Iot Supply Chain Security Risk Analysis And Mitigation
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IoT Supply Chain Security Risk Analysis and Mitigation
This SpringerBrief introduces methodologies and tools for quantitative understanding and assessment of supply chain risk to critical infrastructure systems. It unites system reliability analysis, optimization theory, detection theory and mechanism design theory to study vendor involvement in overall system security. It also provides decision support for risk mitigation. This SpringerBrief introduces I-SCRAM, a software tool to assess the risk. It enables critical infrastructure operators to make risk-informed decisions relating to the supply chain, while deploying their IT/OT and IoT systems. The authors present examples and case studies on supply chain risk assessment/mitigation of modern connected infrastructure systems such as autonomous vehicles, industrial control systems, autonomous truck platooning and more. It also discusses how vendors of different system components are involved in the overall security posture of the system and how the risk can be mitigated through vendor selection and diversification. The specific topics in this book include: Risk modeling and analysis of IoT supply chains Methodologies for risk mitigation, policy management, accountability, and cyber insurance Tutorial on a software tool for supply chain risk management of IoT These topics are supported by up-to-date summaries of the authors’ recent research findings. The authors introduce a taxonomy of supply chain security and discusses the future challenges and directions in securing the supply chains of IoT systems. It also focuses on the need for joint policy and technical solutions to counter the emerging risks, where technology should inform policy and policy should regulate technology development. This SpringerBrief has self-contained chapters, facilitating the readers to peruse individual topics of interest. It provides a broad understanding of the emerging field of cyber supply chain security in the context of IoT systems to academics, industry professionals and government officials.
Decision Making and Security Risk Management for IoT Environments
This book contains contemporary research that outlines and addresses security, privacy challenges and decision-making in IoT environments. The authors provide a variety of subjects related to the following Keywords: IoT, security, AI, deep learning, federated learning, intrusion detection systems, and distributed computing paradigms. This book also offers a collection of the most up-to-date research, providing a complete overview of security and privacy-preserving in IoT environments. It introduces new approaches based on machine learning that tackles security challenges and provides the field with new research material that’s not covered in the primary literature. The Internet of Things (IoT) refers to a network of tiny devices linked to the Internet or other communication networks. IoT is gaining popularity, because it opens up new possibilities for developing many modern applications. This would include smart cities, smart agriculture, innovative healthcare services and more. The worldwide IoT market surpassed $100 billion in sales for the first time in 2017, and forecasts show that this number might reach $1.6 trillion by 2025. However, as IoT devices grow more widespread, threats, privacy and security concerns are growing. The massive volume of data exchanged highlights significant challenges to preserving individual privacy and securing shared data. Therefore, securing the IoT environment becomes difficult for research and industry stakeholders. Researchers, graduate students and educators in the fields of computer science, cybersecurity, distributed systems and artificial intelligence will want to purchase this book. It will also be a valuable companion for users and developers interested in decision-making and security risk management in IoT environments.
Supply Chain Software Security
Delve deep into the forefront of technological advancements shaping the future of supply chain safety and resilience. In an era where software supply chains are the backbone of global technology ecosystems, securing them against evolving threats has become mission critical. This book offers a comprehensive guide to understanding and implementing next-generation strategies that protect these intricate networks from most pressing risks. This book begins by laying the foundation of modern software supply chain security, exploring the shifting threat landscape and key technologies driving the future. Delve into the heart of how AI and IoT are transforming supply chain protection through advanced predictive analytics, real-time monitoring, and intelligent automation. Discover how integrating application security practices within your supply chain can safeguard critical systems and data. Through real-world case studies and practical insights, learn how to build resilient supply chains equipped to defend against sophisticated attacks like dependency confusion, backdoor injection, and adversarial manipulation. Whether you’re managing a global software operation or integrating DevSecOps into your CI/CD pipelines, this book offers actionable advice for fortifying your supply chain end-to-end. You Will: Learn the role of AI and machine learning in enhancing supply chain threat detection Find out the best practices for embedding application security within the supply chain lifecycle Understand how to leverage IoT for secure, real-time supply chain monitoring and control Who Is This Book For The target audience for a book would typically include professionals and individuals with an interest or involvement in cloud-native application development and DevOps practices. It will cover fundamentals of cloud-native architecture, DevOps principles, and provide practical guidance for building and maintaining scalable and reliable applications in a cloud-native environment. The book's content will cater to beginner to intermediate level professionals seeking in-depth insights.