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200-201 Practice Question: Which TWO of the following are characteristics of…
Which TWO of the following are characteristics of behavioral-based anomaly detection in network monitoring? (Select 2)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Establishes a baseline of normal traffic
Correct: A (establishes baseline) and E (detects zero-day attacks). Behavioral-based anomaly detection learns normal traffic patterns and flags deviations, making it effective against unknown attacks. B is incorrect because it describes signature-based detection. C is incorrect because while behavioral detection can analyze encrypted traffic metadata without decryption, it is not a defining characteristic; the main focus is on baseline deviations. D is incorrect because static rules are characteristic of rule-based detection, not behavioral.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Establishes a baseline of normal traffic
Why this is correct
Behavioral analysis uses baselines to find deviations.
- ✗
Relies on predefined signatures
Why it's wrong here
Signatures are used in signature-based detection, not behavioral.
- ✗
Can inspect encrypted traffic without decryption
Why it's wrong here
Behavioral analysis can work with metadata but cannot inspect payload.
- ✗
Uses static rules written by administrators
Why it's wrong here
Static rules are rule-based, not behavioral.
- ✓
Can detect zero-day attacks
Why this is correct
By recognizing anomalies, it can catch unknown threats.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This 200-201 practice question is part of Courseiva's free Cisco certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 200-201 exam.