OneTrust had eight patents in big data during Q2 2024. OneTrust LLC’s patents in Q2 2024 focus on methods, systems, and devices for identifying data processing activities, generating insightful user interfaces displaying data processing activity components, and prompting data subjects to consent to data processing. These inventions aim to map target data within computing systems without exposing it to potential data-related incidents, utilizing techniques such as data asset scanning, prediction generation, application code scans, and consent capture systems. The disclosed systems also enable the detection of changes in data processing activity components and data categories between scans of different versions of application code. 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 big data 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 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, and identifying data processing activities based on correlations with known data elements and flows. The system utilizes machine-learning models to predict data associations and flows, enabling actions to be performed based on identified processing activities, such as ensuring secure handling of personal data and managing risks associated with data processing.
The patent also covers the use of classifiers to generate predictions for data assets and pairs of assets, determining the likelihood of data flow between assets, and identifying risks associated with data processing activities. Additionally, the system allows for actions to be taken in response to requests related to target data, such as accessing, revising, or deleting data. Furthermore, the system includes provisions for injecting test data to analyze data flows and utilizes rules-based models to identify data flows between assets. Overall, the method and system described in the patent aim to enhance data processing activities by leveraging machine learning and predictive models to ensure efficient and secure handling of data assets within a computing 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.
