This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

As the applications of data mining, the non-trivial extraction of implicit information in a data set, have expanded in recent years, so has the need for techniques that are tolerable to imprecision, uncertainty, and approximation. Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies is a compendium that addresses this need. It integrates contrasting techniques of conventional hard computing and soft computing to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low-cost solution. This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities, forming a foundation for the development of the field.

This book presents two practical physical attacks. It shows how attackers can reveal the secret key of symmetric as well as asymmetric cryptographic algorithms based on these attacks, and presents countermeasures on the software and the hardware level that can help to prevent them in the future. Though their theory has been known for several years now, since neither attack has yet been successfully implemented in practice, they have generally not been considered a serious threat. In short, their physical attack complexity has been overestimated and the implied security threat has been underestimated. First, the book introduces the photonic side channel, which offers not only temporal resolution, but also the highest possible spatial resolution. Due to the high cost of its initial implementation, it has not been taken seriously. The work shows both simple and differential photonic side channel analyses. Then, it presents a fault attack against pairing-based cryptography. Due to the need for at least two independent precise faults in a single pairing computation, it has not been taken seriously either. Based on these two attacks, the book demonstrates that the assessment of physical attack complexity is error-prone, and as such cryptography should not rely on it. Cryptographic technologies have to be protected against all physical attacks, whether they have already been successfully implemented or not. The development of countermeasures does not require the successful execution of an attack but can already be carried out as soon as the principle of a side channel or a fault attack is sufficiently understood.

Cisco Systems, Inc. is the worldwide leader in networking for the Internet, and its Intrusion Detection Systems line of products is making in roads in the IDS market segment, with major upgrades having happened in February of 2003. Cisco Security Professional's Guide to Secure Intrusion Detection Systems is a comprehensive, up-to-date guide to the hardware and software that comprise the Cisco IDS. Cisco Security Professional's Guide to Secure Intrusion Detection Systems does more than show network engineers how to set up and manage this line of best selling products ... it walks them step by step through all the objectives of the Cisco Secure Intrusion Detection System course (and corresponding exam) that network engineers must pass on their way to achieving sought-after CCSP certification.

This provides a comprehensive overview of the key principles of security concerns surrounding the upcoming Internet of Things (IoT), and introduces readers to the protocols adopted in the IoT. It also analyses the vulnerabilities, attacks and defense mechanisms, highlighting the security issues in the context of big data. Lastly, trust management approaches and ubiquitous learning applications are examined in detail. As such, the book sets the stage for developing and securing IoT applications both today and in the future.

As information technology continues to advance in massive increments, the bank of information available from personal, financial, and business electronic transactions and all other electronic documentation and data storage is growing at an exponential rate. With this wealth of information comes the opportunity and necessity to utilize this information to maintain competitive advantage and process information effectively in real-world situations. Data Mining and Knowledge Discovery Technologies presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data mining methods, structures, tools, and methods, the knowledge discovery process, and data marts, among many other cutting-edge topics.

This book presents an exhaustive and timely review of key research work on fuzzy XML data management, and provides readers with a comprehensive resource on the state-of-the art tools and theories in this fast growing area. Topics covered in the book include: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models, reengineering of fuzzy XML into fuzzy database models, and reasoning of fuzzy XML. The book is intended as a reference guide for researchers, practitioners and graduate students working and/or studying in the field of Web Intelligence, as well as for data and knowledge engineering professionals seeking new approaches to replace traditional methods, which may be unnecessarily complex or even unproductive.

With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as Uncertain .

This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants."

The technologies in data mining have been applied to bioinformatics research in the past few years with success, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays a essential role in understanding the emerging problems in genomics, proteomics, and systems biology. ""Advanced Data Mining Technologies in Bioinformatics"" covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. ""Advanced Data Mining Technologies in Bioinformatics"" is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic.

Data Mining techniques are gradually becoming essential components of corporate intelligence systems and progressively evolving into a pervasive technology within activities that range from the utilization of historical data to predicting the success of an awareness campaign. In reality, data mining is becoming an interdisciplinary field driven by various multi-dimensional applications. Data Mining Applications for Empowering Knowledge Societies presents an overview on the main issues of data mining, including its classification, regression, clustering, and ethical issues. This comprehensive book also provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications.

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

This book presents the latest developments regarding a detailed mobile agent-enabled anomaly detection and verification system for resource constrained sensor networks; a number of algorithms on multi-aspect anomaly detection in sensor networks; several algorithms on mobile agent transmission optimization in resource constrained sensor networks; an algorithm on mobile agent-enabled in situ verification of anomalous sensor nodes; a detailed Petri Net-based formal modeling and analysis of the proposed system, and an algorithm on fuzzy logic-based cross-layer anomaly detection and mobile agent transmission optimization. As such, it offers a comprehensive text for interested readers from academia and industry alike.

This book presents breakthroughs in the design of Wireless Energy Harvesting (WEH) networks. It bridges the gap between WEH through radio waves communications and power transfer, which have largely been designed separately. The authors present an overview of the RF-EHNs including system architecture and RF energy harvesting techniques and existing applications. They also cover the idea of WEH in novel discoveries of information, the theoretical bounds in WEH, wireless sensor networks, usage of modern channel coding together with WEH, energy efficient resource allocation mechanisms, distributed self-organized energy efficient designs, delay-energy trade-off, specific protocols for energy efficient communication designs, D2D communication and energy efficiency, cooperative wireless networks, and cognitive networks.

This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks - many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes.

The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain. ""Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection"" provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining. Covering a comprehensive range of topics, this book discusses underlying frameworks, mining techniques, interest metrics, and real-world application domains within the field.

This book presents a comprehensive introduction to Integrated Business Planning (IBP), building on practitioner's experience and showcasing the value gains when moving from disconnected planning to IBP. It also proposes a road map for the transformation of planning, including technological initiatives, business priorities and organizational processes, and demonstrates how to motivate different IBP stakeholders to work together, when and how to connect strategic (to be understood as long term SC&O), tactical and operational planning and how to leverage functional and data integration features of SAP IBP. Real-world business-process use cases help to show the practical implications of implementing SAP IBP. Furthermore the book explores new capabilities, talent acquisition and retention, career development leadership, IBP Center of Expertise. A discussion of how disruptive technology trends like big data, Internet of Things, machine learning and artificial intelligence can influence IBP now and in the near future rounds out the book.

The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory. The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.

Cyber Crime and Cyber Terrorism Investigator's Handbook is a vital tool in the arsenal of today's computer programmers, students, and investigators. As computer networks become ubiquitous throughout the world, cyber crime, cyber terrorism, and cyber war have become some of the most concerning topics in today's security landscape. News stories about Stuxnet and PRISM have brought these activities into the public eye, and serve to show just how effective, controversial, and worrying these tactics can become. Cyber Crime and Cyber Terrorism Investigator's Handbook describes and analyzes many of the motivations, tools, and tactics behind cyber attacks and the defenses against them. With this book, you will learn about the technological and logistic framework of cyber crime, as well as the social and legal backgrounds of its prosecution and investigation. Whether you are a law enforcement professional, an IT specialist, a researcher, or a student, you will find valuable insight into the world of cyber crime and cyber warfare. Edited by experts in computer security, cyber investigations, and counter-terrorism, and with contributions from computer researchers, legal experts, and law enforcement professionals, Cyber Crime and Cyber Terrorism Investigator's Handbook will serve as your best reference to the modern world of cyber crime.

The end of the 20th century witnessed an information revolution that introduced a host of new economic efficiencies. This economic change was underpinned by rapidly growing networks of infrastructure that have become increasingly complex. In this new era of global security we are now forced to ask whether our private efficiencies have led to public vulnerabilities, and if so, how do we make ourselves secure without hampering the economy. In order to answer these questions, Sean Gorman provides a framework for how vulnerabilities are identified and cost-effectively mitigated, as well as how resiliency and continuity of infrastructures can be increased. Networks, Security and Complexity goes on to address specific concerns such as determining criticality and interdependency, the most effective means of allocating scarce resources for defense, and whether diversity is a viable strategy. The author provides the economic, policy, and physics background to the issues of infrastructure security, along with tools for taking first steps in tackling these security dilemmas. He includes case studies of infrastructure failures and vulnerabilities, an analysis of threats to US infrastructure, and a review of the economics and geography of agglomeration and efficiency. This critical and controversial book will garner much attention and spark an important dialogue. Policymakers, security professionals, infrastructure operators, academics, and readers following homeland security issues will find this volume of great interest.

This book covers novel research on construction and analysis of optimal cryptographic functions such as almost perfect nonlinear (APN), almost bent (AB), planar and bent functions. These functions have optimal resistance to linear and/or differential attacks, which are the two most powerful attacks on symmetric cryptosystems. Besides cryptographic applications, these functions are significant in many branches of mathematics and information theory including coding theory, combinatorics, commutative algebra, finite geometry, sequence design and quantum information theory. The author analyzes equivalence relations for these functions and develops several new methods for construction of their infinite families. In addition, the book offers solutions to two longstanding open problems, including the problem on characterization of APN and AB functions via Boolean, and the problem on the relation between two classes of bent functions.

The field of enterprise systems integration is constantly evolving, as every new technology that is introduced appears to make all previous ones obsolete. Despite this continuous evolution, there is a set of underlying concepts and technologies that have been gaining an increasing importance in this field. Examples are asynchronous messaging through message queues, data and application adapters based on XML and Web services, the principles associated with the service-oriented architecture (SOA), service composition, orchestrations, and advanced mechanisms such as correlations and long-running transactions. Today, these concepts have reached a significant level of maturity and they represent the foundation over which most integration platforms have been built.

This book addresses integration with a view towards supporting business processes. From messaging systems to data and application adapters, and then to services, orchestrations, and choreographies, the focus is placed on the connection between systems and business processes, and particularly on how it is possible to develop an integrated application infrastructure in order to implement the desired business processes. For this purpose, the text follows a layered, bottom-up approach, with application-oriented integration at the lowest level, followed by service-oriented integration and finally completed by process-oriented integration at the topmost level. The presentation of concepts is accompanied by a set of instructive examples using state-of-the-art technologies such as Java Message Service (JMS), Microsoft Message Queuing (MSMQ), Web Services, Microsoft BizTalk Server, and the Business Process Execution Language (BPEL).

The book is intended as a textbook for advance undergraduate or beginning graduate students in computer science, especially for those in an information systems curriculum. IT professionals with a background in programming, databases and XML will also benefit from the step-by-step description of the various integration levels and the related implementation examples.

During the last few years, software evolution research has explored new domains such as the study of socio-technical aspects and collaboration between different individuals contributing to a software system, the use of search-based techniques and meta-heuristics, the mining of unstructured software repositories, the evolution of software requirements, and the dynamic adaptation of software systems at runtime. Also more and more attention is being paid to the evolution of collections of inter-related and inter-dependent software projects, be it in the form of web systems, software product families, software ecosystems or systems of systems.

With this book, the editors present insightful contributions on these and other domains currently being intensively explored, written by renowned researchers in the respective fields of software evolution. Each chapter presents the state of the art in a particular topic, as well as the current research, available tool support and remaining challenges. The book is complemented by a glossary of important terms used in the community, a reference list of nearly 1,000 papers and books and tips on additional resources that may be useful to the reader (reference books, journals, standards and major scientific events in the domain of software evolution and datasets).This book is intended for all those interested in software engineering, and more particularly, software maintenance and evolution. Researchers and software practitioners alike will find in the contributed chapters an overview of the most recent findings, covering a broad spectrum of software evolution topics. In addition, it can also serve as the basis of graduate or postgraduate courses on e.g., software evolution, requirements engineering, model-driven software development or social informatics.

Organizations with computer networks, Web sites, and employees carrying laptops and Blackberries face an array of security challenges. Among other things, they need to keep unauthorized people out of the network, thwart Web site hackers, and keep data safe from prying eyes or criminal hands. This book provides a high-level overview of these challenges and more. But it is not for the hard-core IT security engineer who works full time on networks. Instead, it is aimed at the nontechnical executive with responsibility for ensuring that information and assets stay safe and private. Written by a practicing information security officer, Philip Alexander, the book contains the latest information and arms readers with the knowledge they need to make better business decisions. Information Security: A Manager's Guide to Thwarting Data Thieves and Hackers covers the following technical issues in a nontechnical manner: -The concept of "defense in depth" -Network design -Business-continuity planning -Authentication and authorization -Providing security for your mobile work force -Hackers and the challenges they can present -Viruses, Trojans, and worms But it doesn't stop there. The book goes beyond the technical and covers highly important topics related to data security like outsourcing, contractual considerations with vendors, data privacy laws, and hiring practices. In short, Alexander gives the reader a 360-degree look at data security: What to be worried about; what to look for; the tradeoffs among cost, efficiency, and speed; what different technologies can and can't do; and how to make sure technical professionals are keeping their eyes on the right ball. Best of all, it conveys informationin an understandable way, meaning managers won't need to rely solely on the IT people in their own company--who may speak an entirely different language and have entirely different concerns. Hackers and data thieves are getting smarter and bolder every day. Information Security is your first line of defense.

This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.