200-201 Question 178
Single answerA cybersecurity analyst is tasked with monitoring network traffic for potential threats. The organization uses a combination of rule-based systems, signature-based detection, and predictive AI. During the monitoring process, the analyst observes an alert triggered by predictive AI, which identifies unusual behavior in network traffic that does not match any known signature or pre-defined rule. What is the most likely reason predictive AI flagged this behavior?
- A
The behavior matches a known malware signature in the threat database.
- B
The behavior deviates from established baselines and exhibits characteristics of potential malicious activity.
- C
The behavior violates a predefined rule configured in the intrusion detection system (IDS).
- D
The behavior is flagged because predictive AI only detects malware based on static signatures.
Show answer and explanation
Correct answer: B
Explanation
Predictive AI is designed to go beyond traditional rule-based or signature-based systems by identifying anomalies and potential threats through behavioral analysis and machine learning. In this scenario, the AI flagged unusual behavior because it detected deviations from normal patterns that could indicate malicious activity, even in the absence of known signatures or predefined rules.
- A. Incorrect.
This option is incorrect because predictive AI does not rely on known malware signatures. Signature-based detection systems are responsible for identifying matches in the threat database.
- B. Correct.
This option is correct because predictive AI uses machine learning models to detect anomalies by analyzing deviations from normal baselines and identifying patterns indicative of potential threats, even if they do not match known signatures or rules.
- C. Incorrect.
This option is incorrect because predefined rules are part of rule-based systems, not predictive AI. Rule violations are flagged by systems such as IDS with threshold-based configurations.
- D. Incorrect.
This option is incorrect because predictive AI does not rely solely on static signatures. Instead, it uses dynamic learning to detect previously unseen or evolving threats.