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Handbook of Sharing Confidential Data
Statistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure compu...
Information and Communications Security
This book constitutes the refereed proceedings of the 8th International Conference on Information and Communications Security, ICICS 2006, held in Raleigh, NC, USA, December 2006. The 22 revised full papers and 17 revised short papers cover security protocols, applied cryptography, access control, privacy and malicious code, network security, systems security, cryptanalysis, applied cryptography and network security, and security implementations.
Data Science in Context
Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.
New Trends in Software Methodologies, Tools and Techniques
Software is the essential enabler for the new economy and science. It creates new markets and new directions for a more reliable, flexible, and robust society. It empowers the exploration of our world in ever more depth. However, software often falls short behind our expectations. Current software methodologies, tools and techniques remain expensive and not yet reliable for a highly changeable and evolutionary market. Many approaches have been proven only as case-by-case oriented methods. This book presents a number of new trends and theories in the direction in which we believe software science and engineering may develop to transform the role of software and science in tomorrow's information society. This publication is an attempt to capture the essence of a new state-of-art in software science and its supporting technology. It also aims at identifying the challenges such a technology has to master.
Data-Intensive Text Processing with MapReduce
Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handl...
Research and Advanced Technology for Digital Libraries
ECDL2000, the Fourth European Conference on Research and Advanced Te- nology for Digital Libraries, is being held this year in Lisbon, Portugal, following previous events in Pisa (1997), Heraklion (1998), and Paris (1999). One major goal of the ECDL conference series has been to draw information professionals, stakeholders, and user communities from both the research world and from - dustry into a discussion of the alternative technologies, policies, and scenarios for global digital libraries. The success of previous conferences makes them a hard act to follow. The eld of digital libraries draws on a truly diverse set of scienti c and technical disciplines. In the past three years, moreover,...
Federated Learning
Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II featuresemerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for dri...
Anomaly Detection as a Service
Anomaly detection has been a long-standing security approach with versatile applications, ranging from securing server programs in critical environments, to detecting insider threats in enterprises, to anti-abuse detection for online social networks. Despite the seemingly diverse application domains, anomaly detection solutions share similar technical challenges, such as how to accurately recognize various normal patterns, how to reduce false alarms, how to adapt to concept drifts, and how to minimize performance impact. They also share similar detection approaches and evaluation methods, such as feature extraction, dimension reduction, and experimental evaluation. The main purpose of this b...
Mathematical Foundations of Computer Science 1999
This volume contains papers selected for presentation during the 24th Interna tional Symposium on Mathematical Foundations of Computer Science held on September 6-10, 1999 in Szklarska Por^ba, Poland. The symposium, organized alternately in the Czech Republic, Slovakia, and Poland, focuses on theoretical aspects and mathematical foundations of computer science. The scientific program of the symposium consists of five invited talks given by Martin Dyer, Dexter Kozen, Giovanni Manzini, Sergio Rajsbaum, and Mads Tofte, and 37 accepted papers chosen out of 68 submissions. The volume contains all accepted contributed papers, and three invited papers. The contributed papers have been selected for ...
Handbook of Research on Cloud Computing and Big Data Applications in IoT
Today, cloud computing, big data, and the internet of things (IoT) are becoming indubitable parts of modern information and communication systems. They cover not only information and communication technology but also all types of systems in society including within the realms of business, finance, industry, manufacturing, and management. Therefore, it is critical to remain up-to-date on the latest advancements and applications, as well as current issues and challenges. The Handbook of Research on Cloud Computing and Big Data Applications in IoT is a pivotal reference source that provides relevant theoretical frameworks and the latest empirical research findings on principles, challenges, and applications of cloud computing, big data, and IoT. While highlighting topics such as fog computing, language interaction, and scheduling algorithms, this publication is ideally designed for software developers, computer engineers, scientists, professionals, academicians, researchers, and students.
