Fortinet FCP_FWB_AD-7.4 Exam Questions - Navigate Your Path to Success

The Fortinet FCP - FortiWeb 7.4 Administrator (FCP_FWB_AD-7.4) exam is a good choice for Fortinet Network Security Engineers Fortinet Cybersecurity Specialists and if the candidate manages to pass Fortinet FCP - FortiWeb 7.4 Administrator exam, he/she will earn Fortinet Certified Professional, Fortinet FCP Fortinet Certified Professional Public Cloud Security Certifications. Below are some essential facts for Fortinet FCP_FWB_AD-7.4 exam candidates:

In actual Fortinet FCP - FortiWeb 7.4 Administrator (FCP_FWB_AD-7.4) exam, a candidate can expect 36 Questions and the officially allowed time is expected to be around 65 Minutes.
TrendyCerts offers 36 Questions that are based on actual Fortinet FCP_FWB_AD-7.4 syllabus.
Our Fortinet FCP_FWB_AD-7.4 Exam Practice Questions were last updated on: Mar 12, 2025

Sample Questions for Fortinet FCP_FWB_AD-7.4 Exam Preparation

Question 1

Refer to the exhibit.

FCP_FWB_AD-7.4 Exam Question 1 Exhibit 1

Which statement is true?

AFortiWeb cannot perform content inspection on the traffic because it is encrypted.

BFortiWeb is decrypting and re-encrypting the traffic.

CThe server is not performing any cryptography on the traffic.

DThe server is encrypting traffic being sent to the client.

Correct : B

In the diagram, FortiWeb is positioned between the client and the server, handling encrypted HTTPS traffic from the client and sending unencrypted HTTP traffic to the server. This indicates that FortiWeb is performing SSL offloading, which means it is decrypting the HTTPS traffic from the client, inspecting it, and then re-encrypting the traffic before forwarding it to the server.

Options Selected by Other Users:

Question 2

How are bot machine learning (ML) models different from API or anomaly detection models?

ABot ML models analyze multiple connections overtime instead analyzing each connection as a single unit.

BBot ML models detect only anomalies and not actual threats.

CBot ML models inspect more types of connection properties.

DBot ML models do not update models periodically from new data.

Correct : A

Bot ML models analyze multiple connections over time instead of analyzing each connection as a single unit: This is the key distinction. Bot ML models focus on analyzing patterns over a period of time, looking at behavioral patterns across multiple requests or connections from the same source to identify potential bot activity. Unlike traditional anomaly detection or API models that may focus on single connections or individual transactions, bot detection typically examines aggregated behavior to identify patterns indicative of bots, such as high-frequency requests or unusual traffic flows.