What is one aspect of ForeScout's machine learning capabilities?

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One key aspect of ForeScout's machine learning capabilities is the detection of anomalies in device behavior. This feature enables the platform to establish a baseline of normal behavior for devices on the network and identify any deviations from that baseline. By recognizing patterns and unusual activities, the system can alert administrators to potential security threats, such as compromised devices or unauthorized access attempts, in real time. This proactive approach enhances the overall security posture of an organization by allowing for quicker response to potential risks and minimizing vulnerabilities.

The other choices do not align with the purpose and functionality of machine learning in this context. Decreased security protocols and decreased alert responsiveness are counterproductive to the goals of a security system, as they would weaken defenses and response times. Storing all device data indefinitely is impractical and not a feature associated with intelligent anomaly detection, which typically focuses on relevant data analysis rather than endless storage.

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