Next generation cyber defense driven by analytics and machine learning

The biggest problem for security teams is often too much data and many are addressing this by turning to analytics and machine learning, according to a new report.

The study from CyberEdge Group surveyed 1,200 IT security decision makers and practitioners and finds 47 percent intend to deploy advanced analytics solutions in the next year.

More than 90 percent of IT security organizations have invested in ML and/or artificial intelligence technologies to combat advanced threats, and more than 80 percent say they are already seeing a difference.

That said, the percentage of organizations affected by a successful cyberattack rose slightly this year, from 77 percent to 78 percent, despite last year's first-ever decline. Organizations affected by successful ransomware attacks increased too from 55 percent to 56 percent. More concerning is that the percentage of organizations that elected to pay ransoms rose considerably, from 39 percent to 45.

"Security analytics and machine learning could very well hit their stride in 2019," says Steve Piper, CEO of CyberEdge Group. "We surveyed our research participants on their intended cyber investments across a broad range of security technologies. Respondents identified ‘advanced security analytics with machine learning’ as the most-wanted security technology for the coming year. This makes sense, given that 'too much data to analyze' surpassed 'lack of skilled personnel' as the greatest inhibitor to IT security’s success."

Shortage of security skills is still an issue, with 84 percent of organizations experiencing a problem compared to 81 percent a year ago. On average, IT security consumes 12.5 percent of the overall IT budget in organizations and the average security budget is set to go up by 4.9 percent in 2019.

The full Cyberthreat Defense Report is available from the CyberEdge site.

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