Mobile AI Data Sanitization with Local-Remote Scrubbing

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Solution Overview

Problem

Existing data sanitization systems on mobile devices face challenges in identifying sensitive data due to the large size of regex routines, limited storage space, and the lack of insight into how locally run artificial intelligence models sanitize data, leading to security risks and inefficiencies.

Innovation Solution

A bifurcated sanitization process using a machine learning model on the mobile device for initial sanitization, followed by a remote server scrubbing application to ensure accuracy, combined with on-demand model updates and unconventional output formats to maintain control and adaptability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If regex routines are transmitted to a remote server for processing, then data sanitization capability is improved, but transmission security risks and system complexity increase

Engineering Contradiction:

Improvedata sanitization capabilityVSAvoidtransmission security risks

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent extracts the regex routines from the remote server environment and embeds them directly into the mobile application. This allows the sanitization logic to execute locally on the device, eliminating the need to transmit data to external servers while maintaining comprehensive sanitization capabilities through an extensible corpus of regex patterns.

Inventive Principle:

Principle #2Taking out (Extraction)

2Object-affected harmful factors

If a corpus of regex routines is stored locally on the mobile device, then transmission security is improved, but device storage space is consumed

Engineering Contradiction:

Improvetransmission security risksVSAvoiddevice storage space

Core Design Contradiction:

Object-affected harmful factorsVSQuantity of substance

Solution Approach 1:

The patent segments the regex corpus into manageable components that can be efficiently stored and executed. By organizing the regex patterns in a structured, modular format within the application, the system achieves comprehensive data sanitization coverage while optimizing storage utilization on mobile devices with limited space.

Inventive Principle:

Principle #1Segmentation

3Measurement precision

If multiple regex routines are implemented to capture different types of sensitive data, then data sanitization accuracy is improved, but device complexity increases

Engineering Contradiction:

Improvedata sanitization accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements a universal regex engine within the mobile application that can execute multiple different regex patterns. This single multi-functional component handles various types of sensitive data (personally identifiable information, financial data, health information, etc.) without requiring separate processing systems, thereby maintaining high sanitization accuracy while controlling complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12361163B2Systems and methods for sanitizing sensitive data and preventing data leakage from mobile devices

Publication Date: 2025.07.15 CAPITAL ONE SERVICES LLC

AI summary

Methods and systems are described herein for leveraging artificial intelligence to sanitize sensitive data and prevent the data from leaving the mobile device and/or be exposed to unauthorized third parties. More specifically, methods and systems are described for a novel and unconventional architecture for a data sanitization application, a novel and unconventional delivery format for the data sanitization model, and a novel and unconventional output format of the data sanitization model.