Home Technology 5 Top Uses of Machine Learning in Cybersecurity

5 Top Uses of Machine Learning in Cybersecurity

Artificial intelligence (AI) has come along way over the past decade, especially when it comes to machine learning. Machine learning is about computers being able to learn on their own. It can also help seek out security threats for businesses and respond effectively to any attacks.

Experts estimate that by 2021 machine learning in cybersecurity will bring the total level of spending between analytics, big data, and AI to around $96 million. Many big names are using machine learning to help with security issues. Google uses it to analyze threats that run on Android, while Amazon uses it to sort data on its cloud service. Here are a few other examples of how AI and machine learning’s being used in security:

1.Used to close zero-day vulnerabilities

Traffic was monitored on the dark web via a team at Arizona State University using machine learning techniques. In doing so, they successfully identified data pertaining to zero-day exploits. Armed with this knowledge companies could close vulnerabilities and stop data breaches before they happen.

2. Enhancing human analysis

While analysts are very good at their job, they aren’t and never will be as good as AI. In 2016, MIT developed an AI system that used adaptive machine learning in which to help analysts find those needles in the haystack. The machine filtered the data first then passed it onto the analysts for finer tuning. In doing this the number of alerts was brought down considerably.

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3. Detection of malicious activity/stop attacks

AI and machine learning help protect businesses against malicious activity and stop attacks by detecting them before they begin. UK start-up Darktrace has been around since 2013 and is a company that’s no stranger to AI. Over the past four years, it’s helped various customers stay protected against attacks, including the NHS.

4. Automate repetitive security tasks

By taking away some of the more menial jobs from workers it will free them to do more important work. “Let the machines handle the repetitive work and the tactical firefighting like interrupting ransomware so that the humans can free up time to deal with strategic issues – like modernizing off Windows XP – instead,” said David Palmer.

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5. Analyzing mobile endpoints

Earlier this year an announcement was made as to the collaboration of MobileIron and Zimperium that will see more enterprises integrate machine learning security solutions into their businesses. Others that are also boosting their mobile security solutions include Wandera, Skycure, and LookOut.

Source CSOOnline

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KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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