Applications of Machine Learning in Cybersecurity

Applications of Machine Learning in Cybersecurity

Currently, most vendors are talking about machine learning and artificial intelligence. But what are they, and what do they do? Machine learning is a branch of information technology that allows computers and other devices to learn new behaviours and changes based on empirical data. 

The main goal is to design and develop algorithms that will allow computers to react to changes and display behaviour learned from their past experiences without human interaction. Since computers are able to learn, it is essential to understand how machine learning and artificial intelligence can benefit cybersecurity. Here are the main applications of machine learning in cybersecurity: 


Developing Respective Defence Responses in Emails 

Machine learning can collect, analyse and process information without human interference. Concerning cybersecurity, this technology will help to analyse previous attacks and develop a particular defence response. It helps an automated cyber defence system with minimum-skilled cybersecurity forces. 

With the help of artificial intelligence and machine learning algorithms, Google is able to block unwanted email communications on Gmail with 99% accuracy. Also, companies are taking advantage of this technology to protect their employees and customer’s privacy and personal data. 


Breaking the Language Barrier 

Another major barrier to the production of actionable threat intelligence is language. Most of the data required by the security experts are buried in unstructured text form and distributed across millions of sites on both dark and open web. With the help of machine language, there is natural language processing that poses great benefits for cybersecurity. 

This language enables computers and other devices to gather all information and make sense of it irrespective of the format and punctuation. Powerful natural language engines are in the position to understand common jargon and slang across all languages in the world, which is something that a team of analysts could never aspire to.

Date: 31 October 2018, 13:10 pm
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