Neural Network Key Generation for Quantum-Resistant Security
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Solution Overview
Problem
Current key exchange technologies are vulnerable to man-in-the-middle attacks, compromising security due to the development of quantum computing and the limitations of public key cryptography.
Innovation Solution
A machine learning-based key generation method using neural networks for secure key exchange, where two key generation apparatuses generate and verify commit values, match weight values, and generate a session secret key using hash functions and Message Authentication Codes (MAC) to ensure secure communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If public key cryptography is used for key exchange, then key sharing between users is enabled, but security is compromised due to quantum computing development
Solution Approach 1:
The patent changes the fundamental parameter of cryptographic security from algebraic problem-based (public key cryptography) to neural network-based synchronization. This parameter change makes the system resistant to quantum computing attacks while maintaining key exchange functionality, directly resolving the contradiction between current security mechanisms and future quantum threats
Solution Approach 2:
The patent replaces the traditional mechanical/mathematical system of public key cryptography with a neural network-based system. The neural networks synchronize through learning processes rather than relying on algebraic problems, substituting the underlying mechanism to achieve quantum-resistant security
2Productivity
If unauthenticated key exchange is used, then key exchange efficiency is improved, but vulnerability to man-in-the-middle attacks increases
Solution Approach 1:
The patent implements feedback mechanisms where users can identify and verify the other party in the key exchange process. The neural network synchronization process provides inherent feedback through the matching of synchronized states, allowing users to confirm they are exchanging keys with the intended party, thus preventing man-in-the-middle attacks while maintaining efficiency
Solution Approach 2:
The patent introduces neural network synchronization as an intermediary mechanism that enables both efficient key exchange and authentication. The synchronization process itself acts as a mediator that verifies party identity without requiring separate authentication protocols, resolving the contradiction between efficiency and security
Data Source
AI summary
Disclosed herein are a key generation apparatus and method based on machine learning. The key generation method includes generating, by first and second key generation apparatuses, first and second commit values, and uploading the first commit value and the second commit value to an external repository, training, by the first and second key generation apparatuses, a neural network so as to match weight values with each other, sharing, by the first and second key generation apparatuses, the first and second commit values with each other, comparing shared first and second commit values with uploaded commit values, and then verifying the commit values, and when verification of the commit values has succeeded, generating, by the first and second key generation apparatuses, hash values using the matched weight value, verifying whether the hash values are identical to each other, and generating a session secret key based on a result of verification.