CCSK Exam Dumps - Certificate of Cloud Security Knowledge v5 (CCSKv5.0)

The key characteristic that differentiates cloud networks from traditional networks is that cloud networks are often software-defined networks (SDNs). This means that network management, configuration, and provisioning in the cloud are handled through software, rather than relying on traditional hardware-based network components. SDNs allow for greater flexibility, scalability, and automation, enabling cloud providers to dynamically adjust resources to meet changing demands.

The key outcomes of implementing robust cloud risk management practices focus on ensuring the security and resilience of cloud environments. This involves identifying, assessing, and mitigating risks associated with the use of cloud services, such as security threats, data privacy issues, and service availability concerns. By adopting strong risk management practices, organizations can better protect their data, ensure business continuity, and maintain compliance with regulations, which ultimately strengthens the overall security and reliability of their cloud environments.

Negotiating shared responsibilities is an important aspect of cloud security but is not the direct outcome of risk management practices. It's about clarifying roles between the customer and provider. Transferring compliance to the cloud service provider via inheritance is not the complete picture. While cloud service providers may help with compliance, the responsibility for compliance and risk management is still shared. Reducing the need for compliance withregulatory requirements is incorrect. Robust risk management practices help ensure compliance with regulatory requirements, not reduce the need for them.

One of the biggest challenges incloud security risk assessmentisthe lack of transparencyregardingcloud provider operations and security controls.

Key Issues with Limited Visibility:

Cloud providers manage infrastructure at a global scale:

Customerscannot directly inspectsecurity implementations.

Rely onthird-party attestationslikeSOC 2, ISO 27001, CSA STARinstead of direct assessments.

Multi-tenancy complexities:

Cloud customersshare infrastructurewith other tenants.

Data isolation mechanisms (e.g., virtual private clouds, encryption)must be trustedwithout direct verification.

Regulatory compliance challenges:

Organizations handling sensitive data (e.g., healthcare, finance)requirestrict controls.

Cloud providers may not offer sufficient audit logsor control overdata residency and processing.

Incident response limitations:

In traditional IT, organizations controllog access, forensic analysis, and recovery.

In the cloud,incident investigation depends on the provider’s logging and notification practices.

Thisvisibility issueis extensively covered in:

CCSK v5 - Security Guidance v4.0, Domain 4 (Compliance and Audit Management)

ENISA’s Cloud Computing Risk Assessment (Limited visibility into cloud provider security policies)​

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.

Assisting analysts is a valid benefit of AI, but reducing false positives directly improves anomaly detection capabilities. Threat intelligence refers to gathering and analyzing information about potential threats but isn't directly focused on reducing false positives in the same way as anomaly detection. Automated responses can be part of AI's role in cybersecurity, but reducing false positives is more directly related to improving anomaly detection.

An SDP creates a "dark" network, visible only to authorized users, enhancing security by hiding infrastructure from potential attackers. Reference: [Security Guidance v5, Domain 7 - Infrastructure & Networking]

DevOps aims to improve collaboration and integration between development and operations teams, streamlining delivery and enhancing software quality. Reference: [CCSK Study Guide, Domain 10 - DevOps & DevSecOps]