Encrypted 3D Object Analysis Using Minkowski Sums for Privacy
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Solution Overview
Problem
Existing additive manufacturing technologies face challenges in ensuring the printability of complex designs, compatibility with post-printing processes, and interfacing with other parts while maintaining design confidentiality and privacy.
Innovation Solution
Implementing homomorphic encryption to perform computations on 3D object models in an encrypted domain, using Minkowski sum protocols to analyze printability and compatibility without revealing proprietary information to untrusted service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D object models are sent to service providers for analysis, then processing capability and analysis accuracy are improved, but data privacy and security are compromised
Solution Approach 1:
The patent introduces an encrypted intermediate representation of the 3D model as a mediator between the client and service provider. The service provider operates on this encrypted representation rather than the original model, allowing analysis to be performed without exposing the actual design data. This intermediary layer enables the service provider to process information while maintaining client data privacy.
Solution Approach 2:
The patent creates an encrypted copy of the 3D model that can be processed by the service provider. This encrypted copy contains sufficient information for analysis purposes but cannot be decrypted or used to reconstruct the original model. The service provider works with this copy, which allows processing without compromising the original data's security.
2Loss of information
If complex analysis computations are performed locally, then data privacy is maintained, but processing time and computational resources are excessive
Solution Approach 1:
The patent segments the processing task into two parts: local encryption and remote computation. The client device performs encryption of the 3D model locally, then sends only the encrypted data to the service provider. The computationally intensive analysis is performed remotely on the encrypted data, dividing the workload to maintain privacy while reducing local processing burden and time.
Solution Approach 2:
The encrypted representation serves as an intermediary that enables remote processing. Instead of performing all computations locally which would be time-consuming, the system uses the encrypted intermediary to offload computations to the service provider, significantly reducing processing time while maintaining data privacy through the encryption layer.
3Loss of information
If service providers perform analysis on encrypted data, then data privacy is maintained, but computational complexity and processing difficulty increase
Solution Approach 1:
The patent uses homomorphic encryption as an intermediary mechanism that allows computations to be performed on encrypted data. The encryption scheme is designed so that mathematical operations on the encrypted representation yield encrypted results that correspond to the correct operations on the original data. This intermediary encryption layer maintains privacy while enabling the necessary computations.
Solution Approach 2:
The patent changes the parameter space by working with encrypted representations rather than plain data. The service provider operates in the encrypted parameter space, performing computations that translate to correct results when decrypted. This parameter transformation allows maintenance of privacy while enabling the required analysis through the mathematical properties of the encryption scheme.
Data Source
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AI summary
The present disclosure provides techniques for processing a three-dimensional (3D) object file or object model in a privacy-preserving manner. An example method includes receiving, from a remote computing device, an encrypted object file comprising a specification of a 3D printable object and receiving a request to process the encrypted object file to identify a characteristic of the 3D printable object. The method also includes obtaining an encrypted comparison file and computing an encrypted Minkowski sum of the encrypted object file and the encrypted comparison file to generate an encrypted result file that comprises information about the characteristic. Computing the encrypted Minkowski sum is performed without decrypting the encrypted object file. The method also includes sending the encrypted result file to the remote computing device.