This book has evolved out of roughly ve years of working on computing with social trust. In the beginning, getting people to accept that social networks and the relationships in them could be the basis for interesting, relevant, and exciting c- puter science was a struggle. Today, social networking and social computing have become hot topics, and those of us doing research in this space are nally nding a wealth of opportunities to share our work and to collaborate with others. This book is a collection of chapters that cover all the major areas of research in this space. I hope it will serve as a guide to students and researchers who want a strong introduction to work in the eld, and as encouragement and direction for those who are considering bringing their own techniques to bear on some of these problems. It has been an honor and privilege to work with these authors for whom I have so much respect and admiration. Thanks to all of them for their outstanding work, which speaks for itself, and for patiently enduringall my emails. Thanks, as always, to Jim Hendler for his constant support. Cai Ziegler has been particularly helpful, both as a collaborator, and in the early stages of development for this book. My appreciation also goes to Beverley Ford, Rebecca Mowat and everyone at Springer who helped with publication of this work.

Learn to analyze and measure risk by exploring the nature of trust and its application to cybersecurity Trust in Computer Systems and the Cloud delivers an insightful and practical new take on what it means to trust in the context of computer and network security and the impact on the emerging field of Confidential Computing. Author Mike Bursell’s experience, ranging from Chief Security Architect at Red Hat to CEO at a Confidential Computing start-up grounds the reader in fundamental concepts of trust and related ideas before discussing the more sophisticated applications of these concepts to various areas in computing. The book demonstrates in the importance of understanding and quantifying risk and draws on the social and computer sciences to explain hardware and software security, complex systems, and open source communities. It takes a detailed look at the impact of Confidential Computing on security, trust and risk and also describes the emerging concept of trust domains, which provide an alternative to standard layered security. Foundational definitions of trust from sociology and other social sciences, how they evolved, and what modern concepts of trust mean to computer professionals A comprehensive examination of the importance of systems, from open-source communities to HSMs, TPMs, and Confidential Computing with TEEs. A thorough exploration of trust domains, including explorations of communities of practice, the centralization of control and policies, and monitoring Perfect for security architects at the CISSP level or higher, Trust in Computer Systems and the Cloud is also an indispensable addition to the libraries of system architects, security system engineers, and master’s students in software architecture and security.

"This book brings together scholars with significantly different backgrounds who share interests in the interplay between trust and technology, presenting novel theoretical perspectives on the topics of trust and technology, as well as some empirical investigations into the trust-building, trust-repairing, and trust-destroying practices in the context of technology"--Provided by publisher.

Most aspects of our private and social lives—our safety, the integrity of the financial system, the functioning of utilities and other services, and national security—now depend on computing. But how can we know that this computing is trustworthy? In Mechanizing Proof, Donald MacKenzie addresses this key issue by investigating the interrelations of computing, risk, and mathematical proof over the last half century from the perspectives of history and sociology. His discussion draws on the technical literature of computer science and artificial intelligence and on extensive interviews with participants. MacKenzie argues that our culture now contains two ideals of proof: proof as traditionally conducted by human mathematicians, and formal, mechanized proof. He describes the systems constructed by those committed to the latter ideal and the many questions those systems raise about the nature of proof. He looks at the primary social influence on the development of automated proof—the need to predict the behavior of the computer systems upon which human life and security depend—and explores the involvement of powerful organizations such as the National Security Agency. He concludes that in mechanizing proof, and in pursuing dependable computer systems, we do not obviate the need for trust in our collective human judgment.

"This book offers a review of recent developments of computer security, focusing on the relevance and implications of global privacy, law, and politics for society, individuals, and corporations.It compiles timely content on such topics as reverse engineering of software, understanding emerging computer exploits, emerging lawsuits and cases, global and societal implications, and protection from attacks on privacy"--Provided by publisher.

This open access book brings together perspectives from multiple disciplines including psychology, law, IS, and computer science on data privacy and trust in the cloud. Cloud technology has fueled rapid, dramatic technological change, enabling a level of connectivity that has never been seen before in human history. However, this brave new world comes with problems. Several high-profile cases over the last few years have demonstrated cloud computing's uneasy relationship with data security and trust. This volume explores the numerous technological, process and regulatory solutions presented in academic literature as mechanisms for building trust in the cloud, including GDPR in Europe. The massive acceleration of digital adoption resulting from the COVID-19 pandemic is introducing new and significant security and privacy threats and concerns. Against this backdrop, this book provides a timely reference and organising framework for considering how we will assure privacy and build trust in such a hyper-connected digitally dependent world. This book presents a framework for assurance and accountability in the cloud and reviews the literature on trust, data privacy and protection, and ethics in cloud computing.

With increasingly divergent views and commitments, and an all-or-nothing mindset in political life, it can seem hard to sustain the level of trust in other members of our society necessary to ensure our most basic institutions work. This book features interdisciplinary perspectives on social trust. The contributors address four main topics related to social trust. The first topic is empirical and formal work on norms and institutional trust, especially the relationships between trust and human behaviour. The second topic concerns trust in particular institutions, notably the legal system, scientific community, and law enforcement. Third, the contributors address challenges posed by diversity and oppression in maintaining social trust. Finally, they discuss different forms of trust and social trust. Social Trust will be of interest to researchers in philosophy, political science, economics, law, psychology, and sociology.

The bestselling author of The End of History explains the social principles of economic life and tells readers what they need to know to win the coming struggle for global economic dominance.

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: Explains how reputation-based systems are used to determine trust in diverse online communities Describes how machine learning techniques are employed to build robust reputation systems Explores two distinctive approaches to determining credibility of resources—one where the human role is implicit, and one that leverages human input explicitly Shows how decision support can be facilitated by computational trust models Discusses collaborative filtering-based trust aware recommendation systems Defines a framework for translating a trust modeling problem into a learning problem Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.

One of the major problems in the development of virtual societies, in particular in electronic commerce and computer-mediated interactions in organizations, is trust and deception. This book provides analyses by various researchers of the different types of trust that are needed for various tasks, such as facilitating on-line collaboration, building virtual communities and network organizations, and even the design of effective and user-friendly human-computer interfaces. The book has a multi-disciplinary character providing theoretical models of trust and deception, empirical studies, and practical solutions for creating trust in electronic commerce and multi-agent systems.