Zscaler. has been granted a patent for a method that enhances early ransomware detection by monitoring message traffic through secure gateways. The technique employs statistical and behavioral anomaly detection, generating alerts to help operators identify and respond to potential ransomware attacks, particularly in cloud environments and Virtual Local Area Networks (VLANs). GlobalData’s report on Zscaler gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Zscaler, was a key innovation area identified from patents. Zscaler's grant share as of July 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Early detection of ransomware using network traffic analysis
The granted patent US12074906B1 outlines a method for enhancing ransomware protection within a Virtual Local Area Network (VLAN). The method involves deploying at least one gateway that connects to multiple client endpoint devices. Each gateway is equipped with a security appliance functioning as a DHCP relay, which assigns itself as the default gateway for the client devices after receiving a DHCP response. Notably, the security appliance modifies the subnet mask to 255.255.255.255, ensuring it serves as the default gateway. Additionally, the gateway transmits a copy of its message traffic to an early ransomware detection system, which analyzes the network traffic for both behavioral and statistical anomalies indicative of potential ransomware attacks.
The patent further specifies that the early ransomware detection system can be cloud-based and emphasizes the importance of analyzing statistical anomalies to identify unusual traffic patterns associated with various phases of a ransomware attack. Behavioral anomalies, which may include specific patterns linked to ransomware, are also monitored. To enhance detection capabilities, the method incorporates a machine learning engine that performs advanced analysis on the collected anomaly data, utilizing multi-factor classification techniques. This engine is specifically trained for early ransomware detection and is capable of generating visualizations and alerts to signal the onset of a potential ransomware attack, thereby providing a proactive approach to network security within VLANs.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
