Thursday, March 28, 2024
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Fortinet Acquires Cloud-Based Threat Analytics Company ZoneFox

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Fortinet completed the acquisition of ZoneFox Limited, a privately-held cloud-based insider threat detection and response company headquartered in Edinburgh, Scotland. The acquisition further enhances the Fortinet Security Fabric and strengthens Fortinet’s existing endpoint and SIEM security business by providing customers with Deepervisibility into endpoints and associated data flow and user behaviour, both on and off the network. Machine learning capabilities able to distill billions of events per day into high-quality threat leads to uncover blind spots and alert users of suspicious activities.

A uniquecloud-based architecture that captures essential data around five core factors – user, device, resource, process, and behavior – to analyze and configure policies easily. Full forensics timeline recording of information, combined with a simple search interface that helps analysts quickly determine the actions needed to boost an enterprise’s security posture. A zero-configuration agent that is easy and fast to deploy; the solution can scale up to support over 10,000 agents without performance loss. Out-of-the-box support for GDPR, ISO 27001, HIPAA and PCI DSS, with “ready-to-go” policies

Ken Xie, founder, chairman of the board and chief executive officer, Fortinet, said, “Enterprise organizations are experiencinga dramatic increase in the number of endpoints and users accessing data and cloud resources, which is also increasing the need to defend against insider threats. In fact, 30 percent of breaches involved insiders acting negligently or maliciously according to the 2018 Verizon Data Breach Investigations Report. By combining ZoneFox’s cloud-based threat-hunting technology with Fortinet’s existing endpoint and SIEM security offerings, we are well positioned to provide our customers with an integrated approach to defend against insider threats, eliminate network blind spots and protect today’s expanding attack surface with automation and machine learning.”

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