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FCP_FWB_AD-7.4 · Question #52

Which two statements accurately describe the FortiWeb machine learning (ML) feature? (Choose two.)

The correct answer is C. ML results in fewer false-positives. D. FortiWeb uses the second layer of ML to identify whether an attack is real. ML results in fewer false-positives because FortiWeb's machine learning feature builds a baseline of normal behavior and intelligently distinguishes legitimate traffic from threats. FortiWeb uses the second layer of ML to identify whether an attack is real, providing deeper…

Advanced Web Protection

Question

Which two statements accurately describe the FortiWeb machine learning (ML) feature? (Choose two.)

Options

  • AThe first layer of ML flags and inspects detected anomalies.
  • BML inspects ail fields and all content of web traffic.
  • CML results in fewer false-positives.
  • DFortiWeb uses the second layer of ML to identify whether an attack is real.

How the community answered

(33 responses)
  • A
    9% (3)
  • B
    15% (5)
  • C
    76% (25)

Explanation

ML results in fewer false-positives because FortiWeb's machine learning feature builds a baseline of normal behavior and intelligently distinguishes legitimate traffic from threats. FortiWeb uses the second layer of ML to identify whether an attack is real, providing deeper analysis after the initial anomaly detection to further reduce false alarms and improve accuracy.

Topics

#machine learning#anomaly detection#false positives#threat analytics

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