Cybersecurity Beyond SIEM

SIEMs provide real-time analysis of security alerts, analyzing data to catch abnormal behavior or potential cyberattacks but can always fail. Join us at a webinar to discuss a way forward in such instances.


Join CIO East Africa and Secureworks on Thursday, 25 February 2021, at a webinar to explore Cybersecurity Beyond Security Information and Event Management (SIEM).

The one-hour event is scheduled to run from 3.00 pm EAT and shall be free to attend.

Gopan Sivasankaran Senior Manager – Solutioning, Middle East & Africa, shall be speaking at the security webinar. Gopan has over 16 years of information security experience in various roles ranging from security analyst, implementer, consultant, architect, and people leader.

Varonis report in their Beginners Guide To Siem that SIEM tools are an important part of the data security ecosystem. They aggregate data from multiple systems and analyse that data to catch abnormal behaviour or potential cyberattacks. It further states that SIEM tools provide a central place to collect events and alerts.

But what if the said tools fail?

SIEM was coined in 2005 by Gartner to describe Security Information and Event Management software, which provides real-time analysis of security alerts. However, a lot has evolved since then. SIEMs traditionally import data, normalise and provide minimal details but are sometimes incapable of detecting new, and especially, unexpected threats.

It is against this backdrop that Secureworks in conjunction with CIO East Africa explores the most current cybersecurity technologies and tools to beef up cybersecurity even beyond SIEMs and which have the potential to indicate an anomaly or potential security threat.

With SIEM tools, correlation rules can only detect known patterns, as noted earlier, leaving the unknown completely undetected. In this digital age, cyber hackers and criminals continually advance, leaving SIEMs only model of security as being ‘not very reliable.’ Security beyond SIEM capabilities requires behavior-based security analytics powered by machine learning to detect risky behaviour.

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