Название: Machine Learning Techniques and Analytics for Cloud Security (Advances in Learning Analytics for Intelligent Cloud-IoT Systems)
Автор: Rajdeep Chakraborty (Editor), Anupam Ghosh (Editor), Jyotsna Kumar Mandal (Editor)
Издательство: Scrivener Publishing LLC
Год: 2022
Формат: true pdf/epub
Страниц: 470
Размер: 23.4 Mb
Язык: English

This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions
The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively.