Generative AI Authentication Policy Recommendations

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Solution Overview

Problem

Client organizations struggle to configure optimal authentication policies for their applications, often resulting in sub-optimal configurations that compromise security and user experience.

Innovation Solution

An identity management system utilizes generative AI to predict suitable authentication policy configurations for client organizations, providing recommendations and insights into the impact of implementing these policies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If administrators manually configure authentication policies without guidance, then they have full control over configuration, but the configurations are sub-optimal and leave organizations vulnerable to security risks

Engineering Contradiction:

Improvesecurity postureVSAvoidconfiguration ease

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system enables authentication policies to configure themselves automatically through machine learning models that analyze application characteristics and generate optimal policy recommendations without requiring administrator expertise in security best practices

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual administrator configuration work with an automated machine learning-based system that generates authentication policy recommendations, substituting human judgment with algorithmic analysis of application data and security requirements

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If complex authentication policies are implemented to improve security, then security posture improves, but user experience deteriorates due to access issues

Engineering Contradiction:

Improvesecurity assuranceVSAvoiduser experience

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system dynamically adjusts authentication policy parameters based on application-specific characteristics and organizational context, optimizing the balance between security requirements and user experience for each individual application rather than applying uniform complex policies

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent applies authentication policies selectively based on risk assessment, implementing stronger authentication only where necessary rather than uniformly across all applications, thus maintaining security where needed while preserving user experience where possible

Inventive Principle:

Principle #16Partial or excessive action

3Ease of operation

If generic authentication policies are applied to all applications, then configuration is simplified, but the policies do not meet best practices for specific applications

Engineering Contradiction:

Improveconfiguration simplicityVSAvoidbest practices compliance

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system generates authentication policies tailored to specific application characteristics and organizational contexts, ensuring that each application receives customized policy recommendations that meet best practices for its particular requirements rather than applying generic policies

Inventive Principle:

Principle #3Local quality

4Adaptability or versatility

If administrators lack awareness of best practices, then configuration flexibility is maintained, but sub-optimal configurations result leaving organizations vulnerable

Engineering Contradiction:

Improveconfiguration flexibilityVSAvoidsecurity vulnerability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent introduces an intermediary machine learning system that translates application characteristics and organizational requirements into secure authentication policy recommendations, bridging the gap between administrator flexibility needs and security best practices compliance

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250112961A1Techniques for generating policy recommendations and insights using generative ai

Publication Date: 2025.04.03 OKTA INC

AI summary

Methods, systems, devices, and computer-readable media for generating authentication policy recommendations and insights using generative AI are described. An authentication policy recommendation system associated with an identity management system may receive a request from a client organization for an authentication policy configuration recommendation for an application associated with the client organization. One or more recommended authentication policy rules may be generated for the application using a machine learning model (such as a large-learning model). The model may output the authentication policy rules in a machine-readable format. Based on an analysis of applying information about the client organization to the model-generated recommended authentication policy rule to generate a context-specific recommended authentication policy rule, an impact of implementing the context-specific recommended authentication policy rule may be determined and output. The impact of implementing the context-specific recommended authentication policy rule may be determined in advance of implementing the recommended authentication policy rule.