SAIBERSOC: Synthetic Attack Injection to Benchmark and Evaluate the Performance of Security Operation Centers
This provides a method for security researchers and operators to benchmark SOC performance, though it is incremental as it builds on existing frameworks.
The paper tackles the problem of evaluating Security Operation Centers (SOCs) by introducing SAIBERSOC, a tool that injects synthetic attacks based on the MITRE ATT&CK Framework to measure metrics like detection accuracy and time-to-investigation, with results from an experiment involving 124 students showing it effectively identifies performance variations due to SOC configuration changes.
In this paper we introduce SAIBERSOC, a tool and methodology enabling security researchers and operators to evaluate the performance of deployed and operational Security Operation Centers (SOCs) (or any other security monitoring infrastructure). The methodology relies on the MITRE ATT&CK Framework to define a procedure to generate and automatically inject synthetic attacks in an operational SOC to evaluate any output metric of interest (e.g., detection accuracy, time-to-investigation, etc.). To evaluate the effectiveness of the proposed methodology, we devise an experiment with $n=124$ students playing the role of SOC analysts. The experiment relies on a real SOC infrastructure and assigns students to either a BADSOC or a GOODSOC experimental condition. Our results show that the proposed methodology is effective in identifying variations in SOC performance caused by (minimal) changes in SOC configuration. We release the SAIBERSOC tool implementation as free and open source software.