Machine Learning

Machine learning in cybersecurity

Machine learning is tightly connected with artificial intelligence. We deal with it in our everyday life, not even being aware of it. Machine learning is based on very advanced algorithms capable of improving themselves by using the gathered data.

Protection against cyberattacks today requires technologically-advanced solutions capable not only of mitigating attacks in real time, but above all of detecting the threats and effectively protecting the webpages, networks, and applications. To effectively protect against cyberattacks, Grey Wizard uses algorithms based on machine learning.

The effectiveness of Grey Wizard Shield is based to a large extent on intelligent machine-learning algorithms. The synergy between the knowledge of our world-class cybercrime experts and the machine-learning mechanisms enables Grey Wizard to detect all anomalies through comprehensive monitoring of web applications and identification of dangerous requests from the network.

Web application monitoring

The algorithms employed in Grey Wizard Shield perform a detailed analysis of network traffic between users and web applications. Based on multiple factors, the Grey Wizard application determines a model traffic and its dynamics, thus making it possible to detect any anomalies and at the same time to minimize the risk of false alerts.

Real-time application monitoring enables the Grey Wizard team to immediately respond to any threats related to attacks against customers’ applications.

Identification of dangerous requests

Grey Wizard Shield uses intelligent algorithms also to analyze requests generated by the users, thus providing the highest level of protection against such attacks as SQL injection, cross-site scripting (XSS), or local file inclusion (LFI).

The machine-learning algorithms are always one step ahead of the cybercriminals, because they detect even attacking methods that have not been identified yet. Also, they are capable of recognizing attacks not addressed by traditional rule-based systems.


For media

Provide us with contact details.

Thank you