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Data and Applications Security and Privacy XXXIII: 33rd Annual IFIP WG 11.3 Conference, DBSec 2019, Charleston, SC, USA, July 15–17, 2019, Proceedings (Lecture Notes in Computer Science #11559)
by Simon N. FoleyThis 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.
Data and Applications Security and Privacy XXXVI: 36th Annual IFIP WG 11.3 Conference, DBSec 2022, Newark, NJ, USA, July 18–20, 2022, Proceedings (Lecture Notes in Computer Science #13383)
by Shamik Sural Haibing LuThis book constitutes the refereed proceedings of the 36th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2022, held in Newark, NJ, USA, in July 2022.The 12 full papers and 6 short papers presented were carefully reviewed and selected from 33 submissions. The conference covers research in data and applications security and privacy.
Data and Applications Security and Privacy XXXVII: 37th Annual IFIP WG 11.3 Conference, DBSec 2023, Sophia-Antipolis, France, July 19–21, 2023, Proceedings (Lecture Notes in Computer Science #13942)
by Vijayalakshmi Atluri Anna Lisa FerraraThis volume LNCS 13942 constitutes the refereed proceedings of the 37th Annual IFIP WG 11.3 Conference, DBSec 2023, in Sophia-Antipolis, France, July 19–21, 2023. The 19 full papers presented together with 5 short papers were carefully reviewed and selected from 56 submissions. The conference focuses on secure data sharing; access control and vulnerability assessment; machine learning; and mobile applications.
Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World
by Bruce SchneierYou are under surveillance right now.<P><P> Your cell phone provider tracks your location and knows who’s with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it.<P> The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches.<P> Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He shows us exactly what we can do to reform our government surveillance programs and shake up surveillance-based business models, while also providing tips for you to protect your privacy every day. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.
Data and Society: A Critical Introduction
by Anne Beaulieu Sabina LeonelliData and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.
Data and Society: A Critical Introduction
by Anne Beaulieu Sabina LeonelliData and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.
Data and the City (Regions and Cities)
by Rob Kitchin Tracey P. Lauriault Gavin McArdleThere is a long history of governments, businesses, science and citizens producing and utilizing data in order to monitor, regulate, profit from and make sense of the urban world. Recently, we have entered the age of big data, and now many aspects of everyday urban life are being captured as data and city management is mediated through data-driven technologies. Data and the City is the first edited collection to provide an interdisciplinary analysis of how this new era of urban big data is reshaping how we come to know and govern cities, and the implications of such a transformation. This book looks at the creation of real-time cities and data-driven urbanism and considers the relationships at play. By taking a philosophical, political, practical and technical approach to urban data, the authors analyse the ways in which data is produced and framed within socio-technical systems. They then examine the constellation of existing and emerging urban data technologies. The volume concludes by considering the social and political ramifications of data-driven urbanism, questioning whom it serves and for what ends. This book, the companion volume to 2016’s Code and the City, offers the first critical reflection on the relationship between data, data practices and the city, and how we come to know and understand cities through data. It will be crucial reading for those who wish to understand and conceptualize urban big data, data-driven urbanism and the development of smart cities.
Data for All
by John K. ThompsonDo you know what happens to your personal data when you are browsing, buying, or using apps? Discover how your data is harvested and exploited, and what you can do to access, delete, and monetize it.Data for All empowers everyone—from tech experts to the general public—to control how third parties use personal data. Read this eye-opening book to learn: The types of data you generate with every action, every day Where your data is stored, who controls it, and how much money they make from it How you can manage access and monetization of your own data Restricting data access to only companies and organizations you want to support The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit The data you generate every day is the lifeblood of many large companies—and they make billions of dollars using it. In Data for All, bestselling author John K. Thompson outlines how this one-sided data economy is about to undergo a dramatic change. Thompson pulls back the curtain to reveal the true nature of data ownership, and how you can turn your data from a revenue stream for companies into a financial asset for your benefit. Foreword by Thomas H. Davenport. About the Technology Do you know what happens to your personal data when you&’re browsing and buying? New global laws are turning the tide on companies who make billions from your clicks, searches, and likes. This eye-opening book provides an inspiring vision of how you can take back control of the data you generate every day. About the Book Data for All gives you a step-by-step plan to transform your relationship with data and start earning a &“data dividend&”—hundreds or thousands of dollars paid out simply for your online activities. You&’ll learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. What&’s Inside The types of data you generate with every action, every day How you can manage access and monetization of your own data The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit About the Reader For anyone who is curious or concerned about how their data is used. No technical knowledge required. About the Author John K. Thompson is an international technology executive with over 37 years of experience in the fields of data, advanced analytics, and artificial intelligence. Table of Contents 1 A history of data 2 How data works today 3 You and your data 4 Trust 5 Privacy 6 Moving from Open Data to Our Data 7 Derived data, synthetic data, and analytics 8 Looking forward: What&’s next for our data?
Data for Social Good: Non-Profit Sector Data Projects
by Jane Farmer Anthony McCosker Kath Albury Amir AryaniThis open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations’ datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity.
Data for the Public Good: How Data Can Help Citizens and Government
by Alex HowardAs we move into an era of unprecedented volumes of data and computing power, the benefits aren't for business alone. Data can help citizens access government, hold it accountable and build new services to help themselves. Simply making data available is not sufficient. The use of data for the public good is being driven by a distributed community of media, nonprofits, academics and civic advocates.This report from O'Reilly Radar highlights the principles of data in the public good, and surveys areas where data is already being used to great effect, covering: Consumer financeTransit dataGovernment transparencyData journalismAid and developmentCrisis and emergency responseHealthcare
Data in Society: Challenging Statistics in an Age of Globalisation
by Jeff Evans, Sally Ruane and Humphrey SouthallStatistical data and evidence-based claims are increasingly central to our everyday lives. Critically examining ‘Big Data’, this book charts the recent explosion in sources of data, including those precipitated by global developments and technological change. It sets out changes and controversies related to data harvesting and construction, dissemination and data analytics by a range of private, governmental and social organisations in multiple settings. Analysing the power of data to shape political debate, the presentation of ideas to us by the media, and issues surrounding data ownership and access, the authors suggest how data can be used to uncover injustices and to advance social progress.
Data, Methods and Theory in the Organizational Sciences: A New Synthesis (SIOP Organizational Frontiers Series)
by Kevin R. MurphyData, Methods and Theory in the Organizational Sciences explores the long-term evolution and changing relationships between data, methods, and theory in the organizational sciences. In the last 50 years, theory has come to dominate research and scholarship in these fields, yet the emergence of big data, as well as the increasing use of archival data sets and meta-analytic methods to test empirical hypotheses, has upset this order. This volume examines the evolving relationship between data, methods, and theory and suggests new ways of thinking about the role of each in the development and presentation of research in organizations. This volume utilizes the latest thinking from experts in a wide range of fields on the topics of data, methods, and theory and uses this knowledge to explore the ways in which behavior in organizations has been studied. This volume also argues that the current focus on theory is both unhealthy for the field and unsustainable, and it provides more successful ways theory can be used to support and structure research, and demonstrates the most effective techniques for analyzing and making sense of data. This is an essential resource for researchers, professionals, and educators who are looking to rethink their current approaches to research, and who are interested in creating more useful and more interpretable research in the organizational sciences.
Data-Based Child Advocacy: Using Statistical Indicators to Improve the Lives of Children (SpringerBriefs in Well-Being and Quality of Life Research #0)
by William P. O'HareThis book locates, organizes and summarizes information about the use of child indicators in an advocacy context. It provides a conceptual framework that allows readers to see a wide variety of work as part of a unified field. It provides a description of key concepts and illustrates these concepts by offering many examples from a range of countries and a wide variety of applications. It covers work from governments, non-governmental organization and academics. It describes such aspects as the use of data to educate and increase public awareness, as well as to monitor, set goals and evaluate programs serving children. A growing number of organizations and people are focusing on measuring and monitoring the well-being of children and these child well-being data are often employed in ways that go beyond what is typically considered scholarship. Many of these applications involve some type of advocacy activity. Yet, there is very little in the literature about the use of child indicators in an advocacy context. This book provides a framework for scholars in a variety of disciplines that will help them to structure their thinking about the use of such indicators in a public context.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Driven HR: How to Use AI, Analytics and Data to Drive Performance
by Bernard MarrHow can HR professionals utilize and leverage their organization's data effectively, with the use of AI, for more talent attraction, better employee engagement and higher talent retention to ultimately drive performance?AI is now an integral part of being data-driven. With this updated edition of Data-Driven HR, practitioners can unlock business potential and success through data and analytics. Covering topics such as recruitment, employee engagement, performance management, wellbeing and training, HR practitioners can benefit from knowing how to really be data-driven through the use of data and AI. HR teams will learn how to identify business goals, scrutinize useful sources of data and gain rich and diverse insights from their vast amounts of data. This book brings guidance on how to manage challenges that come with data and AI, as well as how to responsibly and transparently use data to improve decision making. It also includes predictive analytics and how to place warning systems into databases for any potential workforce issues. Packed with practical advice, key takeaways and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.
Data-Driven HR: How to Use Analytics and Metrics to Drive Performance
by Bernard MarrTraditionally seen as a purely people function unconcerned with numbers, HR is now uniquely placed to use company data to drive performance, both of the people in the organization and the organization as a whole. Data-Driven HR is a practical guide which enables HR professionals to leverage the value of the vast amount of data available at their fingertips. Covering how to identify the most useful sources of data, collect information in a transparent way that is in line with data protection requirements and turn this data into tangible insights, this book marks a turning point for the HR profession. Covering all the key elements of HR including recruitment, employee engagement, performance management, wellbeing and training, Data-Driven HR examines the ways data can contribute to organizational success by, among other things, optimizing processes, driving performance and improving HR decision making. Packed with case studies and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.
Data-Driven Organization Design: Delivering Perpetual Performance Gains Through the Organizational System
by Rupert MorrisonUnderstand how to drive business performance with your organizational data and analytics in the second edition of Data-Driven Organization Design.Using data and analytics is a key opportunity for businesses to transform performance and achieve success. With a data-driven approach, all the elements of the organizational system can be connected to design an environment in which people can excel and attain competitive advantage. Data-Driven Organization Design provides a practical framework for HR and organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the most relevant questions of it to help complex, fluid organizations constantly evolve and meet moving objectives. This updated second edition contains new material on organizational planning and analysis, role design and job architecture, position management lifecycle and delta reporting. Alongside this, new case studies and examples will show how these approaches have been applied in practice. Whether planning a long-term transformation, a large redesign or an individual small project, Data-Driven Organization Design will demonstrate how to make the most of your organizational data and analytics to drive business performance.
Data-Driven Personalization: How to Use Consumer Insights to Generate Customer Loyalty
by Zontee HouMake your marketing truly resonate by personalizing every message, powered by data, research and behavioral economics. To break through the noise, marketers today need to be hyper-relevant to their customers. To do that takes data and a deep understanding of your audience. Data-Driven Personalization breaks down the best ways to reach new customers and better engage your best customers. By combining principles of persuasion, behavioral economics and industry research, this book provides readers with an actionable blueprint for how to implement a customer-centric approach to marketing that will drive results. The book is broken into six parts that detail everything from what data is most valuable for personalization to how to build a data-driven marketing team that's prepared for the next five years and beyond. Each chapter includes actionable insights to guide marketers as they implement a data-driven personalization approach to their strategy. The chapters also focus on hands-on tactics like identifying messages that will move the needle with customers, how to generate seamless omnichannel experiences and how to balance personalization with data privacy. The book features case studies from top brands, including FreshDirect, Target, Adobe, Cisco and Spotify.
Data-Driven Policy Impact Evaluation: How Access to Microdata is Transforming Policy Design
by Nuno Crato Paolo ParuoloIn the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.
Data-Driven Storytelling (AK Peters Visualization Series)
by Nathalie Henry Riche Christophe Hurter Nicholas Diakopoulos Sheelagh CarpendaleThis book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.
Data-centric Living: Algorithms, Digitization and Regulation
by Sridhar V.This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.
Data-driven Modelling of Structured Populations: A Practical Guide to the Integral Projection Model (Lecture Notes on Mathematical Modelling in the Life Sciences)
by Mark Rees Stephen P. Ellner Dylan Z. ChildsThis book is a "How To" guide formodeling population dynamics using Integral Projection Models (IPM) startingfrom observational data. It is written by a leading research team in this areaand includes code in the R language (in the text and online) to carry out allcomputations. The intended audience are ecologists, evolutionary biologists,and mathematical biologists interested in developing data-driven models foranimal and plant populations. IPMs may seem hard as they involve integrals. Theaim of this book is to demystify IPMs, so they become the model of choice forpopulations structured by size or other continuously varying traits. The bookuses real examples of increasing complexity to show how the life-cycle of thestudy organism naturally leads to the appropriate statistical analysis, whichleads directly to the IPM itself. A wide range of model types and analyses arepresented, including model construction, computational methods, and theunderlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculationswithin the text is available to readers on GitHub. Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK.
Data-driven Organization Design
by Rupert MorrisonData is changing the nature of competition. Making sense of it is tough. Taking advantage of it is tougher. There is a business opportunity for organizations to use data and analytics to transform business performance. Organizations are by their nature complex. They are a constantly evolving system made up of objectives, processes designed to meet those objectives, people with skills and behaviours to do the work required, and all of this organised in a governance structure. It is dynamic, fluid and constantly moving over time. Using data and analytics you can connect all the elements of the system to design an environment for people to perform; an organization which has the right people, in the right place, doing the right things, at the right time. Only when everyone performs to their potential, do organizations have a hope of getting and sustaining a competitive edge. Data-driven Organization Design provides a practical framework for HR and Organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the right questions of it. Whether looking to implement a long term transformation, large redesign, or a one-off small scale project, this book will show you how to make the most of your organizational data and analytics to drive business performance.
Database Computing for Scholarly Research: Case Studies Using the Online Cultural and Historical Research Environment (Quantitative Methods in the Humanities and Social Sciences)
by Sandra R. Schloen Miller C. ProsserThis book discusses in detail a series of examples drawn from scholarly projects that use the OCHRE database platform (Online Cultural and Historical Research Environment). These case studies illustrate the wide range of data that can be managed with this platform and the wide variety of problems solved by OCHRE’s item-based graph data model. The unique features and design principles of the OCHRE platform are explained and justified, helping readers to imagine how the system could be used for their own data.Data generated by studies in the humanities and social sciences is often semi-structured, fragmented, highly variable, and subject to many interpretations, making it difficult to represent adequately in a conventional database. The authors examine commonly used methods of data management in the humanities and offer a compelling argument for a different approach that takes advantage of powerful computational techniques for organizing scholarly information.This book is a challenge to scholars in the humanities and social sciences, asking them to expect more from technology as they pursue their research goals. Written jointly by a software engineer and a research scholar, each with many years of experience in applying database methods to diverse kinds of scholarly data, it shows how scholars can make the most of their existing data while going beyond the limitations of commonly used software tools to represent their objects of study in a more accurate, nuanced, and flexible way.
Database Nation: The Death of Privacy in the 21st Century
by Simson GarfinkelFifty years ago, in 1984, George Orwell imagined a future in which privacy was demolished by a totalitarian state that used spies, video surveillance, historical revisionism, and control over the media to maintain its power. Those who worry about personal privacy and identity--especially in this day of technologies that encroach upon these rights--still use Orwell's "Big Brother" language to discuss privacy issues. But the reality is that the age of a monolithic Big Brother is over. And yet the threats are perhaps even more likely to destroy the rights we've assumed were ours.Database Nation: The Death of Privacy in the 21st Century shows how, in these early years of the 21st century, advances in technology endanger our privacy in ways never before imagined. Direct marketers and retailers track our every purchase; surveillance cameras observe our movements; mobile phones will soon report our location to those who want to track us; government eavesdroppers listen in on private communications; misused medical records turn our bodies and our histories against us; and linked databases assemble detailed consumer profiles used to predict and influence our behavior. Privacy--the most basic of our civil rights--is in grave peril.Simson Garfinkel--journalist, entrepreneur, and international authority on computer security--has devoted his career to testing new technologies and warning about their implications. This newly revised update of the popular hardcover edition of Database Nation is his compelling account of how invasive technologies will affect our lives in the coming years. It's a timely, far-reaching, entertaining, and thought-provoking look at the serious threats to privacy facing us today. The book poses a disturbing question: how can we protect our basic rights to privacy, identity, and autonomy when technology is making invasion and control easier than ever before?Garfinkel's captivating blend of journalism, storytelling, and futurism is a call to arms. It will frighten, entertain, and ultimately convince us that we must take action now to protect our privacy and identity before it's too late.