OneTrust had two patents in artificial intelligence during Q2 2024. OneTrust LLC’s patents focus on methods and systems for identifying data processing activities associated with data assets and mapping the existence of target data within computing systems without exposing it to potential data-related incidents. The inventions involve scanning data assets, generating predictions for data flows, and identifying data processing activities based on correlations with known data elements. Additionally, the patents include receiving source datasets, anonymizing data samples, generating review datasets, and sending them to review computing systems to protect target data. GlobalData’s report on OneTrust gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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OneTrust had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for identifying data processing activities based on data discovery results (Patent ID: US20240160747A1)
The patent filed by OneTrust LLC describes a method and system for identifying data processing activities associated with various data assets based on data discovery results. The method involves scanning data assets to detect a subset associated with target data, generating predictions for data flow between pairs of assets, identifying data processing activities based on correlations with known data elements, subsets, and data flows, and performing actions based on the identified activities. The system utilizes machine-learning models to predict data associations, determine secure data processing, and manage risks associated with data handling activities.
The patent further details the use of classifiers to generate predictions for data assets and pairs of assets, the identification of personal data handling activities, and the performance of actions such as accessing, revising, or deleting target data. Additionally, the system can identify risks associated with data processing activities, communicate these risks, and take actions to mitigate them, such as suspending activities or encrypting data. The method also involves injecting test data to analyze data flows between assets and utilizes rules-based models to identify data flows. Overall, the patent outlines a comprehensive approach to data asset identification, data flow prediction, and data processing activity management using machine learning and rules-based models.
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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.
