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Cloud Security Alliance CCSK Exam Syllabus Topics:

SectionObjectives
Topic 1: Cloud Computing Concepts & Architectures- Cloud Computing Fundamentals
  • 1. Cloud Architecture
  • 2. Service Models
  • 3. Deployment Models
  • 4. Shared Responsibility Model
Topic 2: Related Technologies & Strategies- Emerging Technologies
  • 1. Security Automation
  • 2. Emerging Cloud Technologies
  • 3. Artificial Intelligence Security
  • 4. Zero Trust
Topic 3: Identity & Access Management- IAM Security
  • 1. Federated Identity
  • 2. Authorization
  • 3. Authentication
  • 4. Privileged Access Management
Topic 4: Application Security- Secure Application Development
  • 1. Secure SDLC
  • 2. Application Testing
  • 3. CI/CD Security
  • 4. API Security
Topic 5: Organization Management- Operational Governance
  • 1. Security Policies
  • 2. Business Continuity
  • 3. Third-Party Management
Topic 6: Cloud Workload Security- Workload Protection
  • 1. Workload Isolation
  • 2. Configuration Security
  • 3. DevSecOps
Topic 7: Security Monitoring- Monitoring & Analytics
  • 1. Threat Detection
  • 2. Cloud Telemetry
  • 3. Logging and SIEM
  • 4. Security Analytics
Topic 8: Risk, Audit & Compliance- Compliance & Legal Requirements
  • 1. Regulatory Compliance
  • 2. Audit Management
  • 3. Risk Assessment
  • 4. Privacy Requirements
Topic 9: Cloud Governance- Governance & Risk Management
  • 1. Cloud Controls Matrix
  • 2. STAR Registry
  • 3. Enterprise Risk Management
  • 4. Policies and Compliance
Topic 10: Infrastructure & Networking- Infrastructure Security
  • 1. Container Security
  • 2. Network Security
  • 3. Virtualization Security
  • 4. Serverless Security
Topic 11: Incident Response & Resilience- Incident Management
  • 1. Resilience Planning
  • 2. Incident Response
  • 3. Disaster Recovery
  • 4. Forensics
Topic 12: Data Security- Data Protection
  • 1. Data Loss Prevention
  • 2. Data Lifecycle
  • 3. Encryption
  • 4. Key Management

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최신 Cloud Security Knowledge CCSK 무료샘플문제 (Q114-Q119):

질문 # 114
Why is it important to control traffic flows between networks in a cybersecurity context?

정답：C

설명：
Controlling traffic flows between networks is critical in a cybersecurity context toreduce the blast radius of attacks. By segmenting networks and implementing controls such as firewalls, organizations can limit the lateral movement of attackers, containing breaches and minimizing their impact.
From theCCSK v5.0 Study Guide, Domain 9 (Network Security), Section 9.2:
"Controlling traffic flows between networks is a fundamental cybersecurity practice to reduce the blast radius of attacks. Network segmentation and micro-segmentation limit an attacker's ability to move laterally within the environment, containing breaches and protecting critical assets."


질문 # 115
An important consideration when performing a remote vulnerability test of a cloud-based application is to

정답：D

설명：
Explanation/Reference:


질문 # 116
An organization deploys an AI application for fraud detection. Which threat is MOST likely to affect its AI model's accuracy?

정답：B

설명：
Correct Option: A. Adversarial attacks
Adversarial attacks are specifically designed to deceive AI and machine learning models by feeding them crafted inputs that result in incorrect outputs. These attacks are highly effective against AI models, especially in areas like fraud detection, where accuracy is critical.
From CSA Security Guidance v4.0 - Domain 13: Security as a Service (SecaaS) and related AI-focused security discussions:
"AI models are vulnerable to adversarial inputs, where attackers introduce subtle perturbations to input data that are imperceptible to humans but cause the AI system to make wrong decisions. These attacks degrade the accuracy and reliability of machine learning models."
- CSA Guidance on AI Security (in Security as a Service domain)
Adversarial ML is a well-recognized field of AI security, where the goal of the attacker is to intentionally corrupt or manipulate input data, thereby lowering the performance or biasing the output of the model.
Why the Other Options Are Incorrect:
* B. DDoS attacks# Affects availability, not accuracy. DDoS can cause downtime but doesn't interfere with model predictions.
* C. Third-party services# May introduce supply chain or dependency risks, but they don't directly impact the AI model's accuracy unless involved in training data pipelines.
* D. Jailbreak attack# More relevant to LLMs (Large Language Models) or chatbots, not structured AI fraud detection models.


질문 # 117
What primary purpose does object storage encryption serve in cloud services?

정답：D

설명：
Encryption in object storage is used to secure stored data and protect it from unauthorized access, ensuring confidentiality. Reference: [Security Guidance v5, Domain 9 - Data Security]


질문 # 118
Which of the following is NOT a characteristic of Object Storage?

정답：C

설명：
Object storage: Similar to a file share accessed via APIs or a web interface. Examples include Amazon S3 and Rackspace cloud files.


질문 # 119
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