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detection and resolution can save organizations a huge amount of money .
Implementing a Security Information and Event Management ( SIEM ) solution that analyzes the network ' s activities and helps to detect attacks , and a User and Entity Behavior Analysis ( UEBA ) tool that uses Machine Learning ( ML ) to detect users ' and entities ' behavior anomalies can act as a multi-layered defense strategy .
It is more difficult to detect such attacks as they go unnoticed amongst the routine activities that administrators carry out using these same tools .
A zero-day exploit happens when a hack occurs on the same day that a vulnerability is exposed . Due to these sophisticated methods , the Mean Time to Identify ( MTTI ) an attack was as high as 197 days , and the Mean Time to Contain ( MTTC ) was 69 days in 2018 . Thus every organization needs effective security solutions to safeguard itself against threats . Early
SIEM and UEBA
SIEM solutions enable organizations to collect and store logs in a central location . They also leverage different traffic flow protocols to keep track of other network activities . This makes it extremely convenient for IT administrators to set thresholds and conditions for realtime alerting in case of security incidents . SIEM solutions also enable IT administrators to correlate a series of events together to identify a threat that otherwise would have been missed . These solutions rely on known patterns or ‘ signatures ’ to identify a threat vector . p
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