Zscaler has patented a method for Exact Data Matching (EDM) to protect customer sensitive data. The system converts data into tokens, monitors user traffic, and takes action based on configured settings. The method involves tokenization, normalization, and inline monitoring to ensure data security. 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 April 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Data matching system for customer sensitive data protection
A recently granted patent (Publication Number: US11973873B2) outlines a method for data matching to identify data content through a multi-tenant cloud-based system. The method involves providing a User Interface (UI) for customers to upload sensitive data and configure specific settings for data matching. Upon receiving customer-specific data, it is converted into tokens such as word, number, alphanumeric, and email tokens. The system then performs inline monitoring of user traffic, tokenization, and normalization of content obtained from monitoring. By detecting the presence of tokens in the monitored content, actions based on the customer's configuration are executed, which may include blocking outbound traffic or reporting the detection of matching tokens.
Furthermore, the method involves distributing tokens across enforcement nodes of the cloud-based system, allowing for the detection of tokens in content processed at these nodes. Each customer has unique sensitive data and configurations for data matching. In the event of updated customer data, the system determines the changes and distributes only the delta tokens across enforcement nodes. Additionally, the tokens are stored as hashes via a one-way hash function to protect sensitive data. Customers perform the one-way hash before providing tokens to the system, ensuring the security and confidentiality of their data throughout the data matching process. The method optimizes scanning of tokens, including looking back at characters for alphanumeric tokens, to enhance the efficiency and accuracy of data matching within the cloud-based system.
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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.
