VoIP (voice over IP) networks are currently being deployed by enterprises, governments, and service providers around the globe and are used by millions of individuals each day. Today, the hottest topic with engineers in the field is how to secure these networks. "Understanding Voice over IP Security" offers this critical knowledge. The book teaches practitioners how to design a highly secure VoIP network, explains Internet security basics, such as attack types and methods, and details all the key security aspects of a VoIP system, including identity, authentication, signaling, and media encryption. What's more, the book presents techniques used to combat spam and covers the future problems of spim (spam over instant messaging) and spim (spam over internet telephony).

This book introduces the reader to the optical switching technology for its application to data centers. In addition, it takes a picture of the status of the technology and system architecture evolution and of the research in the area of optical switching in data center. The book is organized in four parts: the first part is focused on the system aspects of optical switching in intra-data center networking, the second part is dedicated to describing the recently demonstrated optical switching networks, the third part deals with the latest technologies developed to enable optical switching and, finally, the fourth part of the book outlines the future prospects and trends.

Convergence proposes the enhancement of the Internet with a novel, content-centric, publish-subscribe service model based on the versatile digital item (VDI): a common container for all kinds of digital content, including digital representations of real-world resources. VDIs will serve the needs of the future Internet, providing a homogeneous method for handling structured information, incorporating security and privacy mechanisms. CONVERGENCE subsumes the following areas of research: * definition of the VDI as a new fundamental unit of distribution and transaction; * content-centric networking functionality to complement or replace IP-address-based routing; * security and privacy protection mechanisms; * open-source middleware, including a community dictionary service to enable rich semantic searches; * applications, tested under real-life conditions. This book shows how CONVERGENCE allows publishing, searching and subscribing to any content. Creators can publish their content by wrapping it and its descriptions into a VDI, setting rights for other users to access this content, monitor its use, and communicate with people using it; they may even update or revoke content previously published. Access to content is more efficient, as search engines exploit VDI metadata for indexing, and the network uses the content name to ensure users always access the copy closest to them. Every node in the network is a content cache; handover is easy; multicast is natural; peer-to-peer is built-in; time/space-decoupling is possible. Application developers can exploit CONVERGENCE's middleware and network without having to resort to proprietary/ad hoc solutions for common/supporting functionality. Operators can use the network more efficiently, better controlling information transfer and related revenues flows. Network design, operation and management are simplified by integrating diverse functions and avoiding patches and stopgap solutions. Whether as a text for graduate students working on the future of the Internet, or a resource for practitioners providing e-commerce or multimedia services, or scientists defining new technologies, CONVERGENCE will make a valuable contribution to the future shape of the Internet.

Implement a vendor-neutral and multi-cloud cybersecurity and risk mitigation framework with advice from seasoned threat hunting pros In Threat Hunting in the Cloud: Defending AWS, Azure and Other Cloud Platforms Against Cyberattacks, celebrated cybersecurity professionals and authors Chris Peiris, Binil Pillai, and Abbas Kudrati leverage their decades of experience building large scale cyber fusion centers to deliver the ideal threat hunting resource for both business and technical audiences. You'll find insightful analyses of cloud platform security tools and, using the industry leading MITRE ATT&CK framework, discussions of the most common threat vectors. You'll discover how to build a side-by-side cybersecurity fusion center on both Microsoft Azure and Amazon Web Services and deliver a multi-cloud strategy for enterprise customers. And you will find out how to create a vendor-neutral environment with rapid disaster recovery capability for maximum risk mitigation. With this book you'll learn: Key business and technical drivers of cybersecurity threat hunting frameworks in today's technological environment Metrics available to assess threat hunting effectiveness regardless of an organization's size How threat hunting works with vendor-specific single cloud security offerings and on multi-cloud implementations A detailed analysis of key threat vectors such as email phishing, ransomware and nation state attacks Comprehensive AWS and Azure "how to" solutions through the lens of MITRE Threat Hunting Framework Tactics, Techniques and Procedures (TTPs) Azure and AWS risk mitigation strategies to combat key TTPs such as privilege escalation, credential theft, lateral movement, defend against command & control systems, and prevent data exfiltration Tools available on both the Azure and AWS cloud platforms which provide automated responses to attacks, and orchestrate preventative measures and recovery strategies Many critical components for successful adoption of multi-cloud threat hunting framework such as Threat Hunting Maturity Model, Zero Trust Computing, Human Elements of Threat Hunting, Integration of Threat Hunting with Security Operation Centers (SOCs) and Cyber Fusion Centers The Future of Threat Hunting with the advances in Artificial Intelligence, Machine Learning, Quantum Computing and the proliferation of IoT devices. Perfect for technical executives (i.e., CTO, CISO), technical managers, architects, system admins and consultants with hands-on responsibility for cloud platforms, Threat Hunting in the Cloud is also an indispensable guide for business executives (i.e., CFO, COO CEO, board members) and managers who need to understand their organization's cybersecurity risk framework and mitigation strategy.

This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.

As the amount of accumulated data across a variety of fields becomes harder to maintain, it is essential for a new generation of computational theories and tools to assist humans in extracting knowledge from this rapidly growing digital data. Global Trends in Intelligent Computing Research and Development brings together recent advances and in depth knowledge in the fields of knowledge representation and computational intelligence. Highlighting the theoretical advances and their applications to real life problems, this book is an essential tool for researchers, lecturers, professors, students, and developers who have seek insight into knowledge representation and real life applications.

R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs and practice datasets are available for download. The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. This new edition has updated programming, an expanded index, and even more statistical methods covered in over 25 new sections.

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis.
Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.
Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance.
Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.

Recent achievements in hardware and software development, such as multi-core CPUs and DRAM capacities of multiple terabytes per server, enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of enterprise data. Professor Hasso Plattner and his research group at the Hasso Plattner Institute in Potsdam, Germany, have been investigating and teaching the corresponding concepts and their adoption in the software industry for years. This book is based on an online course that was first launched in autumn 2012 with more than 13,000 enrolled students and marked the successful starting point of the openHPI e-learning platform. The course is mainly designed for students of computer science, software engineering, and IT related subjects, but addresses business experts, software developers, technology experts, and IT analysts alike. Plattner and his group focus on exploring the inner mechanics of a column-oriented dictionary-encoded in-memory database. Covered topics include - amongst others - physical data storage and access, basic database operators, compression mechanisms, and parallel join algorithms. Beyond that, implications for future enterprise applications and their development are discussed. Step by step, readers will understand the radical differences and advantages of the new technology over traditional row-oriented, disk-based databases. In this completely revised 2nd edition, we incorporate the feedback of thousands of course participants on openHPI and take into account latest advancements in hard- and software. Improved figures, explanations, and examples further ease the understanding of the concepts presented. We introduce advanced data management techniques such as transparent aggregate caches and provide new showcases that demonstrate the potential of in-memory databases for two diverse industries: retail and life sciences.

Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.

Research findings and dissemination are making healthcare more effective. Electronic health records systems and advanced tools are making care delivery more efficient. Legislative reforms are striving to make care more affordable. Efforts still need to be focused on making healthcare more accessible. Clinical Videoconferencing in Telehealth takes a comprehensive and vital step forward in providing mental health and primary care services for those who cannot make traditional office visits, live in remote areas, have transportation or mobility issues or have competing demands. Practical, evidence-based information is presented in a step by step format at two levels: for administrators, including information regarding selecting the right videoconferencing technology, navigating regulatory issues, policy temples, boilerplate language for entering into care agreements with other entities and practical solutions to multisite programming; and for clinicians, including protocols for safe, therapeutically sound practice, informed consent and tips for overcoming common technical barriers to communication in clinical videoconferencing contexts. Checklists, tables, templates, links, vignettes and other tools help to equip professional readers for providing safe services that are streamlined and relevant while avoiding guesswork, false starts and waste. The book takes a friendly-mentor approach to communication in areas such as: Logistics for administrators: Clinical videoconferencing infrastructures and technologies Policy development, procedures and tools for responsible and compliant programming Navigating issues related to providing services in multiple locations Protocols for clinicians: The informed consent process in clinical videoconferencing Clinical assessment and safety planning for remote services Minimizing communication disruption and optimizing the therapeutic alliance Clinical Videoconferencing in Telehealth aptly demonstrates the promise and potential of this technology for clinicians, clinic managers, administrators and others affiliated with mental health clinical practices. It is designed to be the comprehensive "one-stop" tool for clinical videoconferencing service development for programs and individual clinicians.

This book provides a thorough overview of cutting-edge research on electronics applications relevant to industry, the environment, and society at large. It covers a broad spectrum of application domains, from automotive to space and from health to security, while devoting special attention to the use of embedded devices and sensors for imaging, communication and control. The book is based on the 2020 ApplePies Conference, held online in November 2020, which brought together researchers and stakeholders to consider the most significant current trends in the field of applied electronics and to debate visions for the future. Areas addressed by the conference included information communication technology; biotechnology and biomedical imaging; space; secure, clean and efficient energy; the environment; and smart, green and integrated transport. As electronics technology continues to develop apace, constantly meeting previously unthinkable targets, further attention needs to be directed toward the electronics applications and the development of systems that facilitate human activities. This book, written by industrial and academic professionals, represents a valuable contribution in this endeavor.

This book provides the fundamental knowledge of the classical matching theory problems. It builds up the bridge between the matching theory and the 5G wireless communication resource allocation problems. The potentials and challenges of implementing the semi-distributive matching theory framework into the wireless resource allocations are analyzed both theoretically and through implementation examples. Academics, researchers, engineers, and so on, who are interested in efficient distributive wireless resource allocation solutions, will find this book to be an exceptional resource.

This book presents the current state of the art in the field of e-publishing and social media, particularly in the Arabic context. The book discusses trends and challenges in the field of e-publishing, along with their implications for academic publishing, information services, e-learning and other areas where electronic publishing is essential. In particular, it addresses (1) Applications of Social Media in Libraries and Information Centers, (2) Use of Social Media and E-publishing in E-learning (3) Information Retrieval in Social Media, and (4) Information Security in Social Media.

This book addresses the issue of smart and sustainable development in the Mediterranean (MED) region, a distinct part of the world, full of challenges and risks but also opportunities. Above all, the book focuses on smartening up small and medium-sized cities and insular communities, taking into account their geographical peculiarities, the pattern of MED urban settlements and the abundance of island complexes in the MED Basin. Taking for granted that sustainability in the MED is the overarching policy goal that needs to be served, the book explores different aspects of smartness in support of this goal's achievement. In this respect, evidence from concrete smart developments adopted by forerunners in the MED region is collected and analyzed; coupled with experiences gathered from successful, non-MED, examples of smart efforts in European countries. More specifically, current research and empirical results from MED urban environments are discussed, as well as findings from or concerning other parts of the world, which are of relevance to the MED region. The book's primary goal is to enable policymakers, planners and decision-making bodies to recognize the challenges and options available; and make to more informed policy decisions towards smart, sustainable, inclusive and resilient urban and regional futures in the MED.

This book describes trends in email scams and offers tools and techniques to identify such trends. It also describes automated countermeasures based on an understanding of the type of persuasive methods used by scammers. It reviews both consumer-facing scams and enterprise scams, describing in-depth case studies relating to Craigslist scams and Business Email Compromise Scams. This book provides a good starting point for practitioners, decision makers and researchers in that it includes alternatives and complementary tools to the currently deployed email security tools, with a focus on understanding the metrics of scams. Both professionals working in security and advanced-level students interested in privacy or applications of computer science will find this book a useful reference.

This book is the very first book-length study devoted to the advances in technological development and systems research in cooperative economics. The chapters provide, first of all, a coherent framework for understanding and applying the concepts and approaches of complexity and systems science for the advanced study of cooperative networks and particular cooperative enterprises and communities. Second, the book serves as a unique source of reliable information on the frontier information technologies available for the production, consumer, credit, and agricultural cooperative enterprises, discussing predominant strategies, potential drivers of change, and responses to complex problems. Given the diverse range of backgrounds and advanced research results, researchers, decision-makers, and stakeholders from all fields of cooperative economics in any country of the world will undoubtedly benefit from this book.

Strives to be the point of reference for the most important issues in the field of multidimensional databases. This book provides a brief history of the field and distinguishes between what is new in recent research and what is merely a renaming of old concepts. The book reviews past papers and discusses current research projects in the hope to encourage the search for new solutions to the many problems that are still unsolved. In addition this outlines the incredible advances in technology and ever increasing demands from users in the most diverse applicative areas such as finance, medicine, statistics, business, and many more. Many of the most distinguished and well-known researchers have contributed to this book writing about their own specific field.

The papers in this volume comprise the refereed proceedings of the conference Arti- cial Intelligence in Theory and Practice (IFIP AI 2010), which formed part of the 21st World Computer Congress of IFIP, the International Federation for Information Pr- essing (WCC-2010), in Brisbane, Australia in September 2010. The conference was organized by the IFIP Technical Committee on Artificial Int- ligence (Technical Committee 12) and its Working Group 12.5 (Artificial Intelligence Applications). All papers were reviewed by at least two members of our Program Committee. - nal decisions were made by the Executive Program Committee, which comprised John Debenham (University of Technology, Sydney, Australia), Ilias Maglogiannis (University of Central Greece, Lamia, Greece), Eunika Mercier-Laurent (KIM, France) and myself. The best papers were selected for the conference, either as long papers (maximum 10 pages) or as short papers (maximum 5 pages) and are included in this volume. The international nature of IFIP is amply reflected in the large number of countries represented here. I should like to thank the Conference Chair, Tharam Dillon, for all his efforts and the members of our Program Committee for reviewing papers under a very tight de- line.