Secure Data Allocation via Information Processor Mediation
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Solution Overview
Problem
Existing data storage systems face challenges in securely allocating data across multiple devices without exposing sensitive information, particularly when human or system errors lead to data loss or unintended exposure, and there is a need to identify suitable storage devices before data is stored while maintaining anonymity.
Innovation Solution
A secure data allocation protocol using an information processor linked to query and data processors, which generates random permutations and orthogonal transforms to determine similarity scores between query and candidate terms, allowing secure data allocation without revealing the underlying data, using a system that includes an information processor communicatively linked to a query processor and multiple data processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in multiple storage devices without secure protocols, then data allocation efficiency is improved, but data security and anonymity are compromised
Solution Approach 1:
The patent introduces an information processor as an intermediary between the query processor and data processors. This intermediary receives secure versions of query terms and candidate terms, determines similarity scores, and identifies target datasets without exposing the underlying data. The information processor acts as a mediator that enables efficient data allocation while maintaining security through its intermediary role in the communication chain.
Solution Approach 2:
The patent uses secure versions (copies) of query terms and candidate terms instead of the actual data. These secure versions are transformed representations that preserve the ability to determine similarity while preventing exposure of the underlying sensitive information. The copying principle allows the system to work with data representations that are sufficient for allocation decisions but insufficient for data recovery.
2Reliability
If secure protocols are used for data allocation between multiple parties, then data security is improved, but communication overhead and computational complexity increase
Solution Approach 1:
The patent segments the data allocation system into distinct functional components: a query processor that generates secure query terms, multiple data processors that store secure candidate terms, and an information processor that determines similarity scores. This segmentation allows each component to perform its function independently with well-defined interfaces, reducing overall system complexity while maintaining security.
Solution Approach 2:
The patent transforms data terms into secure versions using parameter changes in the form of orthogonal transforms and random permutations. These transformations change the representation parameters of the data while preserving the similarity relationships needed for allocation. The parameter changes enable secure comparison without requiring complex cryptographic protocols for each interaction.
3Measurement precision
If all data is exposed for similarity comparison, then allocation accuracy is improved, but information leakage and security breaches increase
Solution Approach 1:
The patent extracts only the necessary information for similarity comparison while leaving the underlying sensitive data hidden. By working with secure versions of data terms that contain just enough information to determine similarity scores, the system extracts the minimal required information for accurate allocation without exposing the full data content that could lead to information leakage.
Solution Approach 2:
The patent replaces the mechanical approach of directly comparing raw data with a transformed approach using orthogonal transforms and secure representations. This substitution allows similarity comparison to occur in a transformed space where the comparison mechanism works on secure versions rather than exposing the original data, thereby preventing information leakage while maintaining allocation accuracy.
Data Source
AI summary
Data allocation based on secure information retrieval is disclosed. One example is a system including an information processor communicatively linked to a query processor and a plurality of data processors respectively associated with a plurality of datasets. The information processor receives a request from the query processor for identification of a target dataset to be associated with a query term. The information processor generates a random permutation, and receives a secure version of the query term from the query processor, and receives secure versions of a collection of candidate terms from each of a plurality of data processors, each candidate term representing a cluster of similar terms in the associated dataset. The information processor determines similarity scores between the secure version of the query term and secure versions of the candidate terms, and identifies the target dataset of the plurality of datasets based on the determined similarity scores.