Words for health and the human body often make their way into the language we use to describe IT. Computers get viruses; companies manage their security hygiene; incident response teams train on their cyber fitness. Framing IT concepts in terms of health can also be useful when looking at security operations centers (SOCs) and jobs in cybersecurity.
For many businesses and other entities today, SOCs are not the healthiest they could be. Jobs in cybersecurity can be stressful and overwhelming due to the volume of alerts. Many teams lack the staff they need to keep up with the influx.
The average SOC receives over 11,000 alerts a day, and 28% of all alerts are never addressed, says the 2020 State of Security Operations study from Forrester Consulting, sponsored by Palo Alto Networks.
What would healthier jobs in cybersecurity look like? Imagine fewer alerts organized by priority, and analysts being less stressed as a result. With their time freed up from processing false positives and low-value alerts, analysts could have a chance to dig into higher-value work and advance their careers. Applying AI and machine learning (ML) from detection all the way to response can set SOCs on the path toward achieving this vision for their analysts — and strengthening the group’s security postures.
Learn more about AI for cybersecurity
How AI/ML Advances the Health of Your SOC
From sorting alerts to enabling threat sharing, AI/ML can make the SOC more efficient in triage, analysis and response. Connecting the worlds of IT and h ..
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