In today’s modern age of information, new technologies are quickly emerging and being deployed into the field of information technology. Cloud computing is a tool that has proven to be a versatile piece of software within IT. Unfortunately, the high usage of Cloud has raised many concerns related to privacy, security, and data protection that have prevented cloud computing solutions from becoming the prevalent alternative for mission critical systems. Up-to-date research and current techniques are needed to help solve these vulnerabilities in cloud computing. Modern Principles, Practices, and Algorithms for Cloud Security is a pivotal reference source that provides vital research on the application of privacy and security in cloud computing. While highlighting topics such as chaos theory, soft computing, and cloud forensics, this publication explores present techniques and methodologies, as well as current trends in cloud protection. This book is ideally designed for IT specialists, scientists, software developers, security analysts, computer engineers, academicians, researchers, and students seeking current research on the defense of cloud services.

The text provides readers with an overview of cloud computing, beginning with historical perspectives on mainframe computers and early networking protocols, moving to current issues such as security of hardware and networks, performance, evolving IoT areas, edge computing, etc.

This reference text discusses various security techniques and challenges for cloud data protection from both software and hardware aspects. The text provides readers with an overview of cloud computing, beginning with historical perspectives on mainframe computers and early networking protocols, moving to current issues such as security of hardware and networks, performance, evolving IoT areas, edge computing, etc. It also deals with threat detection and incident response in cloud security. It covers important topics including operational security agitations in cloud computing, cyber artificial intelligence (AI) platform for cloud security, and security concerns of virtualization in cloud computing. The book will serve as a useful resource for graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology.

We are now in the era of the Big Data revolution where nearly every aspect of computing engineering is driven by increasingly large, complex, and diverse datasets. Big Data presents not only a world of new opportunities but also new challenges. With threats multiplying exponentially, the ability to gather and analyze massive information will be a decisive factor in the battle against malicious software and adversaries. It is natural to consider a cloud-computing environment to address the computational requirements for big data analytic applications. However, it is equally important to address the security concerns in terms of policies, technologies, and controls deployed to protect data, applications, and the associated infrastructure of cloud computing. In this special issue of JCSM on Big Data, the article by Miller et al. focuses on technical and policy infrastructure for digital forensic analysis in the cloud as cyber-crime is a growing trend around the world. Further, the massive collections of imagery on the Internet have inspired a stream of interesting work on image processing related big data topics. The article by Shen et al. describes their novel structure-based image completion algorithm for object removal while maintaining visually plausible content with consistent structure and scene texture in photos. Such novel technique can benefit a diverse range of applications, from image restoration, to privacy protection, to photo localization. A surge of graph-computing frameworks has appeared in both academia and industry to address the needs of processing complex and large graph-structured datasets, where each has its respective benefits and drawbacks. Leveraging the right platform for the right task is daunting for users of these frameworks. A review by Zhao et al. provides the context for selecting the right graph-parallel processing framework given the tasks in hand. They have studied several popular distributed graph-computing systems aiming to reveal the characteristics of those systems in performing common graph algorithms with real-world datasets. Their findings are extremely informative.

This book provides readers with an overview of Cloud Computing, starting with historical background on mainframe computers and early networking protocols, leading to current concerns such as hardware and systems security, performance, emerging areas of IoT, Edge Computing etc. Readers will benefit from the in-depth discussion of cloud computing usage and the underlying architectures. The authors explain carefully the “why’s and how’s” of Cloud Computing, so engineers will find this book an invaluable source of information to the topic. This second edition includes new material on Cloud Computing Security, Threat Vectors and Trust Models, as well as best practices for a using dynamic cloud infrastructure, and cloud operations management. Several new examples and analysis of cloud security have been added, including edge computing with IoT devices.

This, the 30th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six in-depth papers focusing on the subject of cloud computing. Topics covered within this context include cloud storage, model-driven development, informative modeling, and security-critical systems.

This book highlights research on secure communication of 5G and the Internet of Things (IoT) Networks, along with related areas to ensure secure and Internet-compatible IoT systems. The authors not only discuss 5G and IoT security and privacy challenges, but also energy efficient approaches to improving the ecosystems through communication. The book addresses the secure communication and privacy of the 5G and IoT technologies, while also revealing the impact of IoT technologies on several scenarios in smart city design. Intended as a comprehensive introduction, the book offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in 5G and IoT technologies.

Cloud computing has quickly become the next big step in security development for companies and institutions all over the world. With the technology changing so rapidly, it is important that businesses carefully consider the available advancements and opportunities before implementing cloud computing in their organizations. The Handbook of Research on Security Considerations in Cloud Computing brings together discussion on current approaches to cloud-based technologies and assesses the possibilities for future advancements in this field. Highlighting the need for consumers to understand the unique nature of cloud-delivered security and to evaluate the different aspects of this service to verify if it will meet their needs, this book is an essential reference source for researchers, scholars, postgraduate students, and developers of cloud security systems.

It is essential for an organization to know before involving themselves in cloud computing and big data, what are the key security requirements for applications and data processing. Big data and cloud computing are integrated together in practice. Cloud computing offers massive storage, high computation power, and distributed capability to support processing of big data. In such an integrated environment the security and privacy concerns involved in both technologies become combined. This book discusses these security and privacy issues in detail and provides necessary insights into cloud computing and big data integration. It will be useful in enhancing the body of knowledge concerning innovative technologies offered by the research community in the area of cloud computing and big data. Readers can get a better understanding of the basics of cloud computing, big data, and security mitigation techniques to deal with current challenges as well as future research opportunities.