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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Governance | 9% | - Policies and procedures - Strategic alignment - Cloud service provider management - Governance frameworks |
| Topic 2: Cloud Computing Concepts & Architectures | 8% | - Cloud reference architecture - Shared responsibility model - Cloud deployment models - Cloud service models |
| Topic 3: Incident Response & Resilience | 7% | - Incident response planning - Recovery and remediation - Business continuity and disaster recovery - Detection and containment |
| Topic 4: Infrastructure & Networking | 9% | - Virtualization security - Segmentation and isolation - Cloud native networking security - Network security architecture |
| Topic 5: Cloud Workload Security | 9% | - Virtual machine security - Workload protection strategies - Serverless security - Container and orchestration security |
| Topic 6: Identity & Access Management | 10% | - Authentication and authorization - Identity lifecycle management - Federated identity and SSO - Access control models |
| Topic 7: Risk, Audit, & Compliance | 10% | - Risk assessment and management - Third-party risk management - Audit processes and controls - Compliance frameworks and regulations |
| Topic 8: Application Security | 7% | - Secure software development lifecycle - DevSecOps practices - Cloud application architecture - API security |
| Topic 9: Security Monitoring | 8% | - Threat detection and analysis - Continuous monitoring - Alerting and response workflows - Logging and event management |
| Topic 10: Data Security | 10% | - Data classification and governance - Data lifecycle management - Encryption and key management - Data residency and privacy |
| Topic 11: Organization Management | 7% | - Tenancy and resource management - Security culture and awareness - Cloud security strategy - Roles and responsibilities |
| Topic 12: Related Technologies & Strategies | 6% | - Artificial Intelligence and Generative AI security - Emerging technologies and risks - Zero Trust architecture |
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NEW QUESTION # 118
The most pragmatic option for data disposal in the cloud is which of the following?
Answer: D
NEW QUESTION # 119
Which plane in a network architecture is responsible for controlling all administrative actions?
Answer: B
Explanation:
TheManagement planein a network architecture is responsible for controlling all administrative actions, including configuration, management, monitoring, and maintenance of network devices and services. It provides the interface for administrators to interact with the network, perform system management tasks, and enforce policies.
The management plane typically includes functions such as:
Configuration management
Monitoring and logging
Administrative access control
Policy enforcement
In the context of cloud environments, the management plane also includes APIs and web-based consoles that allow administrators to manage virtual resources. Due to its critical role in controlling network and system settings, securing the management plane is of utmost importance to prevent unauthorized access and potential control over the entire network infrastructure.
NEW QUESTION # 120
When creating business strategies for cloud migration. which is the most important aspect?
Answer: D
Explanation:
Due Diligence is most important aspect when considering adoption to the cloud
NEW QUESTION # 121
Which type of AI workload typically requires large data sets and substantial computing resources?
Answer: D
Explanation:
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)
NEW QUESTION # 122
What is a primary benefit of implementing micro-segmentation within a Zero Trust Architecture?
Answer: D
Explanation:
The primary benefit of implementing micro-segmentation within a Zero Trust Architecture is that it enhances security by isolating workloads from each other. Micro-segmentation involves dividing the network into smaller, isolated segments, so that even if an attacker gains access to one part of the network, they cannot easily move laterally to other parts. This is crucial in a Zero Trust model, which assumes that threats may exist both inside and outside the network, and security is enforced at a granular level for each workload.
NEW QUESTION # 123
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