A virtual network hosts critical workloads, and a new threat detection solution was added. The solution monitors traffic for known attack patterns, yet operators worry about excessive false alerts. Which method best reduces false alerts while maintaining protection against hostile traffic?
Block traffic from outside networks that matches a general rule
Deploy anomaly-based inspection with file updates at frequent intervals
Distribute multiple sensors on random ports without central event analysis
Combine pattern-based detection with ongoing updates and correlation data
Blending pattern-based warnings with updated data and correlation methods reduces noise by distinguishing normal events from recognized threats. Reliance on blanket blocking can disrupt valid connections. Placing multiple sensors with no coherent analysis can miss broader patterns. An anomaly-based tool with file updates alone focuses on unusual spikes but does not address known exploits based on recognized patterns. Routine pattern updates are vital for catching emerging risks, and correlation tools link events to confirm if they signify an attack, resulting in fewer false alarms.
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