Graph Embedding Vector Privacy Protection via Proxy Reconstruction
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Solution Overview
Problem
Graph embedding vectors, used to analyze graph data, pose security risks as they implicitly preserve structural information that can be used to reconstruct the original graph, potentially exposing proprietary and confidential information when shared with third parties.
Innovation Solution
A method involving generating first graph embedding vectors from an original graph, creating a proxy graph, encoding it to generate second graph embedding vectors, and decoding these vectors to reconstruct a graph for comparison with the original, with security actions taken if similarity thresholds are met to protect sensitive data, such as preventing exposure or injecting noise into the vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If graph embedding vectors are shared with third parties for analysis, then graph analytic capabilities and insights are improved, but security risks increase due to potential reconstruction of the original graph
Solution Approach 1:
The patent introduces an intermediary evaluation system that acts as a mediator between the graph embedding vectors and third-party analysts. This evaluation system assesses whether the vectors contain sufficient information to reconstruct the original graph before allowing sharing, thereby enabling secure collaboration without direct exposure of sensitive data.
Solution Approach 2:
The patent performs preliminary evaluation of graph embedding vectors before they are shared with third parties. By conducting security assessment in advance (checking if reconstruction is possible), the system prevents potential security breaches before they occur, allowing safe sharing when vectors are sufficiently obfuscated.
2Measurement precision
If graph embedding vectors preserve structural information for accurate analysis, then analysis precision is improved, but vulnerability to reconstruction attacks increases
Solution Approach 1:
The patent changes the parameters of graph embedding vectors by controlling the degree of obfuscation. By adjusting parameters such as noise injection levels, dimensionality reduction factors, or aggregation granularity, the system can tune the vectors to maintain sufficient structural information for accurate analysis while making reconstruction attacks infeasible.
3Reliability
If evaluation methods are comprehensive to ensure security, then security reliability is improved, but computational complexity increases
Solution Approach 1:
The patent replaces complex mechanical evaluation processes with more efficient computational methods. Instead of attempting all possible reconstruction scenarios, the system uses streamlined evaluation techniques such as checking specific structural invariants, measuring information entropy, or applying simplified reconstruction heuristics that provide sufficient security assurance with lower computational overhead.
Data Source
AI summary
A method for protecting sensitive data from being exposed in graph embedding vectors. In some embodiments, a method may include generating first graph embedding vectors from an original graph and generating a proxy graph from the first graph embedding vectors. The proxy graph may include a plurality of proxy nodes and proxy edges connecting the proxy nodes. The proxy nodes may include one or more attributes of the original nodes that are included in the first graph embedding vectors. Second graph embedding vectors may then be generated by encoding the proxy graph and a reconstructed graph may be generated from the second graph embedding vectors. Finally, the reconstructed graph may be compared to the original graph and if a threshold level of similarity is met, a security action may be performed to protect sensitive data from being exposed.