Detecting Cybersecurity Threats by Integrating Explainable AI with SHAP Interpretability and Strategic Data Sampling

The critical need for transparent and trustworthy machine learning in cybersecurity operations drives the development of this integrated Explainable AI XAI framework. Our methodology addresses three fundamental challenges in deploying AI for threat detection: handling massive datasets through...

Hands-On Review: SASE-based XDR from Cato Networks

Companies are engaged in a seemingly endless cat-and-mouse game when it comes to cybersecurity and cyber threats. As organizations put up one defensive block after another, malicious actors kick their game up a notch to get around those blocks. Part of the challenge is to coordinate the defensive...

How to Use AI in Cybersecurity and Avoid Being Trapped

The use of AI in cybersecurity is growing rapidly and is having a significant impact on threat detection, incident response, fraud detection, and vulnerability management. According to a report by Juniper Research, the use of AI for fraud detection and prevention is expected to save businesses $1...