Beyond the Buzz: 3 Ways Artificial Intelligence Represents the Future of Cybersecurity

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Beyond the Buzz: 3 Ways Artificial Intelligence Represents the Future of Cybersecurity

This guest-post is courtesy of our partners at FPOV - Future Point of View.

Take a quick stroll around any cybersecurity conference and you will witness endless vendors hawking services that feature an ever-present technology buzzword: artificial intelligence. When people say artificial intelligence, in many cases, what they mean is machine learning or machine intelligence. What we’re doing is we are “training” machines to do tasks by feeding these machines vast quantities of data. A simple example is teaching a machine to recognize a cat. By showing a machine a steady stream of cat pictures, a machine can learn to recognize a cat. A more complex example is IBM’s Watson, who famously defeated human Jeopardy! champions in the television quiz show. Through the ingestion of a limitless stream of medical journals, Watson (in addition to dethroning Jeopardy! champions) is now able to help doctors recognize unusual maladies and make more accurate diagnoses.

Artificial Intelligence (AI) and Machine Learning (ML) are poised to transform every facet of the industry and daily life. However, for this post, let’s focus briefly on one specific area by examining three ways AI and ML are enhancing cybersecurity.

Threat Intelligence

Mention the term false positive to a threat analyst, and you will hear an audible groan. These are files or data flagged as malicious but turn out to be harmless. What threat analysts deal with now is information overload. There is way too much for an analyst to reasonably respond to, and that’s not good for organizations that depended upon these analysts to keep them safe. That’s where AI/ML can help in a big way. It will work alongside human analysts to help spot the most critical threats while working to eliminate false positives.


As we move to more virtual work, effective identification becomes paramount. AI and ML will play a key role in identifying users. As an example, companies are harnessing the power of machine learning to effectively use pattern recognition in keystroke dynamics. Simply, they can identify users based on how said user types on a keyboard. This, alongside traditional biometrics such as fingerprint analysis and facial recognition, can create a system of multifactor authentication that will be difficult to circumvent. And then maybe we can finally get rid of passwords. Here’s hoping!

Secure Coding

Humans are fallible; to recognize this one must look no farther than computer code. Writing complex software code is challenging, and it is easy to make mistakes. These mistakes can become software vulnerabilities. AI and ML will help coders spot these errors or vulnerabilities and allow for correction before going to market. Artificial Intelligence and Machine Learning are poised to transform every part of society. This technology will augment humans by giving us the ability to do more in less time and to avoid the tedium of repetitive work while freeing us up to be creative and innovative. It also can go a long way to keeping us safe in cyberspace. And as we continue to conduct a growing amount of our daily lives in the digital space, this will become essential.

Clevyr builds cutting edge, scalable technology software solutions including artificial intelligence for IT operations, digital twinning, predictive analytics, and cognitive computing - plus much more! Check us out at or drop us a line at

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