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CiscoCertified CyberOps Associate

Domain 1Objective 11

1.11 Compare Rule-Based Detection vs. Behavioral and Statistical Detection 200-201 Practice Questions (Page 4)

Part of the 1.0 Security Concepts domain, which accounts for 20% of the 200-201 exam. Cisco does not publish an official question count, but from its 120-minute exam (~50–80 total, ~10–16 in this domain), expect 1–1 from this objective — we provide 36 practice questions to prepare you well beyond it. (estimate)

36questions here
8free pages
4concepts
20%of the exam

Questions 16–20

  1. 16application · medium

    A small business has a legacy intrusion detection system that relies on signatures. The business cannot afford a full-time security analyst to tune the system. Which scenario is this system most likely to handle effectively?

    Select an answer first
  2. 17expert · hard

    A security operations team is evaluating a behavioral detection tool that uses machine learning to establish baselines for user activity. The tool has been in production for a month and is generating a high number of false positives. The team suspects the baselines are not accurate. Which action is most likely to improve the tool's accuracy?

    Select an answer first
  3. 18application · medium

    A security analyst is configuring a network intrusion detection system (IDS) for a small office. The office has a static network environment with few changes. The analyst wants to detect known malware signatures with minimal false positives. Which detection approach is most suitable?

    Select an answer first
  4. 19foundation · easy

    A security analyst is configuring an intrusion detection system to alert on a known malware pattern. Which detection method relies on predefined signatures or patterns to identify known threats?

    Select an answer first
  5. 20application · medium

    A university's security team wants to detect potential data exfiltration by students who download large amounts of research data. The team has no prior knowledge of specific attack signatures. They need a solution that can identify unusual download patterns without manually defining thresholds for each user. Which detection approach best meets this requirement?

    Select an answer first
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