Cyberattacks are still getting faster and more numerous, continuing the age-old IT security arms race. Now, with many organizations also tapping into the cloud and allowing IoT devices to connect to networks, the security landscape offers unprecedented challenges.
To stay a step ahead of attacks and close security gaps, organizations need solutions that are faster and smarter than ever before. For that reason, Palo Alto Networks has developed ML-powered security innovations that are woven directly into the core of our NGFW. This provides features like real-time device identification and inline signatureless attack prevention to enable network administrators to meet modern security challenges head on.
Traditional firewall security solutions can get in the way of network operations and degrade performance by using offline systems that increase the time needed to process and analyze each data transfer. Our ML-Powered NGFW solution makes malware classification decisions at “line speed,” with core, inline functionality. It can inspect and block malicious files before they are downloaded and spread across the organization.
Waiting for scheduled malware signature updates can cause excessive delays in stopping sophisticated attacks. An ML- Powered NGFW pushes signatures in seconds, right after completion of ML-based analysis. This means that every NGFW in your network is updated within seconds. As a result, the first user to see a never-before-seen threat is the only user to experience first-time exposure.
About 45% of enterprises have IoT deployment, and this number is rapidly increasing. Unfortunately, many devices are unsecured, and manual addition to registers doesn’t scale well. Our ML-Powered NGFW bypasses the limitations of signature-based or manual approaches. Our firewalls use signature-based or manual approaches. Our firewalls use fine-tune models in real time to help mitigate the threats posed by unmanaged devices.
Keeping up with rapidly changing networks, applications, and devices can lead to overly permissive policies to avoid breaking applications. An ML-Powered NGFW analyzes vast amounts of telemetry data across millions of IoT devices to give intelligent policy recommendations that reduce risk. Automated policy recommendations based on context-specific device profiles save countless hours and reduce human error, compared to manual management.