Combat Cyber Threats with Machine Learning

Cybercrime is evolving as quickly as technology is. To counteract cyber threats and attacks, it’s imperative for businesses to stay one step ahead.

  • 69% of cybersecurity leaders say staying ahead of attackers is a constant battle and the cost is unsustainable.
  • Data breaches exposed 36 billion records in the first half of 2020
  • Ransomware remediation costs, including business downtime, lost orders, operational costs, and more, grew from an average of $761,106 in 2020 to $1.85 million in 2021
  • Research published by Varonis says that on average, only 5% of companies’ folders are properly protected against cybercrime

There are multiple technologies that are aiming to keep-up to support the fight against cyber-attacks, one of the most rapidly growing in use and advancements is machine learning.

In the last few years we have seen machine learning becoming a crucial part of the cybersecurity landscape. Find out why in this Whitepaper.

This Whitepaper covers:

  • What Is Machine Learning?
  • The most common use cases of ML in Cybersecurity
  • How Does Machine Learning Work?
  • Data collection and exploration– Observability Of The Environment
  • Data features extraction and data preparation – Machine Learning Analytics
  • Training the model – Machine Learning Implementation And Interpretability
  • How to Improve Analytics Capabilities

Fill out the form and Download

This field is for validation purposes and should be left unchanged.

Latest Cyber Security Blogs

We love our community and regularly publish industry blogs to share knowledge and give back.

New to the industry? You might find our Lingo Library useful, it’s full of industry terms with real industry examples.