Securing User-Entered Text In-Transit via ML Image Transformation
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Solution Overview
Problem
Existing security measures for protecting user-entered personally identifiable information (PII) and handwritten signatures while in-transit between devices are inadequate, leaving sensitive information vulnerable to malicious access.
Innovation Solution
Transforming user-entered text, such as PII and handwritten signatures, into images using a machine learning algorithm, which secures the data in-transit by obfuscating and encrypting the information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing security measures (encryption, SSL) are used to protect data in-transit, then data transmission security is improved, but they fail to protect against malicious users who can access the document while transmitted, leaving PII vulnerable
Solution Approach 1:
The patent segments the document into two separate components: the original document containing PII and a transformed image representation of the document. This segmentation allows the PII to be protected through transformation while maintaining the ability to access and process the document information at the destination.
Solution Approach 2:
The patent introduces a machine learning-based transformation mechanism as an intermediary between the original document and the transmitted data. This intermediary transforms the document into an image representation, providing an additional layer of security that obfuscates the PII during transmission while allowing reconstruction at the destination.
2Object-affected harmful factors
If user-entered text is transformed into an image using machine learning, then security against malicious access is improved, but the complexity of the system increases due to the machine learning algorithm requirement
Solution Approach 1:
The patent creates a transformed copy of the document in the form of an image representation. This copy contains the same information as the original document but in a transformed format that provides security during transmission. The copying process uses machine learning to generate the transformed image from the original document.
3Reliability
If the transformed image is transmitted instead of the original document, then security of PII is improved, but the ability to process and search the text content becomes more difficult
Solution Approach 1:
The patent performs preliminary transformation of the document into an image representation before transmission. This preliminary action secures the PII during transmission while preserving the ability to reconstruct and process the text content at the destination through inverse transformation using the same machine learning model.
Data Source
AI summary
Systems and methods described herein discuss securing user-entered data in-transit between a first device and a second device. A user may enter text in a document. A first device may analyze the document to identify the user-entered text. The user-entered text may be separated from the document and transformed into an image using a machine learning algorithm. Transforming the text into an image may secure the data in-transit from the first device to a second device. The second device may receive the image and the document from the first device. The second device may reconstruct the user-entered text from the received image and re-assemble the document from the received document and the reconstructed user-entered text.