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Decentralized Identity Explained

You're reading from   Decentralized Identity Explained Embrace decentralization for a more secure and empowering digital experience

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781804617632
Length 392 pages
Edition 1st Edition
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Author (1):
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Rohan Pinto Rohan Pinto
Author Profile Icon Rohan Pinto
Rohan Pinto
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1 - Digital Identity Era: Then
2. Chapter 1: The History of Digital Identity FREE CHAPTER 3. Chapter 2: Identity Management Versus Access Management 4. Part 2 - Digital Identity Era: Now
5. Chapter 3: IAM Best Practices 6. Chapter 4: Trust Anchors/Sources of Truth and Their Importance 7. Chapter 5: Historical Source of Authority 8. Chapter 6: The Relationship between Trust and Risk 9. Chapter 7: Informed Consent and Why It Matters 10. Chapter 8: IAM – the Security Perspective 11. Part 3 - Digital Identity Era: The Near Future
12. Chapter 9: Self-Sovereign Identity 13. Chapter 10: Privacy by Design in the SSI Space 14. Chapter 11: Relationship between DIDs and SSI 15. Chapter 12: Protocols and Standards – DID Standards 16. Chapter 13: DID Authentication 17. Chapter 14: Identity Verification 18. Part 4 - Digital Identity Era: A Probabilistic Future
19. Chapter 15: Biometrics Security in Distributed Identity Management 20. Index 21. Other Books You May Enjoy

To get the most out of this book

Before diving into learning about distributed systems, it is recommended to have a good foundation in the following areas:

  • Computer networking: A good understanding of computer networking concepts is essential to understand how distributed systems work. Concepts such as TCP/IP, routing, and protocols such as HTTP are fundamental to distributed systems.
  • Operating systems: Understanding operating system concepts, such as process management, memory management, and filesystems, is important as distributed systems often involve multiple nodes with their own operating systems.
  • Data structures and algorithms: Understanding basic data structures and algorithms, such as trees, graphs, hash tables, and search algorithms, is important, as they are used extensively in distributed systems for storing and retrieving data.
  • Programming: Knowledge of a programming language such as Java, Python, or C++ is essential, as distributed systems are usually implemented using these languages.
  • Database systems: Understanding basic concepts of database systems, such as data modeling, normalization, indexing, and transactions, is important since distributed systems need to store and access data across multiple nodes.
  • Cloud computing: Knowledge of cloud computing concepts, such as virtualization, load balancing, and autoscaling, is important since many distributed systems are implemented on cloud infrastructure.

Having a good foundation in these areas will provide a solid basis for understanding distributed systems and their implementation. However, learning about distributed systems is an ongoing process that requires continuous learning and staying up to date with the latest technologies and best practices.

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