Smart Contract Tagging for Secure Electronic Notarization
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Solution Overview
Problem
Current electronic notarization mechanisms face challenges in ensuring data privacy and security, deterring users due to concerns about data breaches during remote online notarization processes.
Innovation Solution
A computing platform retrieves a smart contract from a decentralized distributed ledger system, extracts metadata attributes, tags it based on these attributes, and digitally notarizes documents using synthetically generated fingerprint metadata, ensuring privacy and security through generative AI and blockchain technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users upload documents and personal information online for electronic notarization, then the notarization process can be completed, but data privacy and security are compromised
Solution Approach 1:
The patent extracts personal identifiable information (PII) from uploaded documents using OCR and NLP technologies. The extracted PII is separated from the original document and stored in a secure, access-controlled manner, while the document itself is retained for notarization purposes. This extraction eliminates the need to store complete personal information in the notarization system, thereby reducing privacy risks while maintaining operational functionality.
Solution Approach 2:
The patent introduces an intermediary layer of automated PII detection and redaction systems between the document upload and storage processes. This intermediary automatically identifies, extracts, and masks sensitive information before documents are stored in the system. The intermediary acts as a buffer that protects user privacy while allowing the notarization process to proceed with necessary document verification.
2Reliability
If personal data is stored in a data store for verification, then authentication can be performed, but security risks increase
Solution Approach 1:
The system extracts only the essential verification elements (such as document hashes, metadata, and non-identifying characteristics) needed for authentication, rather than storing complete personal data. This extraction approach maintains authentication reliability by preserving verification capabilities while minimizing the storage of sensitive personal information that could be compromised.
Solution Approach 2:
The patent creates and stores cryptographic hashes and digital fingerprints of documents as copies, rather than storing the actual personal information contained in documents. These cryptographic copies serve as reliable verification mechanisms while being inherently more secure than storing original personal data, as they cannot be reverse-engineered to reveal sensitive information.
3Measurement precision
If complete document information is processed for notarization, then accuracy is improved, but data exposure risk increases
Solution Approach 1:
The system extracts and processes only the specific metadata and structural elements needed for notarization verification (such as document format, signature fields, and authentication markers) while excluding or masking sensitive personal information. This selective extraction maintains verification accuracy by focusing on relevant document characteristics while protecting private data from exposure.
Solution Approach 2:
The patent applies different processing qualities to different parts of the document: sensitive personal information areas are masked or redacted, while verification-critical areas (such as signatures, dates, and document structure) are processed with high fidelity. This local differentiation ensures accurate verification where needed while protecting privacy where appropriate.
Data Source
AI summary
Aspects of the disclosure relate to automatic tagging of smart contracts for electronic notarization in a decentralized finance system. A computing platform may retrieve, from a node in a decentralized distributed ledger system, a smart contract associated with a document for remote online notarization. The computing platform may extract one or more metadata attributes from the document. The computing platform may tag the smart contract based on the extracted one or more metadata attributes. The computing platform may request and receive approval of the tagging from one or more individuals associated with the document for remote online notarization. The computing platform may digitally notarize the document. The computing platform may transmit the tagged smart contract to the node in the decentralized distributed ledger system and cause the tagged smart contract to be saved in the node.