SAIBERSOC

Martin Rosso, Michele Campobasso, Ganduulga Gankhuyag, and Luca Allodi
SAIBERSOC: Synthetic Attack Injection to Benchmark and Evaluate the Performance of Security Operation Centers
Published in ACSAC '20: Proceedings of the 36th Annual Computer Security Applications Conference (ACSAC 2020) on .
[official] [arxiv]

Abstract

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 and does not find differences where there should be none. We release the SAIBERSOC tool implementation as free and open source software.


Additional Info

  1. This paper has artifacts.
  2. This paper received the Distinguished Paper with Artifacts Award (ACSAC’20).
  3. This paper has an extended journal version.