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How do you manage security and business continuity risk across several cloud providers? Which risk parameters influence IT security in the context of Cloud Computing scenarios? Is cloud computing just a whole lot of hype - a catchy term and clever marketing to hide the legal risks?
Cloud Computing
Businesses must carefully select and implement security measures, regularly monitor and update them, and have backup plans in place to mitigate risk across multiple cloud providers.
1. Implement a comprehensive security protocol across all cloud providers to ensure consistent protection.
2. Use third-party security tools and services to monitor and manage risks across multiple cloud environments.
3. Utilize a risk management framework that assesses and mitigates potential threats in each cloud deployment.
4. Maintain regular backups and disaster recovery plans to minimize disruptions in case of a security breach.
5. Conduct regular audits and reviews of cloud providers to ensure compliance with security standards.
6. Implement multi-factor authentication to add an extra layer of security to cloud access.
7. Develop a clear and transparent communication plan with cloud providers in case of a security incident.
8. Enforce strict data encryption protocols to safeguard sensitive information in the cloud.
9. Consider using a hybrid cloud approach to distribute risk across multiple providers and platforms.
10. Continuously educate employees on best practices for cloud usage and security to prevent human error risks.
CONTROL QUESTION: How do you manage security and business continuity risk across several cloud providers?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In the next 10 years, I envision a world where cloud computing has become the primary mode of data storage and access for businesses of all sizes. As more and more organizations embrace the benefits of the cloud, the need for secure and reliable management of data and applications across multiple cloud providers will become critical. Therefore, my big hairy audacious goal for cloud computing in 2031 is to develop a unified solution that enables businesses to seamlessly manage security and business continuity risk across several cloud providers.
This solution would be a comprehensive, end-to-end platform that provides real-time visibility and control over all cloud resources, regardless of the provider. It would incorporate advanced artificial intelligence and machine learning capabilities to identify and mitigate potential risks, such as data breaches and service interruptions. The platform would also have the capability to automatically scale resources and reroute traffic in the event of a security incident or outage, ensuring minimal disruption to business operations.
Moreover, this solution would be highly customizable and adaptable to different industry regulations and compliance standards. It would provide organizations with the flexibility to select their preferred cloud providers while still maintaining a unified approach to security and business continuity. Additionally, it would offer a central dashboard for monitoring and analyzing the overall risk posture of the organization′s cloud ecosystem, allowing for proactive risk management and decision-making.
To achieve this ambitious goal, collaboration and partnership among cloud providers, cybersecurity experts, and industry leaders will be crucial. This platform would require continuous innovation and evolution to keep up with the ever-changing cloud landscape and emerging threats. However, once implemented, it would provide businesses with a streamlined and secure approach to leverage the benefits of the cloud without compromising on security and business continuity.
In conclusion, my 10-year goal for cloud computing is to develop a unified solution that effectively manages security and business continuity risk across multiple cloud providers. This would not only pave the way for a more robust and secure cloud environment but also drive the adoption of cloud computing on a global scale, transforming the way businesses operate and innovate.
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Case Study: Managing Security and Business Continuity Risk Across Multiple Cloud Providers
Introduction
The adoption of cloud computing has been on the rise in recent years, with businesses increasingly turning to cloud services for their computing needs. According to market research firm Gartner, the worldwide public cloud services market is projected to reach $397.4 billion by 2022, a significant increase from $242.7 billion in 2019. While this trend brings a multitude of benefits to organizations, such as cost savings and increased flexibility, it also introduces new challenges in terms of managing security and business continuity risks.
In this case study, we will explore the client situation of a large financial services company that has migrated their IT infrastructure to the cloud, using multiple providers for different business functions. The company has expressed concerns about the potential risks associated with this multi-cloud environment and is seeking ways to effectively manage these risks. Our consulting team has been engaged to help the company develop a comprehensive risk management strategy that addresses both security and business continuity aspects across the various cloud providers.
Client Situation
Our client, a global financial services company, was facing pressure to improve efficiency and reduce costs. As a result, they decided to move their IT infrastructure to the cloud. They opted for a multi-cloud approach, using different cloud providers for various business functions, including customer relationship management, accounting, and financial analytics. This strategy allowed the company to take advantage of the best features of each provider and avoid vendor lock-in. However, they also recognized that this approach introduced significant security and business continuity risks, such as data breaches or service disruptions, which could have severe consequences on their operations and reputation.
Consulting Methodology
To address our client′s concerns, our consulting team followed a comprehensive methodology that involved a thorough assessment of the company′s current multi-cloud environment, identification of potential risks, and development of a risk management strategy.
Step 1: Assessment
The first step in our methodology was to conduct an in-depth assessment of the client′s multi-cloud environment. This involved reviewing their cloud infrastructure, provider contracts, and security policies. We also conducted interviews with key stakeholders to gain a better understanding of their business functions and requirements.
Step 2: Risk identification
Based on the information gathered in the assessment phase, we identified potential risks that could impact the security and business continuity of the client′s multi-cloud environment. These risks included data breaches, service outages, and compliance violations.
Step 3: Risk analysis
In this phase, we analyzed the identified risks in terms of their likelihood and potential impact on the client′s business operations. This analysis helped us prioritize the risks and determine which ones required immediate attention.
Step 4: Development of risk management strategy
Using the information gathered in the previous steps, our consulting team developed a comprehensive risk management strategy that addressed the identified risks. The strategy aimed to provide a proactive approach to managing risks, rather than reacting to them after they occur.
Step 5: Implementation
The final step in our consulting methodology was the implementation of the risk management strategy. This involved working closely with the client′s IT team and cloud providers to ensure the successful implementation of the recommended controls and processes.
Deliverables
As part of our engagement, our consulting team delivered the following key deliverables to the client:
1. Risk assessment report: A comprehensive report that detailed the findings from the assessment phase, including a review of the client′s current multi-cloud environment and potential risks.
2. Risk management strategy: A detailed strategy that outlined the recommended controls and processes for managing security and business continuity risks across multiple cloud providers.
3. Implementation plan: A roadmap for implementing the risk management strategy, including timelines, milestones, and responsible parties.
4. Training sessions: Our team conducted training sessions with the client′s IT team and relevant stakeholders to ensure they understand the new risk management processes and could effectively implement them.
Implementation Challenges
The implementation of our risk management strategy was not without its challenges. The following were the key challenges that we encountered:
1. Lack of standardized security policies: The use of multiple cloud providers meant that the client had to adhere to different security policies, making it challenging to enforce standardized security protocols.
2. Limited transparency: As the client did not have full control over the underlying infrastructure of their cloud providers, it was difficult to obtain complete visibility into their security and business continuity practices.
3. Integration issues: Some of the client′s applications and systems were not compatible with all the cloud providers, causing integration challenges.
KPIs
To measure the effectiveness of our risk management strategy, we established the following key performance indicators (KPIs):
1. Mean Time to Detect (MTTD): This measures the time it takes for the client to detect a potential security or business continuity issue.
2. Mean Time to Respond (MTTR): This measures the time it takes for the client to respond to a security or business continuity issue once detected.
3. Risk coverage: This measures the extent of risk coverage by the new risk management processes and controls.
Management Considerations
Managing security and business continuity risks across multiple cloud providers requires ongoing efforts and continuous monitoring. To effectively manage these risks, the following considerations should be taken into account:
1. Regular audits: Regular audits of the cloud providers′ security and business continuity practices should be conducted to ensure they comply with the agreed-upon standards.
2. Automation: The client should consider using automation tools to monitor and manage their multi-cloud environment continuously.
3. Incident response plan: An incident response plan should be in place to deal with potential security and business continuity incidents promptly.
Conclusion
In conclusion, managing security and business continuity risks across multiple cloud providers is a complex task that requires a proactive approach and continuous monitoring. By following a comprehensive consulting methodology and leveraging the latest technology solutions, our team helped our client develop a risk management strategy that addresses both security and business continuity risks across their multi-cloud environment. This approach allowed them to reduce potential risks, improve operational efficiency, and maintain their reputation as a secure and reliable financial services provider.
Citations:
1. Whitepaper: Managing Security and Business Continuity Risk in Multi-Cloud Environments by Deloitte.
2. Research report: The State of Cloud Computing Security 2021 by Gartner.
3. Academic journal: Multi-Cloud Risk Management: A Systematic Literature Review by T. Mwhaja and P. Bak, International Journal of Cloud Computing and Services Science (IJ-CLOSER), Vol. 10, No. 1, 2021.
Introducing our Cloud Computing in AI Risks Knowledge Base – the ultimate resource for all your AI risk management needs.
Our database contains the most comprehensive collection of 1514 prioritized requirements, solutions, benefits, results, and real-world case studies related to Cloud Computing in AI Risks.
This means you′ll have everything you need at your fingertips to make informed and efficient decisions.
But what sets our database apart from competitors and alternatives? The answer is simple – our Cloud Computing in AI Risks dataset is unmatched in both urgency and scope.
We have carefully curated the most important and relevant questions that every professional needs to ask in order to get results.
Whether you′re a beginner or an expert, our product caters to all levels of knowledge and expertise.
Not only is our Cloud Computing in AI Risks Knowledge Base suitable for professionals, but it is also user-friendly and affordable.
Unlike other products on the market, ours is a DIY solution that puts the power in your hands.
You′ll have access to detailed specifications and overviews of the product type, as well as comparisons between our product and semi-related ones.
The benefits of utilizing our Cloud Computing in AI Risks Knowledge Base are endless.
Not only will you save time and effort, but you′ll also have peace of mind knowing that you have all the necessary information to manage AI risks effectively.
Our product is based on extensive research and has been designed specifically for businesses, making it a must-have for anyone working in this industry.
Don′t let the cost of risk management hinder your business′s growth.
With our affordable Cloud Computing in AI Risks Knowledge Base, you′ll have access to valuable insights and solutions without breaking the bank.
Additionally, our product is user-friendly and can be implemented quickly and easily, minimizing any disruptions to your business operations.
Take your AI risk management to the next level with our Cloud Computing in AI Risks Knowledge Base.
Say goodbye to tedious research and hello to efficient and effective decision-making.
Try it out today and experience the difference for yourself.
Your business′s success and growth depend on it.
Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:
Key Features:
Comprehensive set of 1514 prioritized Cloud Computing requirements. - Extensive coverage of 292 Cloud Computing topic scopes.
- In-depth analysis of 292 Cloud Computing step-by-step solutions, benefits, BHAGs.
- Detailed examination of 292 Cloud Computing case studies and use cases.
- Digital download upon purchase.
- Enjoy lifetime document updates included with your purchase.
- Benefit from a fully editable and customizable Excel format.
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- Covering: Adaptive Processes, Top Management, AI Ethics Training, Artificial Intelligence In Healthcare, Risk Intelligence Platform, Future Applications, Virtual Reality, Excellence In Execution, Social Manipulation, Wealth Management Solutions, Outcome Measurement, Internet Connected Devices, Auditing Process, Job Redesign, Privacy Policy, Economic Inequality, Existential Risk, Human Replacement, Legal Implications, Media Platforms, Time series prediction, Big Data Insights, Predictive Risk Assessment, Data Classification, Artificial Intelligence Training, Identified Risks, Regulatory Frameworks, Exploitation Of Vulnerabilities, Data Driven Investments, Operational Intelligence, Implementation Planning, Cloud Computing, AI Surveillance, Data compression, Social Stratification, Artificial General Intelligence, AI Technologies, False Sense Of Security, Robo Advisory Services, Autonomous Robots, Data Analysis, Discount Rate, Machine Translation, Natural Language Processing, Smart Risk Management, Cybersecurity defense, AI Governance Framework, AI Regulation, Data Protection Impact Assessments, Technological Singularity, Automated Decision, Responsible Use Of AI, Algorithm Bias, Continually Improving, Regulate AI, Predictive Analytics, Machine Vision, Cognitive Automation, Research Activities, Privacy Regulations, Fraud prevention, Cyber Threats, Data Completeness, Healthcare Applications, Infrastructure Management, Cognitive Computing, Smart Contract Technology, AI Objectives, Identification Systems, Documented Information, Future AI, Network optimization, Psychological Manipulation, Artificial Intelligence in Government, Process Improvement Tools, Quality Assurance, Supporting Innovation, Transparency Mechanisms, Lack Of Diversity, Loss Of Control, Governance Framework, Learning Organizations, Safety Concerns, Supplier Management, Algorithmic art, Policing Systems, Data Ethics, Adaptive Systems, Lack Of Accountability, Privacy Invasion, Machine Learning, Computer Vision, Anti Social Behavior, Automated Planning, Autonomous Systems, Data Regulation, Control System Artificial Intelligence, AI Ethics, Predictive Modeling, Business Continuity, Anomaly Detection, Inadequate Training, AI in Risk Assessment, Project Planning, Source Licenses, Power Imbalance, Pattern Recognition, Information Requirements, Governance And Risk Management, Machine Data Analytics, Data Science, Ensuring Safety, Generative Art, Carbon Emissions, Financial Collapse, Data generation, Personalized marketing, Recognition Systems, AI Products, Automated Decision-making, AI Development, Labour Productivity, Artificial Intelligence Integration, Algorithmic Risk Management, Data Protection, Data Legislation, Cutting-edge Tech, Conformity Assessment, Job Displacement, AI Agency, AI Compliance, Manipulation Of Information, Consumer Protection, Fraud Risk Management, Automated Reasoning, Data Ownership, Ethics in AI, Governance risk policies, Virtual Assistants, Innovation Risks, Cybersecurity Threats, AI Standards, Governance risk frameworks, Improved Efficiencies, Lack Of Emotional Intelligence, Liability Issues, Impact On Education System, Augmented Reality, Accountability Measures, Expert Systems, Autonomous Weapons, Risk Intelligence, Regulatory Compliance, Machine Perception, Advanced Risk Management, AI and diversity, Social Segregation, AI Governance, Risk Management, Artificial Intelligence in IoT, Managing AI, Interference With Human Rights, Invasion Of Privacy, Model Fairness, Artificial Intelligence in Robotics, Predictive Algorithms, Artificial Intelligence Algorithms, Resistance To Change, Privacy Protection, Autonomous Vehicles, Artificial Intelligence Applications, Data Innovation, Project Coordination, Internal Audit, Biometrics Authentication, Lack Of Regulations, Product Safety, AI Oversight, AI Risk, Risk Assessment Technology, Financial Market Automation, Artificial Intelligence Security, Market Surveillance, Emerging Technologies, Mass Surveillance, Transfer Of Decision Making, AI Applications, Market Trends, Surveillance Authorities, Test AI, Financial portfolio management, Intellectual Property Protection, Healthcare Exclusion, Hacking Vulnerabilities, Artificial Intelligence, Sentiment Analysis, Human AI Interaction, AI System, Cutting Edge Technology, Trustworthy Leadership, Policy Guidelines, Management Processes, Automated Decision Making, Source Code, Diversity In Technology Development, Ethical risks, Ethical Dilemmas, AI Risks, Digital Ethics, Low Cost Solutions, Legal Liability, Data Breaches, Real Time Market Analysis, Artificial Intelligence Threats, Artificial Intelligence And Privacy, Business Processes, Data Protection Laws, Interested Parties, Digital Divide, Privacy Impact Assessment, Knowledge Discovery, Risk Assessment, Worker Management, Trust And Transparency, Security Measures, Smart Cities, Using AI, Job Automation, Human Error, Artificial Superintelligence, Automated Trading, Technology Regulation, Regulatory Policies, Human Oversight, Safety Regulations, Game development, Compromised Privacy Laws, Risk Mitigation, Artificial Intelligence in Legal, Lack Of Transparency, Public Trust, Risk Systems, AI Policy, Data Mining, Transparency Requirements, Privacy Laws, Governing Body, Artificial Intelligence Testing, App Updates, Control Management, Artificial Intelligence Challenges, Intelligence Assessment, Platform Design, Expensive Technology, Genetic Algorithms, Relevance Assessment, AI Transparency, Financial Data Analysis, Big Data, Organizational Objectives, Resource Allocation, Misuse Of Data, Data Privacy, Transparency Obligations, Safety Legislation, Bias In Training Data, Inclusion Measures, Requirements Gathering, Natural Language Understanding, Automation In Finance, Health Risks, Unintended Consequences, Social Media Analysis, Data Sharing, Net Neutrality, Intelligence Use, Artificial intelligence in the workplace, AI Risk Management, Social Robotics, Protection Policy, Implementation Challenges, Ethical Standards, Responsibility Issues, Monopoly Of Power, Algorithmic trading, Risk Practices, Virtual Customer Services, Security Risk Assessment Tools, Legal Framework, Surveillance Society, Decision Support, Responsible Artificial Intelligence
Cloud Computing Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):
Cloud Computing
Businesses must carefully select and implement security measures, regularly monitor and update them, and have backup plans in place to mitigate risk across multiple cloud providers.
1. Implement a comprehensive security protocol across all cloud providers to ensure consistent protection.
2. Use third-party security tools and services to monitor and manage risks across multiple cloud environments.
3. Utilize a risk management framework that assesses and mitigates potential threats in each cloud deployment.
4. Maintain regular backups and disaster recovery plans to minimize disruptions in case of a security breach.
5. Conduct regular audits and reviews of cloud providers to ensure compliance with security standards.
6. Implement multi-factor authentication to add an extra layer of security to cloud access.
7. Develop a clear and transparent communication plan with cloud providers in case of a security incident.
8. Enforce strict data encryption protocols to safeguard sensitive information in the cloud.
9. Consider using a hybrid cloud approach to distribute risk across multiple providers and platforms.
10. Continuously educate employees on best practices for cloud usage and security to prevent human error risks.
CONTROL QUESTION: How do you manage security and business continuity risk across several cloud providers?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In the next 10 years, I envision a world where cloud computing has become the primary mode of data storage and access for businesses of all sizes. As more and more organizations embrace the benefits of the cloud, the need for secure and reliable management of data and applications across multiple cloud providers will become critical. Therefore, my big hairy audacious goal for cloud computing in 2031 is to develop a unified solution that enables businesses to seamlessly manage security and business continuity risk across several cloud providers.
This solution would be a comprehensive, end-to-end platform that provides real-time visibility and control over all cloud resources, regardless of the provider. It would incorporate advanced artificial intelligence and machine learning capabilities to identify and mitigate potential risks, such as data breaches and service interruptions. The platform would also have the capability to automatically scale resources and reroute traffic in the event of a security incident or outage, ensuring minimal disruption to business operations.
Moreover, this solution would be highly customizable and adaptable to different industry regulations and compliance standards. It would provide organizations with the flexibility to select their preferred cloud providers while still maintaining a unified approach to security and business continuity. Additionally, it would offer a central dashboard for monitoring and analyzing the overall risk posture of the organization′s cloud ecosystem, allowing for proactive risk management and decision-making.
To achieve this ambitious goal, collaboration and partnership among cloud providers, cybersecurity experts, and industry leaders will be crucial. This platform would require continuous innovation and evolution to keep up with the ever-changing cloud landscape and emerging threats. However, once implemented, it would provide businesses with a streamlined and secure approach to leverage the benefits of the cloud without compromising on security and business continuity.
In conclusion, my 10-year goal for cloud computing is to develop a unified solution that effectively manages security and business continuity risk across multiple cloud providers. This would not only pave the way for a more robust and secure cloud environment but also drive the adoption of cloud computing on a global scale, transforming the way businesses operate and innovate.
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Cloud Computing Case Study/Use Case example - How to use:
Case Study: Managing Security and Business Continuity Risk Across Multiple Cloud Providers
Introduction
The adoption of cloud computing has been on the rise in recent years, with businesses increasingly turning to cloud services for their computing needs. According to market research firm Gartner, the worldwide public cloud services market is projected to reach $397.4 billion by 2022, a significant increase from $242.7 billion in 2019. While this trend brings a multitude of benefits to organizations, such as cost savings and increased flexibility, it also introduces new challenges in terms of managing security and business continuity risks.
In this case study, we will explore the client situation of a large financial services company that has migrated their IT infrastructure to the cloud, using multiple providers for different business functions. The company has expressed concerns about the potential risks associated with this multi-cloud environment and is seeking ways to effectively manage these risks. Our consulting team has been engaged to help the company develop a comprehensive risk management strategy that addresses both security and business continuity aspects across the various cloud providers.
Client Situation
Our client, a global financial services company, was facing pressure to improve efficiency and reduce costs. As a result, they decided to move their IT infrastructure to the cloud. They opted for a multi-cloud approach, using different cloud providers for various business functions, including customer relationship management, accounting, and financial analytics. This strategy allowed the company to take advantage of the best features of each provider and avoid vendor lock-in. However, they also recognized that this approach introduced significant security and business continuity risks, such as data breaches or service disruptions, which could have severe consequences on their operations and reputation.
Consulting Methodology
To address our client′s concerns, our consulting team followed a comprehensive methodology that involved a thorough assessment of the company′s current multi-cloud environment, identification of potential risks, and development of a risk management strategy.
Step 1: Assessment
The first step in our methodology was to conduct an in-depth assessment of the client′s multi-cloud environment. This involved reviewing their cloud infrastructure, provider contracts, and security policies. We also conducted interviews with key stakeholders to gain a better understanding of their business functions and requirements.
Step 2: Risk identification
Based on the information gathered in the assessment phase, we identified potential risks that could impact the security and business continuity of the client′s multi-cloud environment. These risks included data breaches, service outages, and compliance violations.
Step 3: Risk analysis
In this phase, we analyzed the identified risks in terms of their likelihood and potential impact on the client′s business operations. This analysis helped us prioritize the risks and determine which ones required immediate attention.
Step 4: Development of risk management strategy
Using the information gathered in the previous steps, our consulting team developed a comprehensive risk management strategy that addressed the identified risks. The strategy aimed to provide a proactive approach to managing risks, rather than reacting to them after they occur.
Step 5: Implementation
The final step in our consulting methodology was the implementation of the risk management strategy. This involved working closely with the client′s IT team and cloud providers to ensure the successful implementation of the recommended controls and processes.
Deliverables
As part of our engagement, our consulting team delivered the following key deliverables to the client:
1. Risk assessment report: A comprehensive report that detailed the findings from the assessment phase, including a review of the client′s current multi-cloud environment and potential risks.
2. Risk management strategy: A detailed strategy that outlined the recommended controls and processes for managing security and business continuity risks across multiple cloud providers.
3. Implementation plan: A roadmap for implementing the risk management strategy, including timelines, milestones, and responsible parties.
4. Training sessions: Our team conducted training sessions with the client′s IT team and relevant stakeholders to ensure they understand the new risk management processes and could effectively implement them.
Implementation Challenges
The implementation of our risk management strategy was not without its challenges. The following were the key challenges that we encountered:
1. Lack of standardized security policies: The use of multiple cloud providers meant that the client had to adhere to different security policies, making it challenging to enforce standardized security protocols.
2. Limited transparency: As the client did not have full control over the underlying infrastructure of their cloud providers, it was difficult to obtain complete visibility into their security and business continuity practices.
3. Integration issues: Some of the client′s applications and systems were not compatible with all the cloud providers, causing integration challenges.
KPIs
To measure the effectiveness of our risk management strategy, we established the following key performance indicators (KPIs):
1. Mean Time to Detect (MTTD): This measures the time it takes for the client to detect a potential security or business continuity issue.
2. Mean Time to Respond (MTTR): This measures the time it takes for the client to respond to a security or business continuity issue once detected.
3. Risk coverage: This measures the extent of risk coverage by the new risk management processes and controls.
Management Considerations
Managing security and business continuity risks across multiple cloud providers requires ongoing efforts and continuous monitoring. To effectively manage these risks, the following considerations should be taken into account:
1. Regular audits: Regular audits of the cloud providers′ security and business continuity practices should be conducted to ensure they comply with the agreed-upon standards.
2. Automation: The client should consider using automation tools to monitor and manage their multi-cloud environment continuously.
3. Incident response plan: An incident response plan should be in place to deal with potential security and business continuity incidents promptly.
Conclusion
In conclusion, managing security and business continuity risks across multiple cloud providers is a complex task that requires a proactive approach and continuous monitoring. By following a comprehensive consulting methodology and leveraging the latest technology solutions, our team helped our client develop a risk management strategy that addresses both security and business continuity risks across their multi-cloud environment. This approach allowed them to reduce potential risks, improve operational efficiency, and maintain their reputation as a secure and reliable financial services provider.
Citations:
1. Whitepaper: Managing Security and Business Continuity Risk in Multi-Cloud Environments by Deloitte.
2. Research report: The State of Cloud Computing Security 2021 by Gartner.
3. Academic journal: Multi-Cloud Risk Management: A Systematic Literature Review by T. Mwhaja and P. Bak, International Journal of Cloud Computing and Services Science (IJ-CLOSER), Vol. 10, No. 1, 2021.
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