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What's New in the NetSec Platform

Local Deep Learning for Advanced Threat Prevention

Table of Contents

Local Deep Learning for Advanced Threat Prevention

Advanced Threat Prevention now supports Local Deep Learning, enabling supported platforms to perform fast, local deep learning-based analysis of zero-day and other evasive threats.

Advanced Threat Prevention now supports Local Deep Learning, which provides a mechanism to perform fast, local deep learning-based analysis of zero-day and other evasive threats, as a complementary feature to the cloud-based Inline Cloud Analysis component of Advanced Threat Prevention. With an Advanced Threat Prevention license, known malicious traffic that matches against Palo Alto Networks published signature set are dropped (or have another user-defined action applied to them); however, certain traffic that matches the criteria for suspicious content are rerouted for analysis using the Deep Leaning Analysis detection module. If further analysis is necessary, the traffic is sent to the Advanced Threat Prevention cloud for additional analysis, as well as the requisite false-positive and false-negative checks. The Deep Learning detection module is based on the proven detection modules operating in the Advanced Threat Prevention cloud, and as such, have the same zero-day and advanced threat detection capabilities. However, they also have the added advantage of processing a much higher volume of traffic, without the lag associated with cloud queries. This enables you to inspect more traffic and receive verdicts in a shorter span of time. This is especially beneficial when faced with challenging network conditions.

Updates to Local Deep Learning models are delivered through content updates. Local Deep Learning is enabled and configured using the Anti-Spyware profile and requires an active Advanced Threat Prevention license.

IPSec Serviceability

Monitor Bandwidth on SD-WAN Devices