Multimodal Semantic Sensor Fingerprinting for Fast Content Verification

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Solution Overview

Problem

There is an increasing concern about the verification of the genuineness of digital content, particularly images, video, and audio, as AI-generated content can be misleading and time-consuming to authenticate.

Innovation Solution

A method and system for creating multimodal semantic sensor data fingerprinting using sensors like cameras and microphones to generate non-reversible cryptographic fingerprints, incorporating system context data, and hashing algorithms to ensure content authenticity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional verification methods are used to determine if digital content is AI-generated, then verification can be performed, but the process becomes time-consuming and inefficient

Engineering Contradiction:

Improvecontent verification reliabilityVSAvoidverification time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary action by embedding a cryptographic fingerprint at the moment of content creation, rather than attempting to verify AI-generated status after the fact. This fingerprint is generated from sensor data and system context at creation time, enabling instant verification without time-consuming analysis later

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The invention creates a cryptographic copy (fingerprint) of the original sensor data and system context that can be independently verified. This fingerprint serves as a portable verification token that can be checked without needing to analyze the original content or access the creation device, enabling rapid verification

Inventive Principle:

Principle #26Copying

2Productivity

If multimodal semantic sensor data fingerprinting is implemented, then content authenticity can be verified instantly, but the system complexity increases

Engineering Contradiction:

Improveverification efficiencyVSAvoidfingerprinting system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the fingerprinting process into distinct modular components: sensor data collection, system context gathering, cryptographic fingerprint generation, and verification. Each component operates independently and can be implemented separately, reducing overall system complexity while maintaining high verification efficiency

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The cryptographic fingerprint acts as an intermediary between the content creation process and verification process. Instead of directly analyzing complex sensor data and system context during verification, the system uses this intermediate fingerprint representation, which simplifies the verification operation while preserving authenticity information

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250245352A1Multimodal semantic sensor data fingerprinting

Publication Date: 2025.07.31 DELL PROD LP

AI summary

An information handling system may receive, from a first sensor of the information handling system, content to be associated with a semantic cryptographic fingerprint. The first information handling system may also receive, from the first sensor context data contains information about time and date, geolocation coordinates, metadata, etc. Based, at least in part, on the semantic cryptographic fingerprint and the context data, the information handling system may determine a cryptographic tag. The information handling system may sign the cryptographic hash with a private key. Finally, the information handling system may then publish the cryptographic hash with an indicator of the content to a public database or directory.