OneTrust had seven patents in cybersecurity during Q1 2024. OneTrust LLC’s patents filed in Q1 2024 focus on integrating third party computing system functionality into a first party system while analyzing and mitigating risks, updating classifier priorities in a model, and tracking usage of information security entities for tenants on a multi-tenant security platform. These patents aim to improve risk management, data classification, and security assurance processes for organizations. GlobalData’s report on OneTrust gives a 360-degree view of the company including its patenting strategy. Buy the report here.
OneTrust grant share with cybersecurity as a theme is 42% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Systems and methods for mitigating risks of third-party computing system functionality integration into a first-party computing system (Patent ID: US20240098109A1)
The patent filed by OneTrust LLC describes a system and method for integrating third-party computing system functionality into a first-party computing system while managing and mitigating associated risks. The system involves accessing risk data from various tenant computing systems to determine the risk score related to integrating third-party functionality based on past integrations. By analyzing this data, a recommended control set is generated to mitigate identified risks, which can be implemented by the first-party computing system. The system utilizes a combination of rules-based and machine-learning models to generate control recommendations based on the common control set and mitigation weights determined from the risk data.
Furthermore, the method involves identifying risks associated with integrating third-party functionality, accessing control data from multiple computing systems that have previously integrated the same functionality, and determining a common control set to mitigate these risks. By processing risk scores and control data, the system generates control recommendations using rules-based models. The implementation of these recommendations can involve modifying the third-party functionality or disabling it, with the option to generate a user interface displaying the recommended controls. Overall, the system aims to provide a structured approach to integrating third-party computing system functionality into a first-party system while effectively managing and mitigating associated risks based on historical data and control measures implemented by other systems.
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