Machine Learning Technology and Analytics for Cloud Security It covers new methodologies, research, case studies, and policies on almost all machine learning techniques and analytics for cloud security solutions.
This book aims to integrate machine learning approaches to address various analytical problems in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical treatment. Traditional encryption approaches are poorly applicable to resource-constrained devices. To address these issues, machine learning approaches can be effectively used to provide security for the ever-expanding cloud environment.
Machine learning algorithms can also be used to address various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, countermeasures against passive attacks, protocol design, privacy system design, and applications.
The book also includes case studies/projects outlining how machine learning algorithms and analytics can be used to implement various security capabilities into existing cloud-based products across public, private, and hybrid clouds.
Machine learning techniques and analytics for cloud security, It's sold by Wiley and normally retails for $194, but for a limited time it's available completely free to BetaNews readers.
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