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Rajdeep Chakraborty obtained his PhD in CSE from the University of Kalyani. Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography. 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. 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. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment.

The conventional cryptography approach is less applied in resource-constrained devices.

Cloud security with ML has long-standing challenges that require methodological and theoretical handling. 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. This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY

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