Critical systems and infrastructure rely heavily on ICT systems and networks where security issues are a major concern. Authentication methods verify that messages come from trusted sources and guarantee the smooth flow of information and data. In this edited reference, the authors present state-of-art research and development in authentication technologies including challenges and applications for Cloud Technologies, IoT and Big Data. Topics covered include authentication; cryptographic algorithms; digital watermarking; biometric authentication; block ciphers with applications in IoT; identification schemes for Cloud and IoT; authentication issues for Cloud applications; cryptography engines for Cloud based on FPGA; and data protection laws.

This comprehensive guide to blockchain technologies in networks covers principles, core technologies and innovative applications. It gives unprecedented insights into recent advances and developments in the area, and explains how blockchain technologies make networks more secure and fit-for-purpose. A wide range of topics are covered, touching on many of the areas where this technology is already in use. Applications include cryptographic hash, digital signature and distributed consensus mechanisms, smart contracts, social networks, reputation systems, and security and financial services.

Cloud Computing has already been embraced by many organizations and individuals due to its benefits of economy, reliability, scalability and guaranteed quality of service among others. But since the data is not stored, analysed or computed on site, this can open security, privacy, trust and compliance issues. This one-stop reference covers a wide range of issues on data security in Cloud Computing ranging from accountability, to data provenance, identity and risk management.

Data Security in Cloud Computing covers major aspects of securing data in Cloud Computing. Topics covered include NOMAD: a framework for ensuring data confidentiality in mission-critical cloud based applications; 3DCrypt: privacy-preserving pre-classification volume ray-casting of 3D images in the cloud; multiprocessor system-on-chip for processing data in Cloud Computing; distributing encoded data for private processing in the cloud; data protection and mobility management for cloud; understanding software defined perimeter; security, trust and privacy for Cloud Computing in transportation cyber-physical systems; review of data leakage attack techniques in cloud systems; Cloud Computing and personal data processing: sorting out legal requirements; the Waikato data privacy matrix; provenance reconstruction in clouds; and security visualization for Cloud Computing.

In this title, a team of top experts address cyber security for e-Health technologies and systems. It examines the need for better security and privacy infrastructure, outlining methods and policies for working with sensitive data. The authors focus on the latest methods and visionary work within health and social care for cyber security, making it vital reading for professionals and researchers in healthcare technologies and security, professionals in public health and law, healthcare policy developers and government decision makers.

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This book covers state of the art interdisciplinary research on key disruptive and interrelated technologies such as Big Data, Edge computing, IoT and Cloud computing. The authors address the challenges from a distributed system perspective, with clear contributions in theory and applications. Real-world case studies look at the integration of these technologies in healthcare, disaster management, smart grids, and other areas. The book covers vital topics including devices and sensing; cloud and edge Infrastructure; big data processing; application resource management; and privacy and security.

With the rapid evolution of cyberspace, computing, communications and sensing technologies, organizations and individuals rely more and more on new applications such as fog and cloud computing, smart cities, Internet of Things (IoT), collaborative computing, and virtual and mixed reality environments. Maintaining their security, trustworthiness and resilience to cyber-attacks has become crucial which requires innovative and creative cyber security and resiliency solutions. Computing algorithms have been developed to mimic the operation of natural processes, phenomena and organisms such as artificial neural networks, swarm intelligence, deep learning systems, biomimicry, and more. The amazing characteristics of these systems offer a plethora of novel methodologies and opportunities to cope with emerging cyber challenges.

This edited book presents a timely review of the fundamentals, latest developments and diverse applications of nature-inspired algorithms in cyber security and resiliency. Topics include bio-inspired collaboration and cyber security; immune-based defense and resiliency; bio-inspired security and resiliency of network traffic; nature inspired machine learning approach for cyber security; nature-inspired algorithms in A.I. for malicious activity detection; DNA-inspired characterization and detection of novel social Twitter spambots; nature-inspired approaches for social network security; bio-inspired cyber-security for smart grid; nature-inspired cryptography and cryptanalysis, and more.

Security and development matter: they often involve issues of life and death and they determine the allocation of truly staggering amounts of the world’s resources. Particularly since the start of the wars in Afghanistan and Iraq, there has been momentum in policy circles to merge the issues of security and development to attempt to end conflicts, create durable peace, strengthen failing states, and promote the conditions necessary for people to lead healthier and more prosperous lives.

In many ways this blending of security and development agendas seems admirable and designed to produce positive outcomes all around. However, it is often the case that the two concepts in combination do not receive equal weight, with security issues getting priority over development concerns. This is not desirable and actually undermines security in the longer term. Moreover, there are major challenges in practice when security practitioners and development practitioners are asked to agree on priorities and work together.

Security and Development in Global Politics illuminates the common points of interest but also the significant differences between security and development agendas and approaches to problem solving. With insightful chapter pairings—each written by a development expert and a security analyst—the book explores seven core international issues: aid, humanitarian assistance, governance, health, poverty, trade and resources, and demography. Using this comparative structure, the book effectively assesses the extent to which there really is a nexus between security and development and, most importantly, whether the link should be encouraged or resisted.

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and data becomes more critical with emerging security and privacy threats and challenges. This book presents a comprehensive view on how to advance security and privacy in big data, cloud computing, and their applications. Topics include cryptographic tools, SDN security, big data security in IoT, privacy preserving in big data, security architecture based on cyber kill chain, privacy-aware digital forensics, trustworthy computing, privacy verification based on machine learning, and chaos-based communication systems. This book is an essential reading for networking, computing, and communications professionals, researchers, students and engineers, working with big data and cloud computing.

Hospitals, medical practices and healthcare organizations are implementing new technologies at breakneck speed. Yet privacy and security considerations are often an afterthought, putting healthcare organizations at risk of data security and privacy issues, fines, damage to their reputations, with serious potential consequences for the patients. Electronic Health Record systems (EHRs) consist of clinical notes, patient listings, lab results, imaging results and screening tests. EHRs are growing in complexity over time and requiring increasing amounts of data storage.

With the development of the IoT, the Cloud and Smart Cities frameworks, new privacy and security methods are being pursued to secure healthcare-based systems and platforms. Presenting a detailed framework as well as comparative case studies for security protection, data integrity, privacy preservation, scalability, and healthcare legislation, this edited volume covers state of the art research and addresses privacy and security methods and technologies for EHRs.

As computers are increasingly embedded, ubiquitous and wirelessly connected, security becomes imperative. This has led to the development of the notion of a 'trusted platform', the chief characteristic of which is the possession of a trusted hardware element which is able to check all or part of the software running on this platform. This enables parties to verify the software environment running on a remote trusted platform, and hence to have some trust that the data sent to that machine will be processed in accordance with agreed rules.

This new text introduces recent technological developments in trusted computing, and surveys the various current approaches to providing trusted platforms. It also includes application examples based on recent and ongoing research. The core of the book is based on an open workshop on Trusted Computing, held at Royal Holloway, University of London, UK.

Trusted Platform Modules (TPMs) are small, inexpensive chips which provide a limited set of security functions. They are most commonly found as a motherboard component on laptops and desktops aimed at the corporate or government markets, but can also be found on many consumer-grade machines and servers, or purchased as independent components. Their role is to serve as a Root of Trust - a highly trusted component from which we can bootstrap trust in other parts of a system. TPMs are most useful for three kinds of tasks: remotely identifying a machine, or machine authentication; providing hardware protection of secrets, or data protection; and providing verifiable evidence about a machine's state, or attestation.

This book describes the primary uses for TPMs, and practical considerations such as when TPMs can and should be used, when they shouldn't be, what advantages they provide, and how to actually make use of them, with use cases and worked examples of how to implement these use cases on a real system. Topics covered include when to use a TPM; TPM concepts and functionality; programming introduction; provisioning: getting the TPM ready to use; first steps: TPM keys; machine authentication; data protection; attestation; other TPM features; software and specifications; and troubleshooting. Appendices contain basic cryptographic concepts; command equivalence and requirements charts; and complete code samples.

The interplay of privacy, security and user-determination is an important consideration in the roll-out of biometric technologies. It brings into play requirements such as privacy of biometric data in systems, communication and databases, soft biometric profiling, biometric recognition of persons across distributed systems and in nomadic scenarios, and the convergence between user convenience, usability and authentication reliability.

User-Centric Privacy and Security in Biometrics explores how developments in biometrics will address security and privacy aspects. The book surveys and evaluates how biometric techniques can enhance and increase the reliability of security strategies in a variety of applications. This includes privacy-preserving state-of-the-art works and future directions in the view of biometrics as part of broader security concepts. The fundamental emphasis is on privacy within and for biometrics, particularly for the protection of biometric data, informed consent of data usage, transparency on biometric data, and big data fraud prevention.