AI Security Access Management Using Machine Learning Models

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Solution Overview

Problem

Existing security access management systems face challenges in efficiently granting and renewing security accesses, often leading to improper access and resource wastage due to unnecessary security access grants and renewals.

Innovation Solution

A system utilizing artificial intelligence, specifically machine learning models, to manage security access by determining user eligibility based on user profiles and generating certification information for security access renewal or revocation based on user behavior.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If security access is granted based on manual review and renewal processes, then security personnel can verify user eligibility, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:

Improvesecurity access control accuracyVSAvoidaccess grant and renewal processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical review processes with automated machine learning models that analyze user profiles and behavior data. The first ML model determines initial security access eligibility, while the second ML model assesses renewal eligibility based on behavior information, eliminating the need for manual security personnel review and significantly reducing processing time while maintaining or improving accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service security access management by automatically evaluating user eligibility and renewal requests without requiring security personnel intervention. The ML models autonomously make access decisions based on user profiles and behavior data, allowing the security access system to serve itself without external manual input

Inventive Principle:

Principle #25Self-service

2Productivity

If security access is renewed for all users automatically, then administrative overhead is reduced, but resource wastage increases due to unnecessary access grants

Engineering Contradiction:

Improvesecurity access management efficiencyVSAvoidresource wastage from unnecessary access

Core Design Contradiction:

ProductivityVSLoss of substance

Solution Approach 1:

The patent implements a feedback mechanism where the second machine learning model continuously evaluates user behavior information to determine renewal eligibility. The system monitors user behavior patterns and feeds this information back into the renewal decision process, automatically revoking access for users who no longer meet eligibility criteria and maintaining access only for those who do, thereby preventing resource wastage while improving management efficiency

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system changes the decision parameters for security access renewal by using behavior information and ML model assessments instead of automatic renewal for all users. The second ML model dynamically adjusts access status based on updated user profiles and behavior data, ensuring that resource allocation matches actual user needs and preventing wastage from unnecessary access grants

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If manual review processes are used for security access decisions, then detailed human judgment can be applied, but the complexity and cost of the system increases

Engineering Contradiction:

Improveuser eligibility assessment accuracyVSAvoidsecurity management system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces complex manual human review processes with machine learning models that automatically assess user eligibility. The first ML model evaluates initial access requests by analyzing user profiles, while the second ML model assesses renewal eligibility based on behavior information, providing precise automated decisions without the operational complexity and costs associated with manual human review systems

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250141874A1Systems and methods for using artificial intelligence to facilitate security access management

Publication Date: 2025.05.01 CAPITAL ONE SERVICES LLC

AI summary

A system obtains a user profile that is associated with a user. The system determines, based on the user profile, and by using a first machine learning model, that the user is to be granted a security access and thereby causes the security access to be granted to the user. The system obtains, based on causing the security access to be granted to the user, user behavior information associated with the user. The system generates, based on the user behavior information, and by using a second machine learning model, certification information that indicates whether the security access is to be renewed or revoked. The system thereby causes the security access to be renewed when the certification information indicates that the security access is to be renewed, or the security access to be revoked when the certification information indicates that the security access is to be revoked.