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Monitoring and improving the performance of Security Operation Centers (SOC) are becoming crucial due to the emerging need of benefiting from Managed Security Services (MSS) rather than hiring in-house security experts. In this paper, by observing workflows of a real-world SOC, a system consisting of three different modules is designed for monitoring analysts' activities, analysis performance measurement, and performing simulation scenarios. The system empowers managers to evaluate the SOC's performance, which helps them to conform to Service Level Agreement (SLA) and see the need for improvement. Moreover, the designed system is strengthened by a background service module to provide feedback about anomalies or informative issues for security analysts. Three case studies have been conducted based on real data collected from the operational SOC, and simulation results have demonstrated the effectiveness of the different modules of the designed system in improving the SOC performance.

The concept of attack surface has seen many applications in various domains, e.g., software security, cloud security, mobile device security, Moving Target Defense (MTD), etc. However, in contrast to the original attack surface metric, which is formally and quantitatively defined for a software, most of the applications at higher abstraction levels, such as the network level, are limited to an intuitive and qualitative notion, losing the modeling power of the original concept. In this paper, we lift the attack surface concept to the network level as a formal security metric for evaluating the resilience of networks against zero day attacks. Specifically, we first develop novel models for aggregating the attack surface of different network resources. We then design heuristic algorithms to estimate the network attack surface while reducing the effort spent on calculating attack surface for individual resources. Finally, the proposed methods are evaluated through experiments.