The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks where multiple users can build their own sensing applications at the same time. It enables a multi-user on-demand sensory system, where computing, sensing, and wireless network resources are shared among applications. Therefore, it has inherent challenges for providing security and privacy across the sensor cloud infrastructure. With the integration of WSNs with different ownerships, and users running a variety of applications including their own code, there is a need for a risk assessment mechanism to estimate the likelihood and impact of attacks on the life of the network. The data being generated by the wireless sensors in a sensor cloud need to be protected against adversaries, which may be outsiders as well as insiders. Similarly, the code disseminated to the sensors within the sensor cloud needs to be protected against inside and outside adversaries. Moreover, since the wireless sensors cannot support complex and energy-intensive measures, the lightweight schemes for integrity, security, and privacy of the data have to be redesigned. The book starts with the motivation and architecture discussion of a sensor cloud. Due to the integration of multiple WSNs running user-owned applications and code, the possibility of attacks is more likely. Thus, next, we discuss a risk assessment mechanism to estimate the likelihood and impact of attacks on these WSNs in a sensor cloud using a framework that allows the security administrator to better understand the threats present and take necessary actions. Then, we discuss integrity and privacy preserving data aggregation in a sensor cloud as it becomes harder to protect data in this environment. Integrity of data can be compromised as it becomes easier for an attacker to inject false data in a sensor cloud, and due to hop by hop nature, privacy of data could be leaked as well. Next, the book discusses a fine-grained access control scheme which works on the secure aggregated data in a sensor cloud. This scheme uses Attribute Based Encryption (ABE) to achieve the objective. Furthermore, to securely and efficiently disseminate application code in sensor cloud, we present a secure code dissemination algorithm which first reduces the amount of code to be transmitted from the base station to the sensor nodes. It then uses Symmetric Proxy Re-encryption along with Bloom filters and Hash-based Message Authentication Code (HMACs) to protect the code against eavesdropping and false code injection attacks.

This holistic book is an invaluable reference for addressing various practical challenges in architecting and engineering Intelligent IoT and eHealth solutions for industry practitioners, academic and researchers, as well as for engineers involved in product development. The first part provides a comprehensive guide to fundamentals, applications, challenges, technical and economic benefits, and promises of the Internet of Things using examples of real-world applications. It also addresses all important aspects of designing and engineering cutting-edge IoT solutions using a cross-layer approach from device to fog, and cloud covering standards, protocols, design principles, reference architectures, as well as all the underlying technologies, pillars, and components such as embedded systems, network, cloud computing, data storage, data processing, big data analytics, machine learning, distributed ledger technologies, and security. In addition, it discusses the effects of Intelligent IoT, which are reflected in new business models and digital transformation. The second part provides an insightful guide to the design and deployment of IoT solutions for smart healthcare as one of the most important applications of IoT. Therefore, the second part targets smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and big data analytics that are aimed at providing connected health interventions to individuals for healthier lifestyles.

The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks where multiple users can build their own sensing applications at the same time. It enables a multi-user on-demand sensory system, where computing, sensing, and wireless network resources are shared among applications. Therefore, it has inherent challenges for providing security and privacy across the sensor cloud infrastructure. With the integration of WSNs with different ownerships, and users running a variety of applications including their own code, there is a need for a risk assessment mechanism to estimate the likelihood and impact of attacks on the life of the network. The data being generated by the wireless sensors in a sensor cloud need to be protected against adversaries, which may be outsiders as well as insiders. Similarly, the code disseminated to the sensors within the sensor cloud needs to be protected against inside and outside adversaries. Moreover, since the wireless sensors cannot support complex and energy-intensive measures, the lightweight schemes for integrity, security, and privacy of the data have to be redesigned. The book starts with the motivation and architecture discussion of a sensor cloud. Due to the integration of multiple WSNs running user-owned applications and code, the possibility of attacks is more likely. Thus, next, we discuss a risk assessment mechanism to estimate the likelihood and impact of attacks on these WSNs in a sensor cloud using a framework that allows the security administrator to better understand the threats present and take necessary actions. Then, we discuss integrity and privacy preserving data aggregation in a sensor cloud as it becomes harder to protect data in this environment. Integrity of data can be compromised as it becomes easier for an attacker to inject false data in a sensor cloud, and due to hop by hop nature, privacy of data could be leaked as well. Next, the book discusses a fine-grained access control scheme which works on the secure aggregated data in a sensor cloud. This scheme uses Attribute Based Encryption (ABE) to achieve the objective. Furthermore, to securely and efficiently disseminate application code in sensor cloud, we present a secure code dissemination algorithm which first reduces the amount of code to be transmitted from the base station to the sensor nodes. It then uses Symmetric Proxy Re-encryption along with Bloom filters and Hash-based Message Authentication Code (HMACs) to protect the code against eavesdropping and false code injection attacks.

This book constitutes the refereed proceedings of the 8th VLDB Workshop on Secure Data Management held in Seattle,WA, USA in September 2, 2011 as a satellite workshop of the VLDB 2011 Conference . The 10 revised full papers presented were carefully reviewed and selected from 19 submissions. The papers are organized in topical sections on privacy protection and quantification, security in cloud and sensor networks and secure data managment technologies.

This book gives a comprehensive and systematic review of secure compressive sensing (CS) for applications in various fields such as image processing, pattern recognition, Internet of things (IoT), and cloud computing. It will help readers grasp the knowledge of secure CS and its applications, and stimulate more readers to work on the research and development of secure CS. It discusses how CS becomes a cryptosystem, followed by the corresponding designs and analyses. The application of CS in multimedia data encryption is presented, in which the general design framework is given together with several particular frameworks including parallel CS, involvement of image processing techniques, and double protection mechanism. It also describes the applications of CS in cloud computing security and IoT security, i.e., privacy-preserving reconstruction in cloud computing and secure low-cost sampling in IoT, respectively.

Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. The Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing is a vital reference source that provides valuable insight into current and emergent research occurring within the field of distributed computing. It also presents architectures and service frameworks to achieve highly integrated distributed systems and solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting a range of topics such as data sharing, wireless sensor networks, and scalability, this multi-volume book is ideally designed for system administrators, integrators, designers, developers, researchers, academicians, and students.

This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28–31, 2022. The 34 full papers and 4 short papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in topical sections as follows: cyberspace security, cyberspace privacy, cyberspace anonymity and short papers.