Deterministic Data Perturbation for Repeatable Privacy-Preserving Services

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Solution Overview

Problem

Existing data services risk exposing sensitive information by revealing personally identifying data, especially when dealing with small and changing data sets, and they often provide inconsistent results due to unpredictable perturbation methods.

Innovation Solution

A data service system that generates a seed for each request using a hash function, which seeds a pseudorandom number generator to produce consistent perturbations, ensuring repeatable and privacy-preserving results without storing state information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If random perturbation is applied to data results, then privacy protection is improved, but result consistency and repeatability deteriorate

Engineering Contradiction:
Improveprivacy protectionVSAvoidresult consistency
Core Design Contradiction:
Object-affected harmful factorsVSReliability

Solution Approach 1:

The system performs preliminary action by generating a seed value before applying perturbation. The seed is derived from hashing the input data and request parameters, ensuring that the same input always produces the same seed, which in turn produces the same perturbed result. This preliminary seed generation enables both privacy protection through perturbation and result consistency through determinism.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary mechanism - the seed value - that mediates between the random perturbation process and the requirement for consistent results. The seed acts as a deterministic random number generator seed that produces the same sequence of random numbers whenever the same input data is processed, thus maintaining both privacy (through perturbation) and reliability (through consistency).

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If state information is stored to ensure repeatability, then result consistency is improved, but storage requirements and system complexity increase

Engineering Contradiction:
Improveresult repeatabilityVSAvoidstorage requirements
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The system performs self-service by generating the seed deterministically from the input data itself using a hash function. Instead of requiring external state storage or memory to track previous seeds, the system uses the input data's own characteristics (through hashing) to generate the seed. This eliminates the need for persistent storage while maintaining repeatability - the same input data always generates the same seed, which always produces the same perturbed result.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical/storage-based approach to ensuring repeatability with a computational/deterministic approach. Instead of storing state information in memory or database to track previous results and reproduce them, the system uses a deterministic algorithm (hash function followed by seeded random number generation) that inherently produces consistent results without requiring any storage infrastructure.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If deterministic seed generation is used, then result repeatability is improved, but privacy protection may deteriorate due to predictability

Engineering Contradiction:
Improveresult repeatabilityVSAvoidprivacy protection
Core Design Contradiction:
ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system applies parameter changes by using a cryptographic hash function to transform the input data into a seed value. The hash function acts as a one-way transformation that preserves the deterministic relationship (same input → same seed → same perturbed result) while making the seed computationally infeasible to reverse or predict from the output. This parameter transformation maintains repeatability while strengthening privacy protection against prediction attacks.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentUS12488139B2Data services with privacy preservation and repeatability
Publication Date: 2025.12.02 INTUIT INC
  • US12488139B2 patent drawing
  • US12488139B2 patent drawing
  • US12488139B2 patent drawing

AI summary

A processor may receive a request to perform an operation. The processor may generate a seed derived from data required to perform the operation. The processor may generate a perturbation based on inputting the seed into a pseudorandom number generator. The processor may generate the actual result based on performing the operation. The processor may generate a perturbed result, wherein generating the perturbed result may comprise performing a second operation based on the actual result and the perturbation. The processor may return the perturbed result in response to the request.