The Royal Bank of Canada has filed a patent for systems and methods to generate access entitlements to networked computing resources. The patent describes a system that receives an entitlement request, generates an entitlement prediction based on an entitlement model and hierarchical levels, and transmits a signal for granting access to a networked computing resource. GlobalData’s report on Royal Bank of Canada gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Royal Bank of Canada, social commerce was a key innovation area identified from patents. Royal Bank of Canada's grant share as of September 2023 was 87%. Grant share is based on the ratio of number of grants to total number of patents.

The patent is filed for a system for generating access entitlements to networked computing resources

Source: United States Patent and Trademark Office (USPTO). Credit: Royal Bank of Canada

A recently filed patent (Publication Number: US20230319055A1) describes a system for generating access entitlements to networked computing resources. The system includes a processor and memory that stores instructions for configuring the processor. When executed, these instructions allow the processor to receive an input data set representing an entitlement request associated with a user identifier. The system then generates an entitlement prediction based on an entitlement model and at least one hierarchical level. The entitlement model defines a cluster representation of entitlement similarity, and the prediction is based on similarity relationships corresponding to the hierarchical level. Finally, the system transmits a signal representing the entitlement prediction for granting downstream access to a networked computing resource.

The entitlement prediction in the system can define either an entitlement associated with the user identifier to provide access to the networked computing resource or a user role among a group of users associated with user identifiers. The cluster representation of entitlement similarity is based on nodes representing user identifiers associated with prior-identified access entitlements or prior-identified access entitlement similarities among corresponding user identifiers.

The system also includes the capability to generate an attestation value that quantifies the entitlement prediction relative to nodes of the cluster representation associated with the prior-identified access entitlements. The system can then determine if the attestation value satisfies a trigger condition. Based on the attestation value, the entitlement prediction includes an indication of whether to propagate the access entitlement to provide access to the networked computing resource.

The processor in the system can determine the hierarchical level corresponding to the entitlement request, which is associated with a feature of the networked computing resource. The entitlement model used in the system includes tunable parameters for generating the cluster representation based on the hierarchical level. The model can be based on agglomerative clustering among nodes and similarity relationships associated with existing access entitlements or on Markov clustering associated with a graph-based representation of entitlement data sets.

In addition to the system, the patent also describes a method for generating access entitlements to access-controlled computing resources. The method includes receiving an input data set representing an entitlement request, generating an entitlement prediction based on an entitlement model and hierarchical level, and transmitting a signal representing the entitlement prediction for granting downstream access to a networked computing resource.

Overall, this patent presents a system and method for generating access entitlements to networked computing resources based on an entitlement model and hierarchical levels, allowing for efficient and accurate access control.

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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.