This book presents a range of cloud computing security challenges and promising solution paths. The first two chapters focus on practical considerations of cloud computing. In Chapter 1, Chandramouli, Iorga, and Chokani describe the evolution of cloud computing and the current state of practice, followed by the challenges of cryptographic key management in the cloud. In Chapter 2, Chen and Sion present a dollar cost model of cloud computing and explore the economic viability of cloud computing with and without security mechanisms involving cryptographic mechanisms. The next two chapters address security issues of the cloud infrastructure. In Chapter 3, Szefer and Lee describe a hardware-enhanced security architecture that protects the confidentiality and integrity of a virtual machine's memory from an untrusted or malicious hypervisor. In Chapter 4, Tsugawa et al. discuss the security issues introduced when Software-Defined Networking (SDN) is deployed within and across clouds. Chapters 5-9 focus on the protection of data stored in the cloud. In Chapter 5, Wang et al. present two storage isolation schemes that enable cloud users with high security requirements to verify that their disk storage is isolated from some or all other users, without any cooperation from cloud service providers. In Chapter 6, De Capitani di Vimercati, Foresti, and Samarati describe emerging approaches for protecting data stored externally and for enforcing fine-grained and selective accesses on them, and illustrate how the combination of these approaches can introduce new privacy risks. In Chapter 7, Le, Kant, and Jajodia explore data access challenges in collaborative enterprise computing environments where multiple parties formulate their own authorization rules, and discuss the problems of rule consistency, enforcement, and dynamic updates. In Chapter 8, Smith et al. address key challenges to the practical realization of a system that supports query execution over remote encrypted data without exposing decryption keys or plaintext at the server. In Chapter 9, Sun et al. provide an overview of secure search techniques over encrypted data, and then elaborate on a scheme that can achieve privacy-preserving multi-keyword text search. The next three chapters focus on the secure deployment of computations to the cloud. In Chapter 10, Oktay el al. present a risk-based approach for workload partitioning in hybrid clouds that selectively outsources data and computation based on their level of sensitivity. The chapter also describes a vulnerability assessment framework for cloud computing environments. In Chapter 11, Albanese et al. present a solution for deploying a mission in the cloud while minimizing the mission's exposure to known vulnerabilities, and a cost-effective approach to harden the computational resources selected to support the mission. In Chapter 12, Kontaxis et al. describe a system that generates computational decoys to introduce uncertainty and deceive adversaries as to which data and computation is legitimate. The last section of the book addresses issues related to security monitoring and system resilience. In Chapter 13, Zhou presents a secure, provenance-based capability that captures dependencies between system states, tracks state changes over time, and that answers attribution questions about the existence, or change, of a system's state at a given time. In Chapter 14, Wu et al. present a monitoring capability for multicore architectures that runs monitoring threads concurrently with user or kernel code to constantly check for security violations. Finally, in Chapter 15, Hasan Cam describes how to manage the risk and resilience of cyber-physical systems by employing controllability and observability techniques for linear and non-linear systems.

Compiles current research on nanomaterials as well as their versatile applications in plant biotic stress management Describes role of nanomaterials as enzyme-mimicking nanoparticles, nano-pesticides, nano-fertilizers, and nanomaterials Reviews day-to-day problems related to crop plants, their diagnostics and stress management Explores trends in nanomaterials utility towards diagnostics, enzyme-mimicking, crop protection and their possible role in plant disease management Includes pertinent nanomaterials including synthetic strategies, properties, chemistry, and applications

This new volume, Deep Learning in Visual Computing and Signal Processing, covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing. The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on deep learning, and more. Key features: Covers both the fundamentals and the latest concepts in deep learning Presents some of the diverse applications of deep learning in visual computing and signal processing Includes over 90 figures and tables to elucidate the text An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this valuable resource will serve as a guide for researchers, engineers, and students who want to have a quick start on learning and/or building deep learning systems. It provides a good theoretical and practical understanding and complete information and knowledge required to understand and build deep learning models from scratch.

This book is a collection of accepted papers that were presented at the International Conference on Communication and Computing Systems (ICCCS-2016), Dronacharya College of Engineering, Gurgaon, September 9-11, 2016. The purpose of the conference was to provide a platform for interaction between scientists from industry, academia and other areas of society to discuss the current advancements in the field of communication and computing systems. The papers submitted to the proceedings were peer-reviewed by 2-3 expert referees. This volume contains 5 main subject areas: 1. Signal and Image Processing, 2. Communication & Computer Networks, 3. Soft Computing, Intelligent System, Machine Vision and Artificial Neural Network, 4. VLSI & Embedded System, 5. Software Engineering and Emerging Technologies.

This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It describes deep learning techniques in conjunction with IoT used by practitioners and researchers worldwide. The authors explore the convergence of IoT and deep learning to enable things to communicate, share information, and coordinate decisions. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. Chapters look at assistive devices in healthcare, alerting and detection devices, energy efficiency in using IoT, data mining for gathering health information for individuals with autism, IoT for mobile applications, and more. The text also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.

This book constitutes the refereed proceedings of the 11th International Conference on Distributed Computing and Networking, ICDCN 2010, held in Kolkata, India, during January 3-6, 2010.

There were 169 submissions, 96 to the networking track and 73 to the distributed computing track. After review the committee selected 23 papers for the networking and 21 for the distributed computing track. The topics addressed are network protocol and applications, fault-tolerance and security, sensor networks, distributed algorithms and optimization, peer-to-peer networks and network tracing, parallel and distributed systems, wireless networks, applications and distributed systems, optical, cellular and mobile ad hoc networks, and theory of distributed systems.

Cyber-Physical Systems (CPS) integrate computing and communication capabilities by monitoring and controlling the physical systems via embedded hardware and computers. This book brings together new and futuristic findings on IoT, Cyber Physical Systems and Robotics leading towards Automation and solving issues of various critical applications in Real-time. The book initially overviews the concepts of IoT, IIoT and Cyber Physical Systems followed by various critical applications and discusses the latest designs and developments that provide common solutions for the convergence of technologies. In addition, the book specifies methodologies, algorithms and other relevant architectures in various fields that include Automation, Robotics, Smart Agriculture and Industry 4.0. The book is intended for practitioners, enterprise representatives, scientists, students and Ph.D Scholars in hopes of steering research further towards cyber physical systems design and development and implementation across various domains. Additionally, this book can be used as a secondary reference, or rather one-stop guide, by professionals for real-life implementation of cyber physical systems. The book highlights: * A Critical Coverage of various domains: IoT, Cyber Physical Systems, Industry 4.0, Smart Automation and related critical applications. * Advanced elaborations for target audiences to understand the conceptual methodology and future directions of cyber physical systems and IoT. * An approach towards Research Orientations to enable researchers to point out areas and scope for implementation of Cyber Physical Systems in several domains for better productivity.

This book is a collection of accepted papers that were presented at the International Conference on Communication and Computing Systems (ICCCS-2016), Dronacharya College of Engineering, Gurgaon, September 9-11, 2016. The purpose of the conference was to provide a platform for interaction between scientists from industry, academia and other areas of society to discuss the current advancements in the field of communication and computing systems. The papers submitted to the proceedings were peer-reviewed by 2-3 expert referees. This volume contains 5 main subject areas: 1. Signal and Image Processing, 2. Communication & Computer Networks, 3. Soft Computing, Intelligent System, Machine Vision and Artificial Neural Network, 4. VLSI & Embedded System, 5. Software Engineering and Emerging Technologies.

This book provides the fundamental concepts of system design using microprocessors in the field of agriculture instrumentation. It begins with an introduction to the field of agriculture and application of instrumentation in agriculture, and the book then covers the transducers specific to the agricultural field. The binary number system and arithmetic are covered as the basic building block of digital circuits and computer organization. The microprocessor basics and Intel 8085 hardware and software have been discussed in detail. The book describes microprocessor peripheral inter-facing and its support chips such as Intel 8225, Intel 8253 and Intel 8279 along with their applications. It discusses analog to digital and digital to analog interface, CRT terminal interface and printer interface. In addition, the book includes case studies on various microprocessor applications in agriculture, such as microprocessor-based system design for grain moisture, safe grain storage, soil nutrient estimation and drip irrigation. Finally, the book ends with an advanced and futuristic topic on precision agriculture to give an exposure to students about future developments in the agricultural system. Key Features : From concepts to design, the book follows a step-by-step approach. Gives a large number of figures for easy understanding of theory. Includes a good number of examples and end-of-chapter exercises both in the hardware and software sections. Presents a number of case studies on the design of microprocessor-based agri-instrumentation systems. Offers exercises on the case studies which can be used for further development of the concepts. The book is primarily intended for the undergraduate and postgraduate students of agricultural engineering for their courses on agri instrumen-tation and microprocessor applications in agriculture.

Cyber-Physical Systems (CPS) integrate computing and communication capabilities by monitoring and controlling the physical systems via embedded hardware and computers. This book brings together new and futuristic findings on IoT, Cyber Physical Systems and Robotics leading towards Automation and solving issues of various critical applications in Real-time. The book initially overviews the concepts of IoT, IIoT and Cyber Physical Systems followed by various critical applications and discusses the latest designs and developments that provide common solutions for the convergence of technologies. In addition, the book specifies methodologies, algorithms and other relevant architectures in various fields that include Automation, Robotics, Smart Agriculture and Industry 4.0. The book is intended for practitioners, enterprise representatives, scientists, students and Ph.D Scholars in hopes of steering research further towards cyber physical systems design and development and implementation across various domains. Additionally, this book can be used as a secondary reference, or rather one-stop guide, by professionals for real-life implementation of cyber physical systems. The book highlights: * A Critical Coverage of various domains: IoT, Cyber Physical Systems, Industry 4.0, Smart Automation and related critical applications. * Advanced elaborations for target audiences to understand the conceptual methodology and future directions of cyber physical systems and IoT. * An approach towards Research Orientations to enable researchers to point out areas and scope for implementation of Cyber Physical Systems in several domains for better productivity.

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.