CCNP Security 300-745 SDSI Practice Test 27

Correct Answer: Analyzing large volumes of telemetry and log data to identify anomalies and patterns that would be impractical for human analysts to detect manually in real time
Explanation: AI analyzes large volumes of telemetry to identify anomalies impractical for manual detection, unlike limiting AI to marketing content generation, eliminating the need for telemetry collection, limiting AI to conversational Q&A, equating AI to a simple static signature rule, or assuming AI guarantees zero incidents.

Correct Answer: Enhancing detection by correlating signals across data sources, reducing false positives through pattern recognition, and surfacing prioritized findings for human analyst review
Explanation: AI enhances detection by correlating signals, reducing false positives, and surfacing prioritized findings for analyst review, unlike fully replacing analysts with no oversight, providing no value beyond signature tools, guaranteeing zero false positives, eliminating the underlying SIEM/EDR platform, or having no relationship to existing collected data.

Correct Answer: Establishing appropriate human oversight and validation checkpoints scaled to the severity of the automated action, since AI-driven decisions can be incorrect and the consequences of an erroneous automated action against infrastructure could be significant
Explanation: Human oversight scaled to action severity addresses the risk of incorrect AI-driven decisions with significant infrastructure consequences, unlike assuming AI is always accurate needing no oversight, granting fully unrestricted autonomous control, disabling decision logging, assuming AI can never be wrong, or requiring no integration with existing tools.

Correct Answer: The tool could produce inaccurate detections (excessive false positives or missed true positives) because its analysis is poorly calibrated to the organization's actual network behavior and threat exposure
Explanation: Poorly calibrated training data risks inaccurate detections not matched to the organization's actual environment, unlike assuming lack of validation stops the tool from functioning, that DNS infrastructure fails, that accuracy improves automatically with no effort, that it reduces tooling costs, or that it has no impact on detection accuracy.

Correct Answer: The demonstrated accuracy and false-positive rate of the AI function in the organization's specific environment, combined with the severity and reversibility of the action it would be permitted to take
Explanation: Demonstrated accuracy/false-positive rate and action severity/reversibility most influence the autonomy granted to AI-driven functions, which is unrelated to the dashboard's color scheme, SOC coffee brand, headquarters parking space count, an internal newsletter's font, or outdoor temperature.

Correct Answer: AI integrated with existing telemetry sources (SIEM/EDR) to enhance detection and correlation, validated against the organization's specific environment for accuracy, and paired with human oversight scaled to the severity of any resulting automated actions
Explanation: AI integrated with existing telemetry, validated for environment-specific accuracy, and paired with severity-scaled human oversight together provide effective governance, unlike full autonomous control with no oversight, no integration with existing telemetry, unvalidated accuracy assumptions, uniform oversight regardless of severity, or generating findings that are never reviewed.

Correct Answer: Investigate whether recent legitimate changes to network behavior or traffic patterns have caused the tool's baseline or model to become miscalibrated, and assess whether retraining or recalibration is needed
Explanation: Investigating whether legitimate network changes caused baseline miscalibration and assessing retraining needs is the appropriate diagnostic step, unlike blaming desktop wallpaper, disabling the tool entirely with no investigation, wrongly assuming this is a deprecated concern, blaming unrelated air conditioning, or blaming the phase of the moon.

Correct Answer: AI excels at processing large volumes of data and identifying patterns at scale, but human analysts provide contextual judgment, accountability, and the ability to interpret findings within broader business and threat context that AI alone may not fully capture
Explanation: AI excels at scale pattern recognition while humans provide contextual judgment, accountability, and broader interpretation, unlike claiming AI and humans are identical, that AI fully replaces human judgment, that this is guest-only, that humans add no value once AI is deployed, or that AI decisions need no human accountability.

Correct Answer: Periodically retraining or recalibrating the AI function against current network behavior, continuously monitoring its accuracy and false-positive/negative rates, and reassessing the appropriate level of autonomous action as confidence in its performance changes
Explanation: Periodic retraining, continuous accuracy monitoring, and reassessing autonomy as confidence changes together maintain effectiveness and trustworthiness over time, unlike a set-once deployment, assuming accuracy stays constant, ignoring false-positive/negative rates, annual-only review, or disabling recalibration once deemed mature.

Correct Answer: Conducting a scoped pilot or proof-of-concept deployment against the organization's actual network traffic and threat scenarios to measure the tool's real-world accuracy and operational fit before broader rollout
Explanation: A scoped pilot against actual traffic and threat scenarios measures real-world fit before full rollout, unlike relying solely on vendor marketing claims, deploying directly to full production with no pilot, assuming uniform performance across environments, selecting by cost alone, or skipping evaluation entirely.