Reduce False-Positive SIEM Alerts

Infer detection rules derived from knowledge graphs on a tactical level

SOC leaders often dive into SIEM detection use case discussions without understanding the broader context of the cyber threat. During recent years SOC organizations have implemented hundreds of ineffective SIEM detection use cases, generating enormous amounts of false-positive alerts, which trigger inefficient follow-up incident response actions. Consequently, this noise results to distraction from important tasks such as threat hunting and missing out on true-positive security events.

To prevent this, Cyber Threat Models should be built to achieve a holistic view on the cyber threats. Implement IdoubleS to build attack graphs on a tactical level for deriving effective SIEM detection rules. This reduces noisy false-positive alerts and saves incident response follow-up endeavors. In addition, your expenses will be reduced and resources will be used more efficiently.

How you can benefit from IdoubleS while implementing the following cyber security frameworks or programs:

BaFIN VAIT/BAIT and Digital Operational Resilience Act (DORA)

IdoubleS helps in optimizing threat detection use cases*.