Signature Correlation Trust Model for Secure Data Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In collaborative grid computing environments, entities face challenges in establishing trust to share data securely with mutually mistrusting parties, as existing methods risk data theft due to lack of assurance about the other entity's trustworthiness.
Innovation Solution
A method is developed to determine signature correlation values for data arrays from each entity, establishing a level of trust based on matching signatures, allowing secure sharing of non-matching data without full access, using a signature algorithm that includes hash functions, word placement, and context identifiers to identify and verify data elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If complete data access is provided to enable full data sharing, then data sharing completeness is improved, but data security and trust are worsened due to risk of data theft
Solution Approach 1:
The patent segments data access into two levels: complete data access for trusted entities and restricted access (signature verification only) for untrusted entities. This allows the system to provide full data sharing benefits to reliable partners while maintaining security by limiting access to signature verification only for entities that have not established trust, thereby resolving the contradiction between data sharing completeness and data security
Solution Approach 2:
The patent implements dynamic access control where the level of data access is not fixed but changes based on the trust relationship between entities. The system dynamically adjusts access rights from restricted (signature verification only) to complete data access as trust is established through successful signature correlation, enabling the system to adaptively balance data sharing completeness and security based on real-time trust assessment
2Adaptability or versatility
If data is made known to enable comparison and sharing, then data sharing capability is improved, but trust between entities is worsened due to potential exploitation
Solution Approach 1:
The patent applies preliminary action by performing signature verification and correlation before allowing data sharing. The system pre-verifies the authenticity and relevance of data through signature correlation analysis, establishing trust credentials before the actual data exchange occurs. This preliminary trust assessment enables the system to safely enable data sharing capability while maintaining entity trust through verified authentication
Solution Approach 2:
The patent introduces signature correlation as an intermediary mechanism between data requesting entities and data providing entities. This intermediary layer verifies trustworthiness and data relevance before allowing direct data access, acting as a mediator that enables data sharing capability while protecting entities from exploitation by untrusted parties through verified authentication
3Reliability
If signature verification is performed on all data elements, then trust establishment is improved, but processing time and complexity are worsened
Solution Approach 1:
The patent applies partial action by performing signature verification on representative samples of data elements rather than all data elements. The system verifies signatures on a subset of data to establish trust correlation, which is sufficient for trust establishment without the time cost of verifying every single data element. This partial verification approach maintains trust establishment reliability while significantly reducing processing time
Data Source
AI summary
A method and system for sharing data and interrogating data include establishing a level of trust between mutually mistrusting entities so that data may be shared therebetween based on the level of trust. The method and system include interrogating data provided from one of the entities to the other entity without the receiving entity having complete access to the data associated therewith.