Association rule mining method for privacy protection under distributed environment

A technology for distributed environment and privacy protection, which is applied in the mining field of association rules for privacy protection in a distributed environment. It can solve the problems of decreased mining accuracy, high algorithm complexity, and damaged attribute correlation, etc., to reduce the amount of calculation and communication. , Improve the excavation efficiency, improve the effect of recovery accuracy

Inactive Publication Date: 2013-06-12
JIANGSU UNIV
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

Secure multi-party computing, using bit-based public key encryption technology to manage a large number of candidate frequent item sets, from which frequent item sets are searched out, the algorithm complexity is high, the efficiency is too low, and th

Method used

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  • Association rule mining method for privacy protection under distributed environment
  • Association rule mining method for privacy protection under distributed environment
  • Association rule mining method for privacy protection under distributed environment

Examples

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specific Embodiment approach

[0048] BEGIN (start)

[0049] k=1; / / 1-itemset

[0050] Repeat

[0051] {

[0052] 1) S 1 According to the candidate k-itemset, construct the itemset random interference matrix P L sent to other local sites.

[0053] 2) Each local site according to P L Disturb all its records, and then count the support numbers of the k-itemsets in the disturbed database, and send them to the semi-trusted third-party site SP to form a matrix of support numbers.

[0054] 3) The semi-integrity third-party site SP sums all the item set support matrixes sent by each local site, obtains the summed support matrix MS', and sends it to S 1 .

[0055] 4) S 1 Use P L -1 (P L The inverse matrix) restores the support count MS of the item set in MS' in the original data, and finds out the value greater than or equal to the threshold (MST-w) (the parameter w is set here, mainly to obtain more approximate frequent items after estimation set, so that more itemsets will have the opportunity to determ...

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Abstract

The invention provides an association rule mining method for privacy protection under a distributed environment. The association rule mining method is used to carry out global mining on multiple data and comprises the steps of: structuring a random disturbance matrix of item sets, carrying out disturbance transformation on data, making statistics on the summation of supporting number matrixes after disturbance, restructuring data distribution, precisely calculating the global support degree of the item sets in a space after pruning, and the like. According to the method disclosed by the invention, by means of structuring the random disturbance matrix to disturb a plurality of attributes at the same time and taking the correlation among the attributes into consideration in a disturbance process, the recover precision is effectively improved; after the supporting number of the item sets is evaluated by using a disturbance method, the final global frequent item set is determined by secure multi-party computation after pruning is carried out based on minimum support degree, thus, the communication traffic is effectively reduced, the mining efficiency is improved, a better compromise between the mining efficiency and the mining precision can be acquired, and the association rule mining method has a wider application range.

Description

technical field [0001] The invention relates to the technical field of privacy protection in data mining, in particular to an association rule mining method for privacy protection in a distributed environment. Background technique [0002] The information age has brought about the explosive growth of data, and it has also given birth to a challenging research field—data mining, which extracts useful knowledge from massive data. As a powerful data analysis tool, data mining can discover potential patterns and laws in data (such as: decision trees, clustering, association rules, neural networks or knowledge expressed in other ways), and can be used in business decision-making, biomedical and scientific Research and other fields play a very important role and have broad application prospects. However, traditional data mining techniques are directly carried out on the original data set, which will cause the leakage of private data. For example, the Center for Disease Control c...

Claims

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Application Information

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IPC IPC(8): G06F21/60G06F17/30
Inventor 薛安荣刘峰
Owner JIANGSU UNIV
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