Machine Learning Techniques and Analytics for Cloud Security. Группа авторов
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7 Part III CLOUD SECURITY ANALYSIS USING MACHINE LEARNING TECHNIQUES 11 Cloud Security Using Honeypot Network and Blockchain: A Review 11.1 Introduction 11.2 Cloud Computing Overview 11.3 Honeypot System 11.4 Blockchain 11.6 Comparative Analysis 11.7 Conclusion References 12 Machine Learning–Based Security in Cloud Database—A Survey 12.1 Introduction 12.2 Security Threats and Attacks 12.3 Dataset Description 12.4 Machine Learning for Cloud Security 12.5 Comparative Analysis 12.6 Conclusion References 13 Machine Learning Adversarial Attacks: A Survey Beyond 13.1 Introduction 13.2 Adversarial Learning 13.3 Taxonomy of Adversarial Attacks 13.4 Review of Adversarial Attack Methods 13.5 Adversarial Attacks on Cloud-Based Platforms 13.6 Conclusion References 14 Protocols for Cloud Security 14.1 Introduction 14.2 System and Adversarial Model 14.3 Protocols for Data Protection in Secure Cloud Computing 14.4 Protocols for Data Protection in Secure Cloud Storage 14.5 Protocols for Secure Cloud Systems 14.6 Protocols for Cloud Security in the Future 14.7 Conclusion References
8 Part IV CASE STUDIES FOCUSED ON CLOUD SECURITY 15 A Study on Google Cloud Platform (GCP) and Its Security 15.1 Introduction 15.2 Google Cloud Platform’s Security Features Basic Overview 15.3 Google Cloud Platform’s Architecture 15.4 Key Security Features 15.5 Key Application Features 15.6 Computation in Google Cloud Platform 15.7 Storage in Google Cloud Platform 15.8 Network in Google Cloud Platform 15.9 Data in Google Cloud Platform 15.10 Machine Learning in Google Cloud Platform 15.11 Conclusion References