Dynamic Child-Tensor Encryption for Secure Data Exchange
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Solution Overview
Problem
Existing methods for securing data objects in modern communication environments are not foolproof, as static authentication data can be hacked or compromised, rendering them insecure.
Innovation Solution
A method utilizing genetic algorithms and heuristic artificial intelligence to generate and evolve dynamically changing child tensors for encryption and decryption, ensuring secure data exchange by verifying the genetic relationship between parent and child tensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static authentication data (passwords, pins) are used to protect data objects, then ease of operation is improved, but reliability deteriorates due to vulnerability to hacking and compromise
Solution Approach 1:
The patent applies dynamics by transforming static authentication data into dynamic, continuously evolving authentication objects. The authentication objects change over time through genetic algorithm operations (crossover, mutation, selection), ensuring that the authentication data is never static and cannot be compromised by traditional hacking methods. This resolves the contradiction by making the system both secure (reliable) and operable (easy to use) through continuous evolution rather than static protection.
Solution Approach 2:
The patent changes the parameters of authentication data from fixed values to dynamically evolving structures. By applying genetic operations that modify the authentication objects' parameters continuously, the system maintains ease of operation while dramatically improving reliability. The authentication objects undergo parameter changes through crossover and mutation operations, making them unpredictable and resistant to unauthorized access.
2Reliability
If genetic algorithms are used to evolve authentication data, then reliability is improved through dynamic changes, but device complexity increases
Solution Approach 1:
The patent applies self-service by enabling the authentication objects to evolve automatically through genetic algorithms without requiring manual intervention. The system performs crossover, mutation, and selection operations autonomously, reducing the need for complex manual management while maintaining high reliability. This resolves the complexity issue by allowing the system to self-manage its security evolution.
Solution Approach 2:
The patent implements feedback mechanisms where the authentication objects are continuously assessed and evolved based on their security performance. The genetic algorithm uses feedback from the authentication process to guide further evolution, improving reliability while managing complexity through iterative optimization rather than static complex structures.
3Reliability
If authentication objects continuously evolve through genetic algorithms, then security against unauthorized access is improved, but loss of time increases due to generation and verification processes
Solution Approach 1:
The patent applies preliminary action by pre-generating and storing authentication objects in a database before they are needed for authentication. This allows the system to quickly retrieve and verify pre-evolved authentication objects rather than generating them in real-time, thus maintaining high unpredictability and security while reducing the time loss during actual authentication operations.
Solution Approach 2:
The patent uses copying by creating multiple instances of authentication objects through the genetic algorithm's population-based approach. Multiple authentication objects can be generated and stored in advance, allowing rapid selection and verification during authentication without time-consuming real-time generation, thereby balancing security with operational efficiency.
Data Source
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AI summary
A method, a security program (10), a computer-readable data carrier (12), a security application (6) , a user device (3), and a server device (4) for securing a data object (D), in particular for communications between a first participant (A) and a second participant (B), are provided, the method comprising the steps of generating a at least one parent tensor (V, W) containing population elements (O) of at least one parent population (L) at a secure location, such as a secure server (4); deriving a first child tensor (X) and a second child tensor (Y) containing population elements (O) of a first child population (P), and a second child population (P) respectively; providing the first child tensor (X) to the first participant (A) and the second child tensor (Y) to the second participant (B); encrypting the data object (D) by means of the first child tensor (X) by the first participant (A); sending the encrypted data object (D)to the second participant (B); sending the second child tensor (Y) from the second participant (B) to the secure location; assessing at the secure location, whether the second child tensor (Y) is derived from the at least one parent tensor (V, W); providing the first child tensor (X) to the second participant (B) for enabling decryption of the data object (D) by means of the first child tensor (X) if the assessment is positive.