Distributed Data Access Control via Contract-Based Verification
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Solution Overview
Problem
Current data processing methods in distributed networks often rely on centralized server centers, compromising user control and data privacy, especially in the face of potential hacker attacks and data misuse, as exemplified by the Cambridge Analytica scandal.
Innovation Solution
A method for processing data in a distributed network utilizing a data model with four levels, a device-independent address reference standard, contract information for access rights, and a control instance for access approval, ensuring standardized data storage and access management across devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in centralized server centers, then data accessibility and management efficiency are improved, but user control over data and data privacy are compromised
Solution Approach 1:
The patent divides data into multiple fragments or shards that are distributed across different nodes in a decentralized network. Each fragment alone is insufficient to reconstruct the original data, ensuring that no single point of failure or unauthorized access can compromise the entire dataset. This segmentation resolves the contradiction by maintaining data accessibility through distributed storage while enhancing user control through cryptographic ownership of data fragments.
Solution Approach 2:
The patent introduces smart contracts and decentralized protocols as intermediaries between users and data storage. These intermediaries automatically enforce access policies, manage data lifecycle, and facilitate data transactions without requiring trusted centralized authorities. This intermediary layer improves management efficiency through automation while preserving user control through programmable access rules.
2Reliability
If data is stored in fragmented form to limit hacker capture, then data security is improved, but data accessibility and usability are worsened
Solution Approach 1:
The patent creates multiple cryptographic copies or representations of data fragments that can be independently verified and reconstructed. Through techniques such as secret sharing and erasure codes, the system generates redundant copies distributed across the network, allowing secure reconstruction of original data from any sufficient subset of fragments. This copying approach enhances security through distribution while maintaining accessibility through reconstructability.
Solution Approach 2:
The patent dynamically adjusts data fragmentation parameters, reconstruction thresholds, and access policy configurations based on security requirements and operational needs. By changing parameters such as the number of required fragments for reconstruction or the granularity of data slicing, the system can optimize the balance between security and accessibility for different use cases without requiring complete system redesign.
3Adaptability or versatility
If standardized data models are implemented for device-independent storage, then data portability and interoperability are improved, but system complexity and implementation difficulty are worsened
Solution Approach 1:
The patent develops a universal data model and protocol suite that can operate across diverse devices, networks, and applications. The standardized data structures, authentication mechanisms, and interaction protocols are designed to be device-agnostic and application-agnostic, allowing the same framework to serve multiple functions including data storage, access control, sharing, and analytics. This universality achieves data portability while managing complexity through reuse of common components.
Solution Approach 2:
The patent implements self-describing data structures and automatic protocol negotiation capabilities that reduce implementation complexity. Data models include embedded metadata that automatically describes their structure, relationships, and access requirements, enabling systems to self-configure and interoperate without extensive manual setup. This self-service approach enhances portability while reducing the burden of standardization implementation.
Data Source
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AI summary
The invention relates to a method for processing data in a distributed network, comprising: - a data model with four levels; - a device-independent address reference standard; - contract information which is mandatorily linked to a specific data record; and - a control instance for checking and approving access to the data records, wherein at least the data records are standardized in such a way that they can be stored and read independently of the device, and wherein the contract information contains subscriber-dependent access rights, wherein the following steps are carried out in response to an access request by means of the control instance: a. comparing the identity of the subscriber with the associated contract information and determining an access authorization of the requesting subscriber; b.Determining at least one restrictive access condition and checking whether the at least one determined restrictive access condition can be met; and only if access authorization exists and the at least one access condition can be met: c. Approving access to the requested specific data set within the scope of the at least one access condition. The method proposed here creates private data sovereignty with simple implementation and, at the same time, device independence for the digital exchange of data sets.