Royal Bank of Canada had five patents in big data during Q2 2024. The Royal Bank of Canada filed patents in Q2 2024 for a system processing data in a Trusted Execution Environment, a computational approach for interactive offers in payment processes, concealing threat detection in website code, and density ratio estimation using a transformer-based architecture to control confounding bias in data. GlobalData’s report on Royal Bank of Canada gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Royal Bank of Canada had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: System and method for secure electronic transaction platform (Patent ID: US20240184898A1)
The patent filed by the Royal Bank of Canada describes a system for processing data within a Trusted Execution Environment (TEE) of a processor. The system includes a trust manager unit for verifying the identity of a partner and issuing a communication key, interfaces for receiving encrypted data from the partner, a secure database for storing encrypted data with a storage key, and a recommendation engine for decrypting and analyzing the data to generate recommendations. The system ensures the security and integrity of the data processing subsystem by segregating the data storage region and data processing subsystem storage region within a protected memory region that is encrypted and isolated from the operating system or kernel system.
Furthermore, the system involves a secure processor that receives third-party data sets, digitally signed by corresponding computing devices, and records them in the protected memory region. The segregated data processing subsystem can generate output data structures based on the stored data sets, utilizing a machine learning data model architecture. The system also includes features such as generating public/private key pairs, encrypting the memory region using a storage encryption key accessible only by the TEE, conducting remote attestation processes, and distributing parameter update data structures to refine the machine learning model architecture. Overall, the system ensures data security, privacy, and integrity within the TEE while enabling efficient data processing and analysis for generating recommendations.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
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.
