Zscaler had five patents in artificial intelligence during Q2 2024. Zscaler Inc filed patents in Q2 2024 for systems and methods related to analyzing log data to determine user-application relations and providing access policies based on app-segments, identifying incorrect labels for machine learning security models, and learning from mistakes to improve detection rates of ML models. These innovations aim to enhance security measures and improve the efficiency of machine learning processes. 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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Zscaler had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Generating zero-trust policy for application access utilizing knowledge graph based application segmentation (Patent ID: US20240205231A1)
The patent filed by Zscaler Inc. describes systems and methods for obtaining log data related to user application usage in an enterprise, analyzing this data to determine relationships between users and applications, grouping applications into segments based on these relationships, and providing access policies based on these segments. The invention involves training an embedding model to produce vector representations of users, applications, and their relationships, transforming data into feature vectors for clustering, and incorporating metadata such as user departments and application details. The system also includes monitoring access policies over time, adjusting segments based on ongoing data, and ensuring the access policy meets quality standards.
The patent further details a method for implementing the described systems and methods, including steps for obtaining log data, analyzing user-application relationships, grouping applications into segments, and establishing access policies based on these segments. This method involves training an embedding model, transforming data into feature vectors for clustering, and considering metadata like user departments and application details. Additionally, the method includes determining user groups based on data analysis, monitoring access policies over time, and adjusting segments as needed to meet quality thresholds. Overall, the patent outlines a comprehensive approach to managing access policies for enterprise applications based on user behavior and relationships.
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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.
