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Service Oriented Computing and Applications

, Volume 12, Issue 2, pp 123–135 | Cite as

Adaptive reallocation of cybersecurity analysts to sensors for balancing risk between sensors

  • Ankit Shah
  • Rajesh Ganesan
  • Sushil Jajodia
  • Hasan Cam
Original Research Paper
  • 108 Downloads

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.

Keywords

Cybersecurity analysts Adaptive reallocation Balance risk between sensors Reactive scheduling Goal programming Mixed-integer programming 

Notes

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.

Supplementary material

11761_2018_235_MOESM1_ESM.pdf (108 kb)
Supplementary material 1 (pdf 108 KB)

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Secure Information SystemsGeorge Mason UniversityFairfaxUSA
  2. 2.Army Research LaboratoryAdelphiUSA

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