TripleBlind, Inc., a security and privacy software firm, has patented a new approach to data privacy using split data and algorithms. The solution securely performs computations on sensitive data without exposing the underlying information to either party involved. Their system advances the field of secure multi-party computation by introducing a method that splits both algorithms and data, ensuring privacy and integrity throughout the process.

At the core of TripleBlind’s invention is a novel approach to dividing algorithms into separate subsets. The Boolean logic algorithm is broken down into two distinct subsets, each handled by different entities. These subsets are then processed independently on split data subsets. This approach ensures that neither entity has access to the entire algorithm or data, mitigating risks of data breaches or unauthorized access.

The system employs a secure multi-party computation method where only AND and XOR operations are utilized, making it nearly impossible for either party to infer the complete data or algorithm. To enhance efficiency, the invention uses Beaver sets, a technique that reduces communication overhead by precomputing certain values, thereby expediting the overall process.

Each entity generates and exchanges shares of mathematical sets, which are used in conjunction with the split data to produce interim results. These results are then combined to derive the final output. The division of data and algorithms, coupled with the secure computation framework, ensures that sensitive information remains protected while still allowing for complex operations to be performed.

TripleBlind’s method represents a significant leap forward in the realm of secure computing, offering a robust solution for scenarios where data privacy is paramount. By innovatively splitting both data and algorithms and leveraging advanced cryptographic techniques, this invention sets a new standard for privacy-preserving computations in various applications.

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