Data Integrity Verification via Intermediary Service
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Solution Overview
Problem
Many computing systems, especially legacy or resource-constrained systems, lack support for integrity verification, making it complex and resource-intensive to detect data modifications or tampering, which can lead to undetected changes in stored information.
Innovation Solution
A data verification service that generates and manages integrity verification information, such as message digests and keyed message digests, on behalf of computing systems, allowing users to store and retrieve data while ensuring integrity verification is performed, even in systems that do not natively support it, by acting as a reverse proxy and utilizing a key management system for cryptographic keys.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If integrity verification is implemented in legacy or resource-constrained computing systems, then data integrity can be verified, but system complexity and resource consumption increase significantly
Solution Approach 1:
The patent introduces a data verification service as an intermediary component that mediates between clients and the computing system. This service handles all integrity verification operations externally, allowing legacy or resource-constrained systems to verify data integrity without modifying their internal structure or consuming additional resources. The verification service generates verification information for stored data and performs verification checks on behalf of clients, thus resolving the contradiction by providing reliability enhancement without increasing system complexity.
2Reliability
If integrity verification protocols are added to computing systems that lack native support, then data tampering can be detected, but implementation complexity and time consumption increase
Solution Approach 1:
The data verification service acts as an intermediary that implements integrity verification protocols externally. It generates verification information (such as cryptographic hashes) for data stored in the computing system and performs verification checks without requiring the computing system itself to support native integrity verification. This approach enables tamper detection capability while keeping implementation complexity low, as the verification logic is centralized in the verification service rather than distributed across multiple systems.
Solution Approach 2:
The verification service performs preliminary actions by generating and storing verification information (such as hashes or digital signatures) alongside the stored data. This preliminary preparation enables rapid verification checks later without requiring complex real-time computation. The service pre-computes verification metadata that can be quickly compared against retrieved data, thus enabling tamper detection while reducing implementation and operational complexity.
3Reliability
If integrity verification is performed on resource-constrained systems, then data modification can be detected, but resource consumption increases
Solution Approach 1:
The data verification service serves as an intermediary that performs all resource-intensive integrity verification operations externally. Clients can verify data integrity by querying the verification service with minimal computational overhead, while the service itself handles the heavy lifting of generating and comparing verification information. This architecture enables data modification detection on resource-constrained systems without increasing their resource consumption, as the verification logic is offloaded to the verification service.
Data Source
AI summary
Techniques and apparatus for performing integrity verification for data stored on computing systems are described. One technique involves receiving a request to retrieve data from a first data repository. One or more parameters of the request are determined. The data is obtained from the first repository, based on the parameters. Verification information for the data is obtained from a second data repository, based on the parameters. A determination is made as to whether the data obtained from the first data repository has been modified. A message is sent that indicates whether the data obtained from the first data repository has been modified.