Zscaler has been granted a patent for systems and methods that involve automatically generating microsegments in a network based on network communication information about hosts and applications. These microsegments allow hosts to locally control communications based on rules for network communication. 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 February 2024 was 70%. Grant share is based on the ratio of number of grants to total number of patents.
Network microsegmentation for controlling local communications based on traffic analysis
A recently granted patent (Publication Number: US11902145B2) discloses a computer-readable storage medium containing code for programming a computing system to perform various steps. These steps include receiving network communication information about hosts and applications in a network, analyzing this information to identify different types of traffic, such as server-to-server, application-to-server, and application-to-application traffic, and automatically generating microsegments in the network based on this analysis. Each microsegment is a grouping of resources, including hosts and applications, with specific rules for network communication. These microsegments are then provided to hosts to enable them to locally allow or block communications based on the defined rules.
Furthermore, the patent describes additional steps that can be taken post-deployment of microsegments, such as observing communication between hosts to detect any unassigned communication paths that are blocked due to the absence of an associated microsegment. In such cases, a new microsegment can be created to address these communication paths. The automatic generation of microsegments is facilitated by a trained machine learning model, which is trained based on labeled network communications categorized as healthy (permitted) or unhealthy (blocked). The network communication information used for analysis includes various data points like IP addresses, ports, host names, unique identifiers, and application names, as well as flow objects with data on both sides of a particular application. The machine learning model used for generating microsegments can be trained via unsupervised learning using these flow objects, and each host is identified by a unique fingerprint.
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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.
