The Power Of Automation: The Role Of Machine Learning In Cybersecurity

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The power of automation: The role of machine learning in cybersecurity paid Fortinet

That’s why the other edge of the sword—a strong, automated defensive bulwark—is critical for enterprises to secure their vast environments.

Analytics is a force multiplier in the effort to detect and secure the network, amplifying the capabilities of security teams, reducing risk, and increasing efficiency and productivity. Here’s a closer look:. AI gives human experts visibility into their complex environments, enhancing the capabilities of security teams.

17% say an inability to detect breaches after they have occurred is the most serious challenge created by a shortage of qualified cybersecurity staff. Time-series analysis and machine learning increase detection capabilities. Such adaptive, continuous-learning technologies adjust to evolving risk models and threats, and they enable something every security team chases: speed.

Productivity increases when automation removes the noise in the network—the millions and tens of millions of harmless events happening across the data flow. “If you can use analytics and machine learning to do that for you,” Heath says,"then your teams end up investigating something more meaningful. That will help them close down any potential issue much faster than they would if they were working alone.

 

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