Public Cloud Security Certified Official Practice Test FCP_FWB_AD-7.4 – Aug-2025
Ace Fortinet FCP_FWB_AD-7.4 Certification with Actual Questions Aug 31, 2025 Updated
Fortinet FCP_FWB_AD-7.4 Exam Syllabus Topics:
| Topic |
Details |
| Topic 1 |
- Encryption, Authentication, and Compliance: This section of the exam assesses the expertise of Security Analysts in mitigating web application vulnerabilities through encryption and authentication mechanisms. Candidates must configure various access control methods, track user authentication, and prevent attacks targeting authentication systems. They must also implement SSL inspection and offloading techniques to enhance security and troubleshoot encryption or authentication-related issues effectively.
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| Topic 2 |
- Web Application Security: This domain evaluates the ability of Cybersecurity Specialists to implement advanced threat mitigation strategies using FortiWeb. Candidates must configure the system to block known attacks, ensure comprehensive web application protection, and troubleshoot threat detection or mitigation-related issues. Additionally, they are expected to set up API protection mechanisms to secure web-based interactions from potential threats.
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| Topic 3 |
- Deployment and Configuration: This section of the exam measures the skills of Network Security Engineers and covers the ability to identify FortiWeb deployment requirements and configure essential system settings. Candidates are expected to set up server pools, security policies, and protected hostnames to ensure seamless deployment. To maintain operational efficiency, they must also configure FortiWeb high availability (HA) for fault tolerance and troubleshoot deployment or system-related issues.
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| Topic 4 |
- Machine Learning (ML): This section tests the skills of Application Security Engineers in leveraging machine learning to enhance web application security. Candidates will configure machine learning algorithms to detect anomalies, mitigate bot-based threats, and secure APIs through AI-driven analysis. Understanding how to fine-tune these ML-based security measures is crucial for ensuring robust application protection against evolving cyber threats.
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