Encrypted 3D Object Analysis for Private Tool Accessibility Checks
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Solution Overview
Problem
Existing additive manufacturing technologies face challenges in ensuring that complex 3D printed objects meet design specifications and can interface with other parts while maintaining privacy of proprietary designs, as they often require significant computational resources and may involve sharing sensitive design data with untrusted service providers.
Innovation Solution
Utilizing homomorphic encryption to perform privacy-preserving computations on 3D object models, allowing a service provider to analyze the model without decrypting it, using Minkowski sum protocols to evaluate printability and compatibility with other parts, while keeping the design data encrypted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If 3D object models are shared with service providers for analysis, then manufacturing quality and design validation improve, but proprietary design information security deteriorates
Solution Approach 1:
Homomorphic encryption serves as an intermediary mechanism that enables the service provider to analyze and validate 3D object models without directly accessing the plaintext design information. The encryption layer acts as a mediator that preserves data security while allowing necessary computational operations for manufacturing quality assurance.
Solution Approach 2:
The system creates and processes encrypted copies of the 3D object models instead of sharing the original plaintext designs. These encrypted representations contain all necessary geometric information for validation while maintaining security, allowing the service provider to work with copies that cannot be reverse-engineered to reveal proprietary information.
2Reliability
If comprehensive analysis of 3D models is performed, then printability and compatibility are improved, but computational resources required increase
Solution Approach 1:
The system performs the minimum necessary computational actions required for validation by operating on encrypted data directly. Instead of decrypting and performing exhaustive analysis, the homomorphic encryption approach enables partial computation that achieves sufficient validation without the excessive computational overhead of full decryption and re-encryption cycles.
Data Source
AI summary
The present disclosure provides techniques for identifying regions of a three-dimensional (3D) printable object that are accessible by a tool. An example method includes receiving, from a remote computing device, an encrypted object file that includes a specification of a 3D printable object and receiving a request to process the encrypted object file to identify regions of the 3D printable object that are accessible by a tool. The method also includes obtaining a tool specification, computing a complement of the tool specification, and encrypting the complement of the tool specification to generate an encrypted comparison file. The method also includes computing an encrypted Minkowski sum of the encrypted object file and the encrypted comparison file to generate an encrypted result file that describes the regions of the 3D printable object that are accessible by the tool. The encrypted Minkowski sum is performed without decrypting the encrypted object file.