Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. In the first volume of this comprehensive two-volume handbook, the authors present several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data. The second volume is dedicated to a wide range of applications in secure data storage, privacy-preserving, Software Defined Networks (SDN), Internet of Things (IoTs), behaviour analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual sentiment analysis, wavelet Neural Network via GPU, stock market movement predictions, and financial reporting. The two-volume work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics.

In the world of mathematics and computer science, technological advancements are constantly being researched and applied to ongoing issues. Setbacks in social networking, engineering, and automation are themes that affect everyday life, and researchers have been looking for new techniques in which to solve these challenges. Graph theory is a widely studied topic that is now being applied to real-life problems. Advanced Applications of Graph Theory in Modern Society is an essential reference source that discusses recent developments on graph theory, as well as its representation in social networks, artificial neural networks, and many complex networks. The book aims to study results that are useful in the fields of robotics and machine learning and will examine different engineering issues that are closely related to fuzzy graph theory. Featuring research on topics such as artificial neural systems and robotics, this book is ideally designed for mathematicians, research scholars, practitioners, professionals, engineers, and students seeking an innovative overview of graphic theory.

The emergence of cloud computing, internet of things, mobile technologies, and social networking have created better-connected members of the public who are digitally linked with each other in real time. Establishing this two-way interaction between citizens and governments has thus become attractive and an expected feature of governments worldwide. Previously, federal and local governments relied on first-generation technologies to provide basic levels of automation and digitization. Now, because of their desire to become more open, transparent, accountable, and connected, newer technologies including cloud computing, mobile networking, big data analytics, Web 2.0, and social media must be developed and utilized. Web 2.0 and Cloud Technologies for Implementing Connected Government is an essential reference source that presents various dimensions of connected government and connected e-governance visions as well as the latest emerging technologies. Offering development methodologies, practical examples, best practices, case studies, and the latest research, this book covers new strategies for implementing better-connected government models and the technologies that serve to establish these frameworks, including in-depth examinations of mobile technologies, automation, business intelligence, etc. as well as the various ethical and security issues surrounding the use and protection of data. This book is essential for federal, state, and local government officials; policymakers; civil servants; IT specialists; security analysts; academicians; researchers; and students.

In recent years, smart cities have been an emerging area of interest across the world. Due to this, numerous technologies and tools, such as building information modeling (BIM) and digital twins, have been developed to help achieve smart cities. To ensure research is continuously up to date and new technologies are considered within the field, further study is required. The Research Anthology on BIM and Digital Twins in Smart Cities considers the uses, challenges, and opportunities of BIM and digital twins within smart cities. Covering key topics such as data, design, urban areas, technology, and sustainability, this major reference work is ideal for industry professionals, government officials, computer scientists, policymakers, researchers, scholars, practitioners, instructors, and students.

First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users' data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters.

Modern businesses are on the lookout for ventures that boost their profits and marketability. Certain new and innovative technological advances can help enterprises accomplish their ambitious goals while providing detailed information to assess all aspects of the business. Global Virtual Enterprises in Cloud Computing Environments is a collection of innovative studies on business processes, procedures, methods, strategy, management thinking, and utilization of technology in cloud computing environments. While highlighting topics including international business strategy, virtual reality, and intellectual capital, this book is ideally designed for corporate executives, research scholars, and students pursuing courses in the areas of management and big data applications seeking current research on effective open innovation strategies in global business.

Now that there's software in everything, how can you make anything secure? Understand how to engineer dependable systems with this newly updated classic In Security Engineering: A Guide to Building Dependable Distributed Systems, Third Edition Cambridge University professor Ross Anderson updates his classic textbook and teaches readers how to design, implement, and test systems to withstand both error and attack. This book became a best-seller in 2001 and helped establish the discipline of security engineering. By the second edition in 2008, underground dark markets had let the bad guys specialize and scale up; attacks were increasingly on users rather than on technology. The book repeated its success by showing how security engineers can focus on usability. Now the third edition brings it up to date for 2020. As people now go online from phones more than laptops, most servers are in the cloud, online advertising drives the Internet and social networks have taken over much human interaction, many patterns of crime and abuse are the same, but the methods have evolved. Ross Anderson explores what security engineering means in 2020, including: How the basic elements of cryptography, protocols, and access control translate to the new world of phones, cloud services, social media and the Internet of Things Who the attackers are - from nation states and business competitors through criminal gangs to stalkers and playground bullies What they do - from phishing and carding through SIM swapping and software exploits to DDoS and fake news Security psychology, from privacy through ease-of-use to deception The economics of security and dependability - why companies build vulnerable systems and governments look the other way How dozens of industries went online - well or badly How to manage security and safety engineering in a world of agile development - from reliability engineering to DevSecOps The third edition of Security Engineering ends with a grand challenge: sustainable security. As we build ever more software and connectivity into safety-critical durable goods like cars and medical devices, how do we design systems we can maintain and defend for decades? Or will everything in the world need monthly software upgrades, and become unsafe once they stop?