This book, authored by some of the pioneers in the security certification domain, provides a foundational knowledge base for designing and deploying effective security certification schemes for cloud-edge distributed systems.

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This book, authored by some of the pioneers in the security certification domain, provides a foundational knowledge base for designing and deploying effective security certification schemes for cloud-edge distributed systems. It gives readers unique and essential insight into the history of security certification and its evolution from static to dynamic models. The book helps readers to understand the importance of security certification across distributed system evolution from cloud-based to artificial intelligence-machine learning systems. It covers in full the certification of cloud-based composite services, discussing the role of multi-factor certification. It also emphasizes processes for continuously certifying services across system and context changes, as well as the certification of the deployment environment and development process and their impact on the overall cloud service certification. The book considers and challenges existing security certification schemes for cloud services, discussing issues and gaps when applied to modern systems in the cloud-edge continuum and built on artificial intelligence. Readers will become familiar with the challenges in certifying cloud-edge distributed systems and machine learning-based systems.
This book also provides actionable insight to readers who manage modern security systems. Security controls have grown in size and complexity, requiring reliable and sustainable certification schemes to support varying quality standards and produce compliant products. It covers the logic behind security standards and the evaluation criteria of main certification standards, further discussing the evolution and corresponding certification of distributed systems towards cloud, cloud-edge, and artificial intelligence. The book teaches readers how to build faster, scalable, and more reliable cloud-edge distributed systems and beyond.

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Establishes the essential role of staging or training Machine Learning algorithms at the component and entire pipeline levels to ensure verifiable and secure systems Reveals weaknesses in traditional certification and verification processes and the strengths of dynamic systems using certified Machine Learning Examines the differences and evolution between continuous, dynamic, adaptive, and virtual certification models as well as international standards and regulations
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Produktdetaljer

ISBN
9783031597237
Publisert
2024-07-18
Utgiver
Vendor
Springer International Publishing AG
Høyde
240 mm
Bredde
168 mm
Aldersnivå
Professional/practitioner, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet