'Companies must rely on the right AI model to stop cyber attacks'


Cyber attacks caused twice as much financial damage in 2023 as in the previous year. Cyber attacks are becoming more sophisticated and harder to defend against, especially when companies rely only on traditional security tools. If companies want to protect their critical data much better, they should bet on self-learning artificial intelligence (AI).

In the past, cybercriminals usually targeted several victims with one cyberattack. New techniques and developments in offensive artificial intelligence make it easier for these criminals to create large-scale attacks that target a single victim; unique and fully customised.

Many traditional security tools operate based on supervised machine learning models trained on data known about cyber attacks that have taken place before. However, these models can fail when they encounter something they have not seen before. If the model is not trained on a specific pattern, it can easily miss it.

Self-learning AI is another approach to building AI tools: self-learning AI is used to understand what is normal behaviour of an organisation as a whole. And therefore also what deviant behaviour is. Think of people who normally never email each other, but now suddenly do. Or people trying to log in to a particular account for the first time. Possibly with an unfamiliar device, or from an unfamiliar location. Self-learning AI can immediately detect and respond to these potential threats, stopping potential cyber attacks before it is too late.

With not only the number of cyber attacks increasing, but these attacks also becoming more unique and complex, companies need to rely on tools that work based on self-learning AI. This is the only way they can protect their critical data and avoid financial losses in the future.


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