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Threat detection metrics: exploring the true-positive spectrum | by Alex Teixeira | Medium

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I’ve had the chance to work with many great security teams during my career and in 2012, I had the opportunity to join Verizon's SOC in Germany. That was a very challenging experience considering its massive scale SecOps. It was also by that time when I realized Splunk could be used as a sort of BI/Reporting platform given its ability to quickly generate eye-catching reports or dashboards from case or incident management systems data. Today, when designing and building detection mechanisms, it's easier to notice the link between threat detection engineering practice and overall SOC services quality, regardless of target customer (internal/external). Without going too deep on that, I guess the true-positive (TP) versus false-positive (FP) classification became widespread in Infosec after the introduction of pattern based Network Intrusion Detection Systems (NIDS). In a nutshell, here's how the assessment is done: "Does the input (network flow) match a pattern?" If yes, it must be either

Threat detection metrics: exploring the true-positive spectrum Alex Teixeira 6 min read · Jun 12, 2019 -- 1 Listen Share I’ve had the chance to work with many great security teams during my career and in 2012, I had the opportunity to join Verizon's SOC in Germany. That was a very challenging experience considering its massive scale SecOps. It was also by that time when I realized Splunk could be used as a sort of BI/Reporting platform given its ability to quickly generate eye-catching reports or dashboards from case or incident management systems data. Today, when designing and building detec

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