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Cloud Security Alliance CCSK Exam Syllabus Topics:

Section	Objectives
Topic 1: Governance, Risk Management, and Compliance	- Cloud governance frameworks and responsibilities - Regulatory and compliance considerations - Risk assessment and management in cloud environments
Topic 2: Cloud Computing Concepts and Architecture	- Cloud reference architecture and service models (IaaS, PaaS, SaaS) - Key cloud characteristics and deployment models
Topic 3: Legal Issues, Contracts, and Electronic Discovery	- Legal jurisdiction and data ownership considerations - Cloud contracts and service level agreements (SLAs)
Topic 4: Cloud Security Architecture and Design	- Identity and access management in cloud environments - Secure cloud architecture principles
Topic 5: Cloud Application Security	- API security and application controls - Secure software development in cloud environments
Topic 6: Cloud Platform and Infrastructure Security	- Container and workload security basics - Network security in cloud environments - Virtualization security
Topic 7: Operations	- Incident response in cloud environments - Logging, monitoring, and auditing - Business continuity and disaster recovery
Topic 8: Data Security and Information Lifecycle Management	- Data retention and secure disposal - Data classification and protection - Encryption and key management

>> CCSK試験問題解説集 <<

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Cloud Security Alliance Certificate of Cloud Security Knowledge v5 (CCSKv5.0) 認定 CCSK 試験問題 (Q11-Q16):

質問 # 11
Cloud Service Provider and Cloud Customer are jointly responsible for ownership of the all risks in shared responsibility model for security across all service models.

A. False
B. True

正解：A

解説：
This is false. This is again a tricky question and one should be careful when answering this type of question. It is the cloud customer is who is ultimately responsible for the ownership of risk in the cloud environment. Consumer just passes some of risk management responsibilities to the cloud service provider.

質問 # 12
In the shared security model, how does the allocation of responsibility vary by service?

A. Responsibilities are divided between the cloud provider and the customer based on the service type.
B. Shared responsibilities should be consistent across all services.
C. Responsibilities are the same across IaaS, PaaS, and SaaS in the shared model.
D. Based on the per-service SLAs for security.

正解：A

解説：
The division of security responsibilities changes according to the service model. In IaaS, CSCs handle more security responsibilities, while in SaaS, the CSP manages more of the security aspects. Reference: [Security Guidance v5, Domain 1 - Shared Responsibility Model]

質問 # 13
How does serverless computing impact infrastructure management responsibility?

A. Shifts more responsibility to cloud service providers
B. Requires extensive on-premises infrastructure
C. Eliminates need for cloud service providers
D. Increases workload for developers

正解：A

解説：
Serverless computing shifts infrastructure management responsibility to the CSP, allowing customers to focus on application logic rather than infrastructure. Reference: [Security Guidance v5, Domain 8 - Cloud Workload Security]

質問 # 14
Which type of AI workload typically requires large data sets and substantial computing resources?

A. Data Preparation
B. Inference
C. Training
D. Evaluation

正解：C

解説：
Among AI workloads,Trainingrequires themost computational power and data resources.
Why AI Training is Computationally Intensive?
Large datasets:
AI models (e.g., deep learning, neural networks)require millions or billions of labeled data points.
Training involvesprocessing massive amounts of structured/unstructured data.
High computational power:
Training deep learning modelsinvolves runningmultiple passes (epochs) over data, adjusting weights, and optimizing parameters.
Requiresspecialized hardwarelikeGPUs (Graphics Processing Units),TPUs (Tensor Processing Units), andHPC (High-Performance Computing).
Long training times:
AI model training can takedays, weeks, or even monthsdepending on complexity.
Cloud platforms offerdistributed computing (multi-GPU training, parallel processing, auto-scaling).
Cloud AI Training Benefits:
Cloud providers (AWS, Azure, GCP) offer ML training serviceswithon-demand scalable compute instances.
Supportsframeworks like TensorFlow, PyTorch, and Scikit-learn.
This aligns with:
CCSK v5 - Security Guidance v4.0, Domain 14 (Related Technologies - AI and ML Security) Cloud AI Security Risks and AI Data Governance (CCM - AI Security Controls)

質問 # 15
CCM: A hypothetical company called: "Health4Sure" is located in the United States and provides cloud based services for tracking patient health. The company is compliant with HIPAA/HITECH Act among other industry standards. Health4Sure decides to assess the overall security of their cloud service against the CCM toolkit so that they will be able to present this document to potential clients. Which of the following approach would be most suitable to assess the overall security posture of Health4Sure's cloud service?

A. The CCM columns are mapped to HIPAA/HITECH Act and therefore Health4Sure could verify the CCM controls already covered ad a result of their compliance with HIPPA/HITECH Act. They could then assess the remaining controls. This approach will save time.
B. The CCM domains are not mapped to HIPAA/HITECH Act. Therefore Health4Sure should assess the security posture of their cloud service against each and every control in the CCM. This approach will allow a thorough assessment of the security posture.
C. The CCM domain controls are mapped to HIPAA/HITECH Act and therefore Health4Sure could verify the CCM controls already covered as a result of their compliance with HIPPA/HITECH Act.
They could then assess the remaining controls thoroughly. This approach saves time while being able to assess the company's overall security posture in an efficient manner.

正解：B

質問 # 16
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