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Privacy protection workflow publishing method for maintaining availability of critical path

A critical path and privacy protection technology, applied in digital data protection, instruments, computing, etc., can solve problems such as difficulty in ensuring the leakage probability of the critical path in the release graph, failure to take into account path hiding, and critical path leakage

Active Publication Date: 2020-12-29
JIANGSU FRONTIER ELECTRIC TECH +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] (1) While ensuring that there are at least k candidate paths with the same length, the concealment of the true length of the path is not taken into account. If the attacker knows that a special node is located on the critical path, there is still a risk of critical path leakage;
[0005] (2) When the number of paths between target nodes is lower than the anonymity strength k, the weight perturbation method that maintains the graph structure is difficult to ensure that the leakage probability of the key path in the release graph does not exceed 1 / k

Method used

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  • Privacy protection workflow publishing method for maintaining availability of critical path
  • Privacy protection workflow publishing method for maintaining availability of critical path
  • Privacy protection workflow publishing method for maintaining availability of critical path

Examples

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Embodiment 1

[0049] Embodiment 1: see figure 1 , a privacy-preserving lineage workflow sharing release method, comprising the following steps:

[0050] Step (1) Given the original workflow WF, the target module pair set H is divided into three categories based on the degree of participation of directed edges in the critical path, zero-visit edges (NVE), full-visit edges (AVE) and partial access edge (PVE);

[0051] Step (2) Anonymize the critical paths between the target module pairs, and perturb the edge weights on the Top-k paths, so that the path weights satisfy the ε-error equivalence after perturbation; if there are less than k paths between the module pairs, If the ε-error equivalence between Top-k paths cannot be realized, continue to step (3);

[0052] Step (3) When there are less than k paths between target modules in H, only after step (2) is executed, the workflow does not satisfy the (k, ε)-critical path anonymity, and the path splitting method is used to find that the targe...

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Abstract

The invention discloses a privacy protection workflow publishing method for maintaining availability of a critical path, which comprises the following steps of: dividing a zero-order access edge, a full-order access edge and a part of access edges in a workflow based on the critical path between a target module pair; introducing a workflow (k, epsilon)-critical path anonymity privacy protection model, carrying out anonymity processing on a critical path between target module pairs, disturbing an edge weight on a Top-k path, realizing (k, epsilon)-critical path anonymity, and maintaining a lineage workflow graph structure unchanged at the same time; in order to solve the problem of anonymity intensity loss caused by the fact that the number of paths between target modules is lower than a kvalue, performing path splitting based on module decomposition, and searching and splitting composite modules on anonymity paths to realize path splitting, so that a workflow release graph strictly meets (k, epsilon)-critical path anonymity. While the privacy attack based on the critical path is prevented, the availability of the topological structure of the critical path is maintained.

Description

technical field [0001] The invention relates to a method for publishing data privacy protection, which is object-oriented to the lineage workflow and realizes the anonymous protection of key paths in the workflow. Background technique [0002] With the deepening of data sharing applications, there is an increasingly urgent need to share and publish genealogy workflows that describe the principles of data generation and evolution. The lineage workflow is usually expressed in the form of a directed acyclic graph (DAG, Directed acyclic graph). The nodes represent the functional modules of the workflow, the directed edges represent the data flow direction and logical order between modules, and the edge weights represent the relationship between modules. The execution cost and transmission cost of . By analyzing the critical path of the workflow and the functional modules on the path, the shortest time required to complete the entire workflow can be measured, and then the time a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/62
CPCG06F21/6254
Inventor 祝永晋倪巍伟闫冬李昆明
Owner JIANGSU FRONTIER ELECTRIC TECH
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