Customized Filter Lists for Faster Confidential Data Transmission

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Solution Overview

Problem

Existing data transmission systems face inefficiencies and potential confidentiality issues due to the need to transmit large volumes of raw data over networks, which can slow down processing and compromise privacy, especially when different entities manage the data locally and remotely.

Innovation Solution

Implementing a customized filter list at the local system to preprocess data before transmission, generated by a server system, which reduces the amount of data sent over the network and ensures only necessary information is processed remotely, thereby enhancing speed and maintaining data confidentiality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If large volumes of raw data are transmitted over the network, then the server system can process complete information, but network traffic increases and processing speed decreases

Engineering Contradiction:

Improvedata completenessVSAvoidprocessing speed

Core Design Contradiction:

ReliabilityVSSpeed

Solution Approach 1:

The local system performs preliminary filtering actions by comparing raw data against a filter list before transmission. This preprocessing step identifies and extracts only the necessary data elements that require remote processing, eliminating unnecessary data transmission and accelerating overall processing speed while maintaining data completeness for relevant items.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system extracts only the essential data elements from the raw data by comparing against the filter list. This extraction process separates necessary data for remote processing from data that can be handled locally or does not require transmission, reducing network traffic while ensuring complete processing of critical information.

Inventive Principle:

Principle #2Taking out (Extraction)

2Reliability

If large volumes of raw data are transmitted over the network, then all data can be processed remotely, but network bandwidth is consumed and transmission time increases

Engineering Contradiction:

Improvedata processing completenessVSAvoidtransmission time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If all raw data is transmitted to the server system, then centralized processing can be performed, but network dependency increases and bandwidth requirements grow

Engineering Contradiction:

Improvecentralized processing capabilityVSAvoidnetwork traffic

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system segments data processing into two parts: filtering operations performed locally at the client system using a filter list, and analysis operations performed remotely at the server system. This segmentation allows the client to handle data preprocessing independently, reducing network traffic to only essential data elements while preserving centralized processing capabilities for complex analysis tasks.

Inventive Principle:

Principle #1Segmentation

4Measurement precision

If comprehensive data is transmitted for analysis, then the server system can perform complete exception analysis, but data confidentiality is compromised and computational load increases

Engineering Contradiction:

Improveanalysis accuracyVSAvoiddata confidentiality risk

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12530346B2Data transmission filtering through a customized filter list

Publication Date: 2026.01.20 SOLUTRAN LLC

AI summary

A system and method are presented to improve the speed of shared network processing by filtering data using a filter list. The filter list filters the data submitted for analysis to the server system. Some data is processed locally, but the filtered data is processed at the server system. The local systems process similar data, but they use distinct data hierarchies to classify the data. Hierarchy designations are utilized in the filter list to filter the data. Rules establish a unified hierarchy that is translated to local hierarchies in the filter lists. Tags are established at the server for exceptions. Tags are translated into data identifiers for inclusion in the filter lists. The size of the filter list is reduced by avoiding redundancies between the tagged data identifiers and the local hierarchy designations. The filter list creation process also creates pre-analysis data at the server to assist in its analysis.