From cloud computing to big data to mobile technologies, there is a vast supply of information being mined and collected. With an abundant amount of information being accessed, stored, and saved, basic controls are needed to protect and prevent security incidents as well as ensure business continuity. Applications of Security, Mobile, Analytic, and Cloud (SMAC) Technologies for Effective Information Processing and Management is a vital resource that discusses various research findings and innovations in the areas of big data analytics, mobile communication and mobile applications, distributed systems, and information security. With a focus on big data, the internet of things (IoT), mobile technologies, cloud computing, and information security, this book proves a vital resource for computer engineers, IT specialists, software developers, researchers, and graduate-level students seeking current research on SMAC technologies and information security management systems.

In the last few decades, the use of the Internet has grown tremendously, and the use of online communications has grown even more. The lack of security in private messages between individuals, however, allows hackers to collect loads of sensitive information. Modern security measures are required to prevent this attack on the world’s communication technologies. Advanced Digital Image Steganography Using LSB, PVD, and EMD: Emerging Research and Opportunities provides evolving research exploring the theoretical and practical aspects of data encryption techniques and applications within computer science. The book provides introductory knowledge on steganography and its importance, detailed analysis of how RS and PDH are performed, discussion on pixel value differencing principles, and hybrid approaches using substitution, PVD, and EMD principles. It is ideally designed for researchers and graduate and under graduate students seeking current research on the security of data during transit.

Businesses constantly face online hacking threats or security breaches in their online mainframe that expose sensitive information to the wrong audience. Companies look to store their data in a separate location, distancing the availability of the information and reducing the risk of data breaches. Modern organizations need to remain vigilant against insider attacks, cloud computing risks, and security flaws within their mainframe. Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities is an essential reference source that discusses maintaining a secure management of sensitive data, and intellectual property and provides a robust security algorithm on consumer data. Featuring research on topics such as public cryptography, security principles, and trustworthy computing, this book is ideally designed for IT professionals, business managers, researchers, students, and professionals seeking coverage on preventing and detecting the insider attacks using trusted cloud computing techniques.

Interdisciplinary approaches using Machine Learning and Deep Learning techniques are smartly addressing real life challenges and have emerged as an inseparable element of disruption in current times. Applications of Disruptive Technology in Management practices are an ever interesting domain for researchers and professionals. This volume entitled Emerging Trends in Disruptive Technology Management for Sustainable Development has attempted to collate five different interesting research approaches that have innovatively reflected diverse potential of disruptive trends in the era of 4th. Industrial Revolution. The uniqueness of the volume is going to cater the entrepreneurs and professionals in the domain of artificial intelligence, machine learning, deep learning etc. with its unique propositions in each of the chapters. The volume is surely going to be a significant source of knowledge and inspiration to those aspiring minds endeavouring to shape their futures in the area of applied research in machine learning and computer vision. The expertise and experiences of the contributing authors to this volume is encompassing different fields of proficiencies. This has set an excellent prelude to discover the correlation among multidisciplinary approaches of innovation. Covering a broad range of topics initiating from IoT based sustainable development to crowd sourcing concepts with a blend of applied machine learning approaches has made this volume a must read to inquisitive wits. Features Assorted approaches to interdisciplinary research using disruptive trends Focus on application of disruptive technology in technology management Focus on role of disruptive technology on sustainable development Promoting green IT with disruptive technology The book is meant to benefit several categories of students and researchers. At the students' level, this book can serve as a treatise/reference book for the special papers at the masters level aimed at inspiring possibly future researchers. Newly inducted PhD aspirants would also find the contents of this book useful as far as their compulsory course-works are concerned. At the researchers' level, those interested in interdisciplinary research would also be benefited from the book. After all, the enriched interdisciplinary contents of the book would always be a subject of interest to the faculties, existing research communities and new research aspirants from diverse disciplines of the concerned departments of premier institutes across the globe. This is expected to bring different research backgrounds (due to its cross platform characteristics) close to one another to form effective research groups all over the world. Above all, availability of the book should be ensured to as much universities and research institutes as possible through whatever graceful means it may be. Hope this volume will cater as a ready reference to your quest for diving deep into the ocean of technology management for 4th. Industrial Revolution.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.