Trusted Checker Agents for Data Access Policy Compliance
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Solution Overview
Problem
In scenarios where data owners store data with untrusted third-party databases, ensuring compliance with defined data access policies becomes challenging due to potential collusion between the third-party server and clients, leading to unauthorized access to records.
Innovation Solution
A trusted checker agent interfaces between the data server and the client, performing policy checking operations using lightweight data structures like Bloom filters to verify compliance with access policies without locally storing the policies, ensuring that only authorized data is transmitted to the requesting entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in untrusted third-party databases, then data storage capacity and accessibility are improved, but data access security and policy compliance deteriorate
Solution Approach 1:
A trusted checker agent is introduced as an intermediary component between the untrusted database server and the client. This agent verifies data access policies by checking query results against policy rules before returning data to the client, thereby maintaining security despite using untrusted third-party storage infrastructure
Solution Approach 2:
The system segments the data access control function into separate components: the untrusted database server handles only data storage and basic query execution, while the trusted checker agent handles policy verification and access control decisions, isolating the security-critical functions from untrusted environments
2Reliability
If data access policies are locally stored and verified, then access control reliability is improved, but device complexity and memory requirements increase
Solution Approach 1:
Instead of storing complete policy definitions locally, the system uses cryptographic hashes (fingerprints) of policy rules as compact representations. These hash values serve as verified copies that can be efficiently stored and compared, dramatically reducing memory requirements while maintaining verification reliability
Solution Approach 2:
The policy representation is transformed from full policy rules to cryptographic hash values, changing the parameter from detailed policy text to compact binary fingerprints. This transformation reduces storage requirements from potentially large policy documents to small fixed-size hash values
3Reliability
If complete policy verification is performed on all query results, then data access security is improved, but processing time and computational overhead increase
Solution Approach 1:
The system performs partial verification by checking only the cryptographic hash of the returned data against the stored policy hash, rather than verifying each individual data record. This partial action approach maintains security guarantees while significantly reducing computational overhead compared to exhaustive verification
Data Source
AI summary
To verify compliance with a data access policy, the system compares electronic data to an electronic data access policy identified by a database; determines whether a portion of the electronic data complies with the electronic data access policy; in response to the portion of the electronic data not complying with the electronic data access policy, indicates that an access to the electronic data by a communication device is not permissible; and declines the access to the portion of the electronic data to the communication device when the access to the electronic data is not permissible. Related methods and computer program products are also discussed.