Microsoft technology licensing, llc (20240135009). Access decision management system for digital resources simplified abstract

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Access decision management system for digital resources

Organization Name

microsoft technology licensing, llc

Inventor(s)

Darren Doyle of Wicklow (IE)

Terry Farrell of Dublin (IE)

Access decision management system for digital resources - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240135009 titled 'Access decision management system for digital resources

Simplified Explanation

The patent application describes a data processing system that receives access requests from clients to access content items managed by a content access management platform. The system analyzes access control information using a machine learning model to determine whether to grant or deny access to the content item.

  • Receiving access requests from client devices
  • Analyzing access control information using a machine learning model
  • Determining automatic access decisions based on the analysis
  • Notifying the content requestor of the access decision

Potential Applications

The technology described in the patent application could be applied in various industries such as digital content distribution, online streaming services, and secure data access management systems.

Problems Solved

This technology helps streamline the access control process for content items, ensuring that only authorized users are granted access while maintaining security and privacy.

Benefits

The system provides a more efficient and automated way to manage access control for content items, reducing the need for manual intervention and improving overall security measures.

Potential Commercial Applications

One potential commercial application of this technology could be in the development of secure content sharing platforms for businesses, where sensitive information needs to be accessed by authorized personnel only.

Possible Prior Art

One possible prior art could be existing access control systems that use machine learning algorithms to analyze user behavior and determine access permissions.

Unanswered Questions

How does the system handle access requests from multiple clients simultaneously?

The patent application does not provide details on how the system manages access requests from multiple clients at the same time. This could be a potential area for further exploration in terms of scalability and performance optimization.

What measures are in place to prevent unauthorized access to the content items?

The patent application focuses on the analysis of access control information to determine access decisions, but it does not elaborate on the specific security measures in place to prevent unauthorized access. Further information on encryption protocols, authentication methods, and data protection mechanisms would be beneficial for a comprehensive understanding of the system's security features.


Original Abstract Submitted

a data processing system implements receiving an access request from the client device of a content requestor to access a content item for which access to the content item is managed by a content access management platform and obtaining access control information. the access control information comprising information associated with a content owner associated with the content item, information associated with the content requestor, and information associated with the content item. the system further implements analyzing the access control information using a first machine learning model trained to analyze the access control information and to output an access determination score, the access determination score representing a level of certainty that the content requestor should be granted access to the content item, determining an automatic access decision to grant or deny the access request based on the access determination score, and notifying the content requestor whether the access request has granted or denied based on the automatic access decision.