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Data Center News > Blog > Global Market > Fortinet extends AI support to network threat detection, cloud workflow
Global Market

Fortinet extends AI support to network threat detection, cloud workflow

Last updated: November 10, 2024 9:50 am
Published November 10, 2024
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“Utilizing pure language queries, groups can simply make clear the rationale behind the alerts which can be generated, perceive the chance, similar to how an attacker may compromise the system, acquire step-by-step steering on examine and reply, and streamline the remediation of points with syntactically appropriate code,” Fortinet acknowledged.

Fortinet has been including assist for AI-related know-how all through its product portfolio. For instance, it not too long ago introduced that its FortiGate NGFW now consists of real-time inline detection and prevention of AI-powered assaults. An improve to the AI-powered Inline Malware Prevention Service consists of new options similar to real-time anti-phishing and an accelerated AI pre-filter, in line with Fortinet.

FortiAnalyzer, which is the seller’s safety analytics and log administration platform, additionally not too long ago gained AI-based enhancements. The options embrace the flexibility to study and detect community configurations, occasions, and alerts, together with superior menace visualization, in line with the corporate. It additionally launched a Safety Automation Subscription that gives options similar to premium stories, occasion handlers, and incident response playbooks.

Different Fortinet Safety Cloth AI enhancements enhance menace evaluation and response and streamline community and safety operations by tying FortiAI system into the seller’s core information lake. That is aimed toward serving to safety operations groups make extra knowledgeable choices, reply to threats sooner, and simplify routine and sophisticated duties.

Learn extra about Fortinet

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See also  You should be worried about cloud squatting
TAGGED: cloud, Detection, extends, Fortinet, Network, support, Threat, workflow
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