Abstract
Cyber Security Operations Center (CSOC) is a service-oriented system. Analysts work in shifts, and the goal at the end of each shift is to ensure that all alerts from each sensor (client) are analyzed. The goal is often not met because the CSOC is faced with adverse conditions such as variations in alert generation rates or in the time taken to thoroughly analyze new alerts. Current practice at many CSOCs is to pre-assign analysts to sensors based on their expertise, and the alerts from the sensors are triaged, queued, and presented to analysts. Under adverse conditions, some sensors have more number of unanalyzed alerts (backlogs) than others, which results in a major security gap for the clients if left unattended. Hence, there is a need to dynamically reallocate analysts to sensors; however, there does not exist a mechanism to ensure the following objectives: (i) balancing the number of unanalyzed alerts among sensors while maximizing the number of alerts investigated by optimally reallocating analysts to sensors in a shift, (ii) ensuring desirable properties of the CSOC: minimizing the disruption to the analyst to sensor allocation made at the beginning of the shift when analysts report to work, balancing of workload among analysts, and maximizing analyst utilization. The paper presents a technical solution to achieve the objectives and answers two important research questions: (i) detection of triggers, which determines when-to reallocate, and (ii) how to optimally reallocate analysts to sensors, which enable a CSOC manager to effectively use reallocation as a decision-making tool.
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Acknowledgements
The authors would like to thank Dr. Cliff Wang of the Army Research Office for the many discussions which served as the inspiration for this research.
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Shah, Ganesan, and Jajodia were partially supported by the Army Research Office under Grants W911NF-13-1-0421 and W911NF-15-1-0576 and by the Office of Naval Research under Grant N00014-15-1-2007.
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Shah, A., Ganesan, R., Jajodia, S. et al. Adaptive reallocation of cybersecurity analysts to sensors for balancing risk between sensors. SOCA 12, 123–135 (2018). https://doi.org/10.1007/s11761-018-0235-3
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DOI: https://doi.org/10.1007/s11761-018-0235-3