world problems, and how to efficiently strengthen privacy protection, will naturally become clear.

As the confluence of networks that is the modern Internet grows to encompass everything from nuclear reactors to home appliances, the affordances offered to the average citizen grow as well-but so, too, do the resources made available to those with malicious intent. Through the rise of Big Data and the Internet of Things, terrorist organizations today have been freed from geographic and logistical confines and now have more power than ever before to strike the average citizen directly at home. This, coupled with the inherently asymmetrical nature of cyberwarfare-which grants great advantage to the attacker-has created an unprecedented national security risk that both governments and their citizens are woefully ill-prepared to face. The Handbook of Research on Civil Society and National Security in the Era of Cyber Warfare addresses the problem of cyber terrorism head-on, first through a review of current literature, and then through a series of progressive proposals aimed at researchers, professionals, and policymakers. Touching on such subjects as cyber-profiling, hacktivism, and digital counterterrorism, this collection offers the tools to begin formulating a ground-up resiliency to cybersecurity threats that starts at the civilian level.

An approach to socio-technical HCI called Human Work Interaction Design (HWID) emerged around 2005. It has grown steadily, and now is the time for sharing this research with a wider audience. In this book, the HWID approach is used to discuss socio-technical HCI theory, cases, methods, and impact. The book introduces HWID as a multi-sided platform for theorizing about socio-technical HCI work design in the digital age. It presents design cases that illustrate the design of socio-technical relations, provides specific advice for researchers, consultants, and policy makers, and reflects on the open issues related to theorizing about sociotechnical HCI. The benefits of HWID include that it meets the requirement of taking both the social and the technical into account, while focusing strongly on the relationship between the social and the technical. In addition, it is truly international and explicitly considers local cultural, organizational, and technological contexts.

The fast and easy way to get things done with Office Perplexed by PowerPoint? Looking to excel at Excel? From Access to Word and every application in between this all-encompassing guide provides plain-English guidance on mastering the entire Microsoft Office suite. Through easy-to-follow instruction, you'll quickly get up and running with Excel, Word, PowerPoint, Outlook, Access, Publisher, Charts and Graphics, OneNote, and more and make your work and home life easier, more productive, and more streamlined. Microsoft Office is the leading productivity tool in the world. From word processing to business communication to data crunching, it requires a lot of knowledge to operate it let alone master it. Luckily, Office 2016 All-in-One For Dummies is here to deliver the breadth of information you need to complete basic tasks and drill down into Office's advanced features. * Create customized documents and add graphic elements, proofing, and citations in Word * Build a worksheet, create formulas, and perform basic data analysis in Excel * Create a notebook and organize your thoughts in Notes * Manage messages, tasks, contacts, and calendars in Outlook Clocking in at over 800 pages, Office 2016 All-in-One For Dummies will be the singular Microsoft Office resource you'll turn to again and again.

Across numerous industries in modern society, there is a constant need to gather precise and relevant data efficiently and quickly. As such, it is imperative to research new methods and approaches to increase productivity in these areas. Next-Generation Information Retrieval and Knowledge Resources Management is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as knowledge discovery, spatial indexing, and data mining, this book is ideally designed for researchers, graduate students, academics, and industry professionals seeking ways to optimize knowledge management processes.

An intellectual property discussion is central to qualitative research projects, and ethical guidelines are essential to the safe accomplishment of research projects. Undertaking research studies without adhering to ethics may be dangerous to researchers and research subjects. Therefore, it is important to understand and develop practical techniques for handling ethics with a specific focus on qualitative projects so that researchers conducting this type of research may continue to use ethical practices at every step of the project. Data Analysis and Methods of Qualitative Research: Emerging Research and Opportunities discusses in detail the methods related to the social constructionist paradigm that is popular with qualitative research projects. These methods help researchers undertake ideal qualitative projects that are free from quantitative research techniques/concepts all while acquiring practical skills in handling ethics and ethical issues in qualitative projects. The chapters each contain case studies, learning outcomes, question and answer sections, and discuss critical research philosophies in detail along with topics such as ethics, research design, data gathering and sampling methods, research outputs, data analysis, and report writing. Featuring a wide range of topics such as epistemology, probability sampling, and big data, this book is ideal for researchers, practitioners, computer scientists, academicians, analysts, coders, and students looking to become competent qualitative research specialists.