Cloud Security: Techniques and Applications
- Length: 212 pages
- Edition: 1
- Language: English
- Publisher: de Gruyter
- Publication Date: 2021-07-20
- ISBN-10: 3110737507
- ISBN-13: 9783110737509
- Sales Rank: #0 (See Top 100 Books)
The book series “Smart Computing Applications” provides a platform for researchers, academicians and practitioners to exchange ideas on recent theoretical and applied data science and computing technologies research, with a particular attention to the possible applications of such technologies in the industry, especially in the field of mechanical and industrial engineering.
This series serves as a valuable resource for graduate, postgraduate, doctoral students, researchers, academicians and industry professionals.
Title Page Copyright Contents Preface Acknowledgement List of Abbreviations List of Contributors Cloud Security Concepts, Threats and Solutions: Artificial Intelligence Based Approach 1 Introduction 2 Literature Analysis 2.1 Significance of artificial intelligence 2.2 Security issues 2.3 Privacy issues 2.4 Security and privacy enhancement using artificial intelligence 3 Security 4 Privacy 5 Security and Privacy Solutions Using Artificial Intelligence 6 Proposed Solutions or Approaches 6.1 Research method 6.2 Research design 6.3 Data collection 6.4 Data analysis 7 Model/ Data Theft Security Technology 7.1 Private separation of teacher ensembles (PATE) 7.2 Unique privacy protection 7.3 Model watermarking 8 Why is AI Technology Essential for Cybersecurity? 9 Results 10 Conclusion 11 References Addressing Security and Privacy in Cloud Computing: Blockchain as a Service 1 Introduction 2 Literature Survey 3 Cloud Computing Concepts 4 Consensus Mechanisms 5 Blockchain Technology Concepts 5.1 Consensus mechanisms 5.2 Structure of blockchain 5.3 Workflow of blockchain 5.4 Features of blockchain 5.5 Potential attacks on blockchain 6 Cloud Security Concerns 7 Blockchain to the Rescue 7.1 Encryption 7.2 Cost management 7.3 Lack of resources 7.4 Governance or control of data 7.5 Managing multiple clouds or servers 7.6 Building a private cloud 7.7 Limited features 7.8 Reliable internet connection 8 Conclusion 9 References Security and Privacy Preservation Model to Mitigate DDoS Attacks in Cloud 1 Introduction 2 Literature Analysis 3 Classification of DDoS Attacks 3.1 Various types of external and internal attacks 3.2 Classifications of DDoS attacks 3.3 Current popular DDoS attacks 3.4 Factors effecting severity of DDoS attacks 4 DDoS Mitigation Techniques 4.1 Reducing attack surface 4.2 CDN’s 4.3 Black hole routing 5 Stages of DDoS Mitigation 5.1 Detection 5.2 Response 5.3 Routing 5.4 Adaption 6 Privacy in DDoS Attacks 7 Summary of Our Contributions Using KNN 8 Summary of DDoS Attacks Detection Methods 8.1 Conventional network entropy 8.2 SDNs 9 Privacy Preserving in Cross-Domain Detection 10 Models 10.1 System model/approaches and threat model 11 Security in Different Cloud Computing Service Models 12 Security in Different Cloud Deployment Models 13 Vulnerabilities in Cloud 13.1 Threats 14 Security Issues 14.1 Security issues layer-wise 15 Proposed Solutions in Literature 15.1 Data confidentiality schemes 15.2 Cloud virtualization confidentiality schemes 15.3 Cloud data integrity schemes 15.4 Integrity schemes in cloud virtualization 16 Onion Encryption (OE) 17 Conclusion 18 References A Secure Cloud Infrastructure towards Smart Healthcare: IoT Based Health Monitoring 1 Introduction 2 Cloud Deployment Models in Healthcare 2.1 Public cloud 2.2 Private cloud 2.3 Community cloud 2.4 Hybrid cloud 3 Cloud Service Models in Healthcare 3.1 Software as a service (SaaS) 3.2 Platform as a service (PaaS) 3.3 Infrastructure as a service (IaaS) 4 Factors to be Considered for the Evaluation of the Cloud System Security 4.1 Confidentiality 4.2 Integrity 4.3 Availability 5 Review of Literature 6 Recommendations for Smart Healthcare Model 7 Types of Cloud Architectures 7.1 Centralized 7.2 Federated 7.3 P2P cloud 8 P2P Architecture 9 Security & Privacy 10 Privacy Requirements and Issues in Healthcare as a Service 10.1 Privacy of the hospitals’ datasets 10.2 Privacy of the hospitals’ votes 10.3 Privacy of the patients’ diagnosed symptoms 11 Cloud Services to Preserve Data Security in Healthcare 12 Real Time Healthcare Dashboard- A Case Study Based on Blood Pressure Readings 13 Conclusion 14 References Internet of Cloud: Secure and Privacy Preserving Cloud Model with IoT Enabled Service 1 Introduction 2 Review of Literature 3 IoT Security and Privacy Issues 3.1 Safety 3.2 Secret 3.3 Cooperation 4 The Future of IoT 5 Generic IoT Layers and Data Integration Model 6 Security and Privacy Policies 7 Implementation of the Recommended Cloud-Edge-IoT Model 8 Discussion and Analysis 8.1 Key points of proposed model 9 Conclusion 10 References Marketing analytics as a Service: Secure Cloud Based Automation Strategy 1 Introduction 2 Cloud Governance through Marketing Automation: To Meet Business Desires 3 Significant Factors Ensuring Security in Cloud Based Marketing Automation Process 3.1 Access security 3.2 Data security 3.3 Platform security 4 Automation of Marketing Life Cycle Through Cloud Based Secure Marketing Solution 4.1 Reach 4.2 Act 4.3 Convert 4.4 Engage 5 Various Cloud Based Secure Marketing Solutions 5.1 Adzooma software 5.2 Bitrix24 software 5.3 WebEngage software 5.4 BetterMetrics software 5.5 EngageBay software 5.6 Agile CRM software 5.7 Sender software 5.8 SendX software 5.9 InTouch software 5.10 SendinBlue 5.11 Freshworks CRM software 5.12 Routee software 5.13 Zoho CRM software 5.14 Omnisend software 5.15 AiHello software 5.16 Mailchimp software 5.17 HubSpot Marketing Hub software 5.18 Constant Contact software 5.19 Wrike software 5.20 Semrush software 6 Results and Discussion 7 Conclusion 8 References Next Generation Cloud Security: State of the Art Machine Learning Model 1 Introduction 1.1 Cloud computing 1.2 Machine learning 1.3 Advantages of machine learning systems on the cloud 1.4 Limitations of machine learning systems on cloud 1.5 Literature survey 2 Machine Learning Based Cloud Solutions to Address Research Issues and Challenges 2.1 Privacy and security aware safety measures 2.2 Performance and its measurement 2.3 Attentive solutions through reliability and availability 2.4 Accustomed solutions through scalability and elasticity 2.5 Adaptive solution through interoperability and portability 2.6 QoS driven resource management and scheduling 2.7 Efficient energy consumption infrastructure 2.8 Able distributed computing with virtualization 2.9 Cost sensitive infrastructure with better throughput 3 Machine Learning Based Cloud Models- Google Cloud Machine Learning Engine: A Case Study 3.1 Google cloud platform introduction 3.2 Various types of services 3.3 How to use google cloud machine learning? 3.4 Tools to interact with artificial intelligence platform 3.5 Advantages of machine learning based google services 3.6 Statistical facts about machine learning 4 Commercial Web Based Clouds based on Machine Learning 4.1 Cloud shell 4.2 Various tools available in cloud shell 4.3 Amazon Web Services 4.4 IBM Cloud 5 State of the art Machine learning algorithms for cloud security 6 Conclusion 7 References Secure Intelligent Framework for VANET: Cloud Based Transportation Model 1 Introduction to VANET 2 Constraints of Cloud 3 Applications of VANET 3.1 Safety applications 3.2 Convenience applications 3.3 Commercial applications 4 VANET- Cloud Based Approach 4.1 VANETs within the cloud 4.2 Vehicular cloud 4.3 Private vehicular cloud 5 Autonomous/Self-Governing Vehicle 6 Vehicle Platoon/Swarm 7 Applications of Vehicular Cloud Computing 7.1 Parking lot data or information based cloud 7.2 Dynamic and self-motivated traffic light management 7.3 Optimizing and enhancing traffic signals 7.4 Road safety communication and message 7.5 VC in developing countries 7.6 Managing parking facilities 8 Characteristics of VANET 8.1 High mobility 8.2 Driver safety 8.3 Dynamic network topology 8.4 Frequent network disconnection 8.5 No power constraints 8.6 Network strength 8.7 Large computational processing 9 Security Services of VANET 9.1 Availability of the service 9.2 Confidentiality of the service 9.3 Authentication of the service 9.4 Data Integrity of the service 9.5 Nonrepudiation of the service 10 Threats and Attacks of VANETs 10.1 Attack on communication 10.2 Attack on safety applications 10.3 Attack on infotainment applications 11 Security and Privacy Related Issues in VANET 11.1 Pseudonyms coupled with PKI-based schemes 11.2 Trust based schemes 11.3 Group signatures 12 Security and Privacy in VCC 12.1 Security services of vehicular cloud computing 12.2 Threats of vehicular cloud computing 12.3 Privacy challenges of vehicular cloud computing 13 Solutions to Security Issues 14 Conclusion 15 References Cloud Manufacturing Service: A Secure and Protected Communication System 1 Introduction 2 Manufacturing Cloud Provision Models 3 Manufacturing Cloud Organization Models 4 Cloud Manufacturing Paradigms 5 Benefits of Cloud Manufacturing 5.1 Scalability 5.2 Increased uptime 5.3 Standardization 5.4 Faster implementation 5.5 Agility 6 Security and Privacy Aspects of Cloud Manufacturing 6.1 Security challenges in cloud manufacturing 6.2 Significant factors effecting security in cloud system 7 Comparison of Traditional/Conventional Manufacturing and Cloud Manufacturing 8 Secure Cloud Manufacturing Models 9 Cloud manufacturing Life Cycle: An Efficient Integrated Approach 10 Proposed Secured Cloud Manufacturing Model Architecture 11 Conclusion 12 References Index
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