AI-Driven Network Architecture Diagram Generation

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Solution Overview

Problem

Current computing network architecture designs are often vulnerable to security threats and compliance issues due to the time-consuming process of identifying and addressing vulnerabilities and regulations post-design, leading to costly re-designs and delays in mitigating emerging threats.

Innovation Solution

An AI-driven system that generates computing network architecture diagrams using data from vulnerability and regulation databases, incorporating machine learning to leverage previous designs and make real-time adjustments to mitigate vulnerabilities and ensure compliance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If security vulnerability assessment and compliance review are performed after network architecture design is completed, then the design can be scrutinized for security issues, but the process becomes time-consuming and requires numerous revisions

Engineering Contradiction:

Improvesecurity vulnerability assessmentVSAvoiddesign revision time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs security vulnerability assessment and compliance review during the network architecture design phase rather than after completion. The AI model evaluates security requirements, identifies potential vulnerabilities, and ensures compliance with regulations as the design is being created, enabling preventive action rather than corrective action later

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops where the AI model constantly evaluates the network architecture design against security requirements and compliance regulations during the design process. This real-time feedback allows designers to make immediate adjustments without requiring multiple revision cycles after the design is completed

Inventive Principle:

Principle #23Feedback

2Reliability

If security vulnerability assessment is performed after network design construction, then security issues can be detected, but costly network re-design is required

Engineering Contradiction:

Improvesecurity vulnerability detectionVSAvoidnetwork re-design cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The AI model performs security vulnerability detection and compliance verification during the design construction phase, identifying and addressing security issues before the network architecture is finalized. This preliminary security assessment prevents the need for costly re-design later by incorporating security requirements from the outset

Inventive Principle:

Principle #10Preliminary action

3Reliability

If there is a delay between detecting new security vulnerabilities and implementing corrective actions, then emerging threats can be identified, but the computing network remains exposed to serious security threats

Engineering Contradiction:

Improvesecurity vulnerability detectionVSAvoidcorrective action implementation time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements continuous monitoring and evaluation of the network architecture against emerging security threats. The AI model continuously updates its assessment as new vulnerabilities are discovered, maintaining an ongoing security evaluation rather than periodic checks, which enables immediate identification and implementation of corrective actions without delay

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The AI-powered system automatically detects new security vulnerabilities and generates corrective action recommendations without requiring manual intervention. The system self-updates its security assessments based on emerging threats and can automatically implement certain corrective measures, reducing the time between vulnerability detection and corrective action implementation

Inventive Principle:

Principle #25Self-service

4Measurement precision

If traditional manual methods are used to ensure network security and compliance, then detailed review can be performed, but the process is time-consuming and requires numerous design revisions

Engineering Contradiction:

Improvesecurity review thoroughnessVSAvoiddesign completion speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system replaces manual security review processes with an AI-powered automated evaluation system. The AI model performs comprehensive security assessments and compliance checks that are both thorough and rapid, eliminating the need for time-consuming manual review while maintaining high precision in identifying security issues and ensuring regulatory compliance

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11310259B2Cybersecurity architectural network based on artificial intelligence

Publication Date: 2022.04.19 BANK OF AMERICA CORP

AI summary

A system for using artificial intelligence to generate a computing network architecture diagram based on user inputs, applicable vulnerability/cyber threat data and internal/external compliance/audit regulation data. In addition, machine-learning techniques may be used that leverage previously implemented computing network architectures. The computing network architecture diagram may be generated absent a baseline diagram or the user inputs may define at least a portion of an initial/baseline network architecture diagram that is modified based on the vulnerability/cyber threat data, the internal/external compliance/audit regulation data and/or the previously implemented computing network architectures. In additional embodiments of the invention, new/emerging vulnerabilities and cyber threats are detected, and in real-time response, adjustments to the computing network infrastructure and determined and implemented.