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Machine Learning Techniques and Analytics for Cloud Security
Читать книгу Machine Learning Techniques and Analytics for Cloud Security - Группа авторов - Страница 1
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Страница 1
Table of Contents
List of Figures
List of Table
Guide
Pages
Страница 7
Страница 8
Страница 9
Страница 10
Preface
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1
Hybrid Cloud: A New Paradigm in Cloud Computing
1.1 Introduction
1.2 Hybrid Cloud
1.2.1 Architecture
1.2.2 Why Hybrid Cloud is Required?
1.2.3 Business and Hybrid Cloud
1.2.4 Things to Remember When Deploying Hybrid Cloud
1.3 Comparison Among Different Hybrid Cloud Providers
1.3.1 Cloud Storage and Backup Benefits
1.3.2 Pros and Cons of Different Service Providers
1.3.2.1 AWS Outpost
1.3.2.2 Microsoft Azure Stack
1.3.2.3 Google Cloud Anthos
1.3.3 Review on Storage of the Providers
1.3.3.1 AWS Outpost Storage
1.3.3.2 Google Cloud Anthos Storage
1.3.4 Pricing
1.4 Hybrid Cloud in Education
1.5 Significance of Hybrid Cloud Post-Pandemic
1.6 Security in Hybrid Cloud
1.6.1 Role of Human Error in Cloud Security
1.6.2 Handling Security Challenges
1.7 Use of AI in Hybrid Cloud
1.8 Future Research Direction
1.9 Conclusion
References
Страница 39
2
Recognition of Differentially Expressed Glycan Structure of H1N1 Virus Using Unsupervised Learning Framework
2.1 Introduction
2.2 Proposed Methodology
2.3 Result
2.3.1 Description of Datasets
2.3.2 Analysis of Result
2.3.3 Validation of Results
2.3.3.1 T-Test (Statistical Validation)
2.3.3.2 Statistical Validation
2.3.4 Glycan Cloud
2.4 Conclusions and Future Work
References
Страница 51
3
Selection of Certain Cancer Mediating Genes Using a Hybrid Model Logistic Regression Supported by Principal Component Analysis (PC-LR)
3.1 Introduction
3.2 Related Methods
3.3 Methodology
3.3.1 Description
3.3.2 Flowchart
3.3.3 Algorithm
3.3.4 Interpretation of the Algorithm
3.3.5 Illustration
3.4 Result
3.4.1 Description of the Dataset
3.4.2 Result Analysis
3.4.3 Result Set Validation
3.5 Application in Cloud Domain
3.6 Conclusion
References
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Cost-Effective Voice-Controlled Real-Time Smart Informative Interface Design With Google Assistance Technology
4.1 Introduction
4.2 Home Automation System
4.2.1 Sensors
4.2.2 Protocols
4.2.3 Technologies
4.2.4 Advantages
4.2.5 Disadvantages
4.3 Literature Review
4.4 Role of Sensors and Microcontrollers in Smart Home Design
4.5 Motivation of the Project
4.6 Smart Informative and Command Accepting Interface
4.7 Data Flow Diagram
4.8 Components of Informative Interface
4.9 Results
4.9.1 Circuit Design
4.9.2 LDR Data
4.9.3 API Data
4.10 Conclusion
4.11 Future Scope
References
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