Pass the Cloud Security Alliance Cloud Security Knowledge CCSK Questions and answers with Dumpstech

The shift-left approach in software development refers to integrating security measures early in the development process, rather than waiting until later stages (such as post-deployment) to address security issues. By shifting security "left" in the software development lifecycle, teams can identify and address potential vulnerabilities and risks early, reducing costs and improving the overall security of the application.

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.

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]

Governance in cybersecurity is crucial because it provides the framework to ensure that security risks are adequately managed while still allowing the organization to adopt new technologies and innovations at a reasonable pace. Effective governance helps organizations balance the need for security controls with the need for agility and speed in adopting new solutions. It ensures that risks are identified, assessed, and mitigated without unnecessarily slowing down progress or stifling innovation.

Without governance, there is a risk that security concerns may be overlooked, or too many restrictions might be placed on adoption, leading to delays or failure to innovate. Proper governance strikes the right balance between security and agility.

Artificial Intelligence (AI), including Large Language Models (LLMs), is significantly impacting IT and security by enablingautomation of threat detection and response. AI-driven tools can analyze vast amounts of data in real-time, identify patterns indicative of threats, and respond faster than human operators, improving security operations efficiency and effectiveness.

From theCCSK v5.0 Study Guide, Domain 12 (Emerging Technologies), Section 12.4:

“AI and machine learning, including Large Language Models, are transforming cloud security by automating threat detection and response. These technologies can process and analyze security logs, network traffic, and user behavior to identify anomalies and potential threats, enabling rapid incident response and reducing the burden on security teams.”

Option C (Automating threat detection and response) is the correct answer.

Option A (Eliminating the need for encryption) is incorrect because AI does not eliminate the need for encryption; encryption remains a fundamental security control.

Option B (Replacing all IT personnel) is incorrect because AI augments, rather than replaces, IT and security personnel.

Option D (Standardizing software development languages) is incorrect because AI does not primarily focus on standardizing development languages.