The future of machine learning in cybersecurity: What can CISOs expect?
Cybercrime

The future of machine learning in cybersecurity: What can CISOs expect?

August saw the Defense Advanced Research Projects Agency (DARPA) host its first Cyber Grand Challenge – the first hacking competition not involving people. During this event, teams left their systems alone to single-handedly find, diagnose and fix software flaws in real time.

Elsewhere, researchers at MIT are not only developing machine learning systems that automatically mine dark web marketplaces for vulnerabilities and zero-day attacks and reports them back as well as software that automatically fixes buggy code, but also a platform that can predict 85% of cyber-attacks.

Machine learning, deep learning, and Artificial Intelligence (AI) are hot topics at the moment, and while there’s plenty of research going on, there’s also some practical applications that can be deployed right now to make life easier for cybersecurity professionals.

A glut of new start-ups, from the likes of Darktrace, Cylance, Deep Instinct, and HackerONE, plus established player such as FireEye, IBM, and Forcepoint, are all working on bringing self-learning systems into the world of security.

 

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Dan Swinhoe

Dan is Senior Staff Writer at IDG Connect. Writes about all manner of tech from driverless cars, AI, and Green IT to Cloudy stuff, security, and IoT. Dislikes autoplay ads/videos and garbage written about 'milliennials'.  

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