Taking security beyond SIEM capabilities requires thinking outside of the (black) box. Gurucul uses behavior-based security analytics powered by machine learning to detect risky behavior. Traditional SIEMs import data, normalize that data and provide minimal enrichment. Correlation rules specify a sequence of events that indicates an anomaly, or potential security threat. This technique is outdated because it generates significant number of false positives. Also, SIEMs are incapable of detecting new, and especially, unexpected threats.
Correlation rules can only detect known patterns. So, unknowns go completely undetected. In today’s digital age, as cybercriminals become more advanced, any time that passes between a breach and an alert is money. You need to be able to detect both known and unknown threats.
Attend this webinar to learn how machine learning based behavior analytics takes security beyond SIEM correlation rules and queries. By taking security beyond SIEM, you can identify risky changes in behavior patterns in real-time and automate corrective action. Get actionable intelligence with low false positives.