A Novel Team Formation Framework Based on Performance in a Cybersecurity Operations Center

Abstract

A Cybersecurity Operations Center (CSOC) performs various tasks to protect an organization from cyber threats. Several types of personnel collaborate to function effectively as a team to analyze the threat signals, in the form of alerts, arriving from various sources. Teams are often formed ad hoc, resulting in an imbalance in their performances and thereby increasing the risk associated with the low-performing teams. The current approach taken by behavioral scientists in forming effective teams focuses on first qualitatively assessing individuals such as analysts, who are then grouped into teams based on their credentials and expertise. Our work takes a holistic view of the CSOC by first defining team requirements and then selecting individuals to form several collaborative teams that meet these requirements for every shift of operation. We present a novel team formation framework that integrates optimization, simulation, and scoring methods to form effective teams and introduce a new collaborative score metric that measures their effectiveness. Results from simulated experiments show the formation of effective teams whose collaborative scores are maximized and balanced. Our approach is also able to identify high and low performers within the first few months of implementing the framework.