32-Dimensional Financial Security Architecture for Adaptive Threat Control

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Solution Overview

Problem

Traditional financial security systems are inadequate in addressing advanced persistent threats, multi-vector attacks, and insider threats, particularly in decentralized finance, due to their limited-dimensional approaches.

Innovation Solution

A 32-dimensional security and risk control system incorporating encryption, isolation, redundancy, AI-based risk control, virtual wormhole and hive architecture, and smart contracts to provide layered and adaptive protection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional limited-dimensional security systems are used, then system simplicity is maintained, but security effectiveness against advanced threats deteriorates

Engineering Contradiction:

Improvesecurity effectivenessVSAvoidsystem dimensionality

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a 32-dimensional security architecture that expands traditional security from limited dimensions (encryption, access control) to comprehensive multi-dimensional coverage including data transmission, storage, identity authentication, transaction integrity, and AI-based threat detection across all layers of financial operations

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The security system is segmented into 32 distinct dimensional layers, each addressing specific security aspects such as encryption protocols, network isolation, redundancy mechanisms, and AI risk control models, allowing targeted security measures for different threat vectors

Inventive Principle:

Principle #1Segmentation

2Reliability

If multi-layered encryption and security protocols are implemented, then data protection is improved, but processing speed deteriorates

Engineering Contradiction:

Improvedata protectionVSAvoidprocessing speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

Security measures such as encryption protocols, integrity checks, and authentication mechanisms are implemented in advance during data transmission and storage operations, allowing security verification to occur before critical operations rather than adding post-processing overhead

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces traditional mechanical security verification methods with AI-based risk control models and machine learning algorithms that can analyze and verify security conditions in real-time with significantly higher speed and accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If AI-based real-time risk control is implemented, then threat detection capability is improved, but computational resource consumption increases

Engineering Contradiction:

Improvethreat detection capabilityVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The AI risk control models are deployed in a distributed architecture where each node performs local risk analysis and only communicates essential findings to central coordination, allowing the system to self-manage computational loads and reduce overall resource consumption while maintaining detection precision

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250209466A132-Dimensional Financial Security and Risk Control System

Publication Date: 2025.06.26 BEI FURONG

AI summary

This invention introduces a 32-dimensional financial security and risk control system designed to address advanced cyber threats and ensure comprehensive protection for financial platforms. It integrates multi-layered encryption, AI-based dynamic risk control, virtual wormholes, and a hive network architecture to secure data transmission, identity verification, and transaction integrity. The system employs smart contracts and AI models to dynamically adjust risk parameters and execute risk mitigation strategies, providing an adaptive and highly secure financial infrastructure.