Imagine the SOC Without a Queue: From Alert Backlog to AI Hypothesis Engine

Traditional security operation centers are designed in a way that most alerts in the queue will not be reviewed by analysts due to time constraints. The typical process involves an alert being generated, assigned a severity score by a detection engine, and then waiting for human review to determine if it should be investigated further. This process is often overwhelmed by the high volume of alerts. The current model is not efficient, leading to a backlog of unreviewed alerts. The traditional SOC setup is based on a reactive approach that struggles to keep up with the alert volume. This has led to a need for a new approach to manage security operations.