Secure Data Allocation via Intermediary Comparison
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Solution Overview
Problem
Existing data storage systems face challenges in securely allocating similar data across multiple storage containers without exposing the data, as human or system errors can lead to inadvertent security breaches and data loss, especially when different containers require different encryption methods and intermediaries may not be secure.
Innovation Solution
A secure protocol using intermediaries to compare and allocate data terms to appropriate storage containers by transforming data into sparse binary vectors, determining similarity profiles, and selecting candidate target storage containers based on these profiles, ensuring anonymity and minimizing information leakage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in multiple storage containers with different encryption methods, then data security is improved, but the complexity of data allocation and verification increases
Solution Approach 1:
The patent introduces a trusted intermediary system that manages the verification and allocation process across multiple storage containers. This intermediary handles the complex tasks of verifying data integrity, managing encryption keys, and coordinating between different storage systems, thereby maintaining high security while reducing the operational complexity for end users.
Solution Approach 2:
The system performs preliminary verification and validation of data before allocation to storage containers. By pre-establishing trust relationships, verifying data integrity markers, and preparing allocation protocols in advance, the system reduces the complexity of real-time decision-making during data storage operations.
2Reliability
If data is encrypted before storage, then data security is improved, but the ability to verify and compare data accurately deteriorates
Solution Approach 1:
The patent creates and verifies cryptographic hashes or digital fingerprints of the encrypted data. These copies serve as verification markers that can be compared without exposing the actual encrypted content, thereby maintaining both security and verification accuracy. The intermediary system stores and compares these data representations to ensure integrity.
Solution Approach 2:
The system transforms data into different parameter representations suitable for verification. By converting encrypted data into verifiable formats such as hash values or encrypted metadata that preserve essential properties for comparison while maintaining security, the system achieves both encryption protection and accurate verification.
3Reliability
If intermediaries are used to manage data allocation, then data security is improved, but the risk of intermediary compromise increases
Solution Approach 1:
The patent divides the intermediary system into multiple independent components or distributed nodes, each responsible for specific verification tasks. This segmentation ensures that a compromise of one intermediary component does not affect the entire system, as other segments can continue to provide verification services and maintain security.
Solution Approach 2:
The system implements feedback mechanisms where intermediaries continuously verify data integrity and report status to the allocation system. This real-time feedback allows for immediate detection and response to potential intermediary compromises, enabling the system to adapt and maintain security even when individual intermediaries are compromised.
Data Source
AI summary
Storage allocation based on secure data comparisons is disclosed. One example is a system including a plurality of intermediaries, a data allocator and a plurality of storage containers. Each intermediary receives a request from the data allocator to identify a target storage container of the plurality of storage containers, for secure allocation of a data term. Each intermediary compares, for each storage container, the truncated data term with a collection of truncated candidate terms to select a representative term of the candidate terms, identifies the selected representative term to the storage container, receives a similarity profile from each storage container, where the similarity profile is representative of similarities between the truncated data term and terms in the storage container, and selects a candidate target storage container based on similarity profiles received from each storage container.