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The CCSK Certification Exam is based on the Cloud Security Alliance's Guidance for Critical Areas of Focus in Cloud Computing, which is widely recognized as the industry standard for cloud security best practices. CCSK exam consists of 60 multiple-choice questions that must be completed within 90 minutes. The questions are designed to test the candidate's understanding of cloud security concepts, principles, and best practices.
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CCSK certification is a valuable credential for professionals who work with cloud-based technologies. It demonstrates a candidate's understanding of cloud security concepts and best practices, and can help them stand out in a competitive job market. Additionally, the CCSK Certification is recognized globally and can be a requirement for certain cloud-related job roles.
NEW QUESTION # 299
According to NIST, what is cloud computing defined as?
Answer: C
Explanation:
NIST defines cloud computing as on-demand network access to a shared pool of configurable resources, aligning with the essential characteristics of cloud services. Reference: [Security Guidance v5, Domain 1 - Cloud Computing Models]
NEW QUESTION # 300
How does running applications on distinct virtual networks and only connecting networks as needed help?
Answer: A
NEW QUESTION # 301
In the context of server-side encryption handled by cloud providers, what is the key attribute of this encryption?
Answer: A
Explanation:
In the context of server-side encryption handled by cloud providers, the data is encrypted after transmission to the cloud using either provider-managed keys or customer-managed keys. The cloud provider takes responsibility for encrypting the data when it is stored in the cloud, ensuring that the data at rest is protected.
Server-side encryption typically uses symmetric encryption for performance reasons, but this attribute is not what defines the encryption process. Also, server-side encryption focuses on protecting data once it's in the cloud, not before transmission. Encryption in transit is typically handled separately from server-side encryption and applies to data as it moves between the client and the cloud.
NEW QUESTION # 302
What is the primary function of a Load Balancer Service in a Software Defined Network (SDN) environment?
Answer: C
Explanation:
The correct answer isC. To distribute incoming network traffic across multiple destinations.
ALoad Balancer Servicein anSDN environmentis responsible forefficiently distributing network trafficacross multiple servers or instances. This ensures high availability, reliability, and optimized resource usage.
Key Functions:
Traffic Distribution:Balances incoming requests to various servers based on predefined algorithms (round-robin, least connections, etc.).
High Availability:Prevents server overload and reduces downtime by distributing workload.
Scalability:Automatically adjusts as the number of requests or available resources changes.
Health Monitoring:Continually checks server availability and responsiveness to avoid directing traffic to non-responsive instances.
Why Other Options Are Incorrect:
A . Isolated virtual networks:Creating isolated networks is a function of network virtualization, not load balancing.
B . Monitor network performance:Monitoring is done by network monitoring tools, not load balancers.
D . Encrypt data for secure transmission:Encryption is handled by security protocols like TLS/SSL, not load balancers.
Real-World Example:
Services likeAWS Elastic Load Balancer (ELB)andAzure Load Balancerensure that traffic is distributed efficiently across instances, maintaining performance and uptime.
Reference:
CSA Security Guidance v4.0, Domain 7: Infrastructure Security
Cloud Computing Security Risk Assessment (ENISA) - SDN and Load Balancing Cloud Controls Matrix (CCM) v3.0.1 - Network and Infrastructure Domains
NEW QUESTION # 303
Which aspect of cybersecurity can AI enhance by reducing false positive alerts?
Answer: D
Explanation:
AI can enhance anomaly detection in cybersecurity by analyzing large volumes of data and identifying patterns that deviate from normal behavior. By using machine learning algorithms, AI can improve the accuracy of anomaly detection, reducing false positive alerts. This helps security teams focus on genuine threats while minimizing distractions from irrelevant alerts.
NEW QUESTION # 304
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