Verified Templates for Secure Data Processing

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Solution Overview

Problem

Existing data processing systems face challenges in securely executing machine-learning models and algorithms across different parties without disclosing sensitive data or model information, particularly in scenarios where there is distrust or wariness among data owners and algorithm providers, necessitating a mechanism for secure validation and execution of computer instructions based on agreed-upon constraints.

Innovation Solution

A system and method utilizing verified templates and blockchain technology to securely process data, where executable computer instructions are validated and executed, ensuring that data owners' sensitive information remains protected and algorithm providers' models are kept secret, by using encrypted inputs and threshold data for prediction comparisons, and allowing parties to agree on data usage conditions without direct access to each other's data or code.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data owners share sensitive data with algorithm providers for machine-learning operations, then the utility and productivity of data processing is improved, but the security and privacy of sensitive information deteriorates

Engineering Contradiction:
Improvedata processing utilityVSAvoiddata security
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The patent introduces a trusted intermediary system that mediates between data owners and algorithm providers. This intermediary validates executable instructions against pre-agreed templates stored on a blockchain, ensuring that data processing operations conform to authorized parameters without requiring direct data sharing. The intermediary acts as a verifier that enables productive collaboration while maintaining security boundaries.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Adaptability or versatility

If algorithm providers access data owners' sensitive data for model training and execution, then the functionality and adaptability of machine-learning operations is improved, but the loss of information control and privacy deteriorates

Engineering Contradiction:
Improvemachine-learning functionalityVSAvoiddata privacy control
Core Design Contradiction:
Adaptability or versatilityVSLoss of information

Solution Approach 1:

The patent segments the data processing workflow into distinct validated components: pre-agreed templates defining authorized operations, executable instructions that must conform to templates, and blockchain-stored verification data. This segmentation allows algorithm providers to access and process data within strictly defined boundaries, enabling versatile machine-learning functionality while preventing unauthorized information access through systematic validation at each processing stage.

Inventive Principle:
Principle #1Segmentation

3Reliability

If parties establish trust mechanisms through blockchain validation of executable instructions, then the reliability and security of data processing is improved, but the device complexity and operational overhead increases

Engineering Contradiction:
Improveprocessing securityVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements preliminary action by requiring parties to pre-agree on and store validation templates on the blockchain before any data processing occurs. These templates define all authorized operations in advance. During actual processing, the system only needs to validate executable instructions against these pre-established templates, significantly reducing real-time complexity while maintaining high security and reliability through upfront preparation.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP4165825B1Verified templates
Publication Date: 2024.12.25 VIA SCIENCE INC
  • EP4165825B1 patent drawingFigure 1
  • EP4165825B1 patent drawingFigure 2
  • EP4165825B1 patent drawingFigure 3

AI summary

A computing system that facilitates approval and validation of executable code between parties. A template including executable code and specifying certain operations and functions to be performed on protected data, as well as constraints thereto, may be verified and agreed upon by parties. The verified template and/or a hash of the verified template may be stored on a blockchain. Prior to execution of the code certain parameters within the template may be filled and validated by a system that will execute the code. A contract, which too may be agreed upon and stored on the blockchain, may also include other terms governing the parties. The filled template may also be validated, and compared against a blockchain version of the template, by the parties prior to execution of the code and prior to access being granted to protected data. Such verifications and validations ensure that data is only operated on, using a secure system, within the parameters as agreed upon by the parties.