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| Section | Objectives |
|---|---|
| Cloud Application Security | - Secure software development in cloud environments - API security and application controls |
| Operations | - Incident response in cloud environments - Logging, monitoring, and auditing - Business continuity and disaster recovery |
| Cloud Platform and Infrastructure Security | - Container and workload security basics - Virtualization security - Network security in cloud environments |
| Legal Issues, Contracts, and Electronic Discovery | - Legal jurisdiction and data ownership considerations - Cloud contracts and service level agreements (SLAs) |
| Cloud Security Architecture and Design | - Secure cloud architecture principles - Identity and access management in cloud environments |
| Data Security and Information Lifecycle Management | - Data retention and secure disposal - Data classification and protection - Encryption and key management |
| Governance, Risk Management, and Compliance | - Regulatory and compliance considerations - Cloud governance frameworks and responsibilities - Risk assessment and management in cloud environments |
| Cloud Computing Concepts and Architecture | - Cloud reference architecture and service models (IaaS, PaaS, SaaS) - Key cloud characteristics and deployment models |
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NEW QUESTION # 26
What process involves an independent examination of records, operations, processes, and controls within an organization to ensure compliance with cybersecurity policies, standards, and regulations?
Answer: B
Explanation:
Auditing is an independent review process that validates adherence to policies, regulations, and standards. It is essential in assessing security posture.
NEW QUESTION # 27
Cloud Security provider is responsible for Platform Security in Platform as a Service(PaaS) model.
Answer: A
Explanation:
It is false. Platform security is a shared responsibility between cloud service provider and cloud service customer in Platform as a Service(PaaS) model.
NEW QUESTION # 28
An adversary uses a cloud Platform to launch a DDoS attack against XYZ company. This type of risk is termed as:
Answer: A
Explanation:
Malicious actors may leverage cloud computing resources to target users, Organizations or other cloud providers. Examples of misuse of cloud service-based resources include launching DDoS attacks, email spam and phishing campaigns; "mining" for digital currency; large-scale automated click fraud; brute- force compute attacks of stolen credential databases; and hosting of malicious or pirated content.
NEW QUESTION # 29
Which of the following cloud essential characteristics refers to the capability of the service to scale resources up or down quickly and efficiently based on demand?
Answer: B
Explanation:
Rapid Elasticity refers to the capability of cloud services to scale resources up or down quickly and efficiently in response to varying demand. This characteristic allows cloud environments to dynamically adjust resource allocation (such as computing power, storage, or bandwidth) to meet the needs of users, ensuring that resources are available when required and minimizing waste when demand decreases. This ability is a key advantage of cloud computing, providing flexibility and cost efficiency for businesses.
NEW QUESTION # 30
An organization deploys an AI application for fraud detection. Which threat is MOST likely to affect its AI model's accuracy?
Answer: B
Explanation:
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.
NEW QUESTION # 31
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