Homomorphic Encryption Layout for Categorical Data Statistics

Solution Overview

Problem

Existing homomorphic encryption methods for categorical data are inefficient and resource-intensive due to the need for separate filtering operations during statistical analysis, which increases computational burden.

Innovation Solution

An apparatus and method that generate a homomorphic encrypted message by creating a categorical column and mask columns for each class, allowing direct statistical operations without additional filtering, using a processor to combine these columns with numerical data for efficient operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If separate filtering operations are performed during statistical analysis of homomorphic encrypted categorical data, then accurate statistical results can be obtained, but computational burden and resource consumption increase significantly

Engineering Contradiction:

Improvestatistical analysis accuracyVSAvoidcomputational burden

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by pre-processing categorical data into a specific format with indicator columns before homomorphic encryption. Each categorical value is represented by multiple indicator columns (one for each possible category), where only the relevant column contains the actual value and others contain placeholder values. This pre-arranged structure enables direct statistical operations without requiring filtering during computation, thus reducing computational burden while maintaining accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent segments categorical data into multiple indicator columns, where each column represents a specific category. Instead of storing categorical data as single values requiring filtering, the data is divided into multiple binary indicator columns that can be directly operated upon homomorphically. This segmentation transforms the filtering problem into direct arithmetic operations on structured columns

Inventive Principle:

Principle #1Segmentation

2Reliability

If traditional homomorphic encryption methods are used for categorical data, then data security is maintained, but operation efficiency during statistical operations decreases

Engineering Contradiction:

Improvedata securityVSAvoidoperation efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent changes the parameter representation of categorical data from traditional single-value encoding to multi-column indicator encoding. By transforming the data structure into indicator columns with specific numerical patterns (actual values in relevant columns, placeholder values in others), the system enables efficient homomorphic operations while maintaining security. The parameter change allows statistical operations to be performed directly on the encrypted structured format without decryption or filtering

Inventive Principle:

Principle #35Parameter changes

3Reliability

If multiple operations are performed to achieve statistical operations on homomorphic encrypted categorical data, then data security is preserved, but processing time increases

Engineering Contradiction:

Improvedata securityVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by pre-processing categorical data into a specific format with indicator columns before homomorphic encryption. Each categorical value is represented by multiple indicator columns (one for each possible category), where only the relevant column contains the actual value and others contain placeholder values. This pre-arranged structure enables direct statistical operations without requiring filtering during computation, thus reducing computational burden while maintaining accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent enables continuous useful action by designing the indicator column structure to support direct homomorphic statistical operations. The pre-arranged format with placeholder values and actual values in specific columns allows multiplication and addition operations to proceed continuously without interruption for filtering or conditional logic, significantly reducing processing time while maintaining security

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS12587358B2Apparatus for homomorphic encryption of categorical data and method for thereof

Publication Date: 2026.03.24 CRYPTO LAB INC

AI summary

Disclosed is an electronic apparatus. The electronic apparatus includes a memory configured to store at least one instruction and store a plurality of categorical data whose values are expressed as a plurality of classes for one category, and a processor configured to execute the at least one instruction to generate the plurality of categorical data into one homomorphic encrypted message, in which the processor is configured to generate a categorical column in which homomorphically encrypted data for each of the plurality of categorical data is located in a plurality of slots, generate mask columns corresponding to each of the plurality of classes to correspond to the number of the plurality of classes, and generate the homomorphic encrypted message by combining the categorical column and the plurality of mask columns.