Modern IDS solutions increasingly use machine learning to detect anomalous behavior that does not match known signatures, reducing reliance on traditional signature-based detection. This catches novel attacks but introduces challenges around explaining alerts and tuning detection thresholds. The most effective deployments combine signature-based and behavior-based detection rather than relying on either alone.
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