Description
Book SynopsisIn recent years, the rising complexity of Internet of Things (IoT) systems has increased their potential vulnerabilities and introduced new cybersecurity challenges. In this context, state of the art methods and technologies for security risk assessment have prominent limitations when it comes to large scale, cyber-physical and interconnected IoT systems. Risk assessments for modern IoT systems must be frequent, dynamic and driven by knowledge about both cyber and physical assets. Furthermore, they should be more proactive, more automated, and able to leverage information shared across IoT value chains.
This book introduces a set of novel risk assessment techniques and their role in the IoT Security risk management process. Specifically, it presents architectures and platforms for end-to-end security, including their implementation based on the edge/fog computing paradigm. It also highlights machine learning techniques that boost the automation and proactiveness of IoT security risk assessments. Furthermore, blockchain solutions for open and transparent sharing of IoT security information across the supply chain are introduced. Frameworks for privacy awareness, along with technical measures that enable privacy risk assessment and boost GDPR compliance are also presented. Likewise, the book illustrates novel solutions for security certification of IoT systems, along with techniques for IoT security interoperability.In the coming years, IoT security will be a challenging, yet very exciting journey for IoT stakeholders, including security experts, consultants, security research organizations and IoT solution providers. The book provides knowledge and insights about where we stand on this journey. It also attempts to develop a vision for the future and to help readers start their IoT Security efforts on the right foot.
Table of Contents
- 1. Introduction
- 2. Security Data Modelling for Configurable Risk Assessment as a Service in IoT Systems
- 3. Data-Driven IoT Security Using Deep Learning Techniques
- 4. Privacy awareness, risk assessment and control measures in IoT platforms: BRAIN-IoT approach
- 5. IoT Network Risk Assessment and Mitigation: The SerIoT Approach
- 6. CHARIOT Integrated Approach to Safety, Privacy and Security
- 7. Pattern-driven Security, Privacy, Dependability and Interoperability in IoT
- 8. Enabling Continuous Privacy Risk Management in IoT Systems
- 9. Data Protection compliance assessment for the Internet of Things
- 10. Cybersecurity certification in IoT environments
- 11. Firmware software analysis at source code and binary levels
- 12. End-to-end security for IoT
- 13. Blockchain ledger solution affirming physical, operational and functional changes in an IoT system
- 14. Leveraging Interledger Technologies in IoT Security Risk Management
- 15. Epilogue
