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Privacy protection associated rule data digging method based on multi-parameter interference

A privacy protection and data mining technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of leakage of privacy, low efficiency of running time, and low degree of privacy protection.

Inactive Publication Date: 2014-02-26
TONGJI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This invention improves how we can use an advanced method called MAKE (Massive Aviation Communications) for reconstruction of interfering signals from geospatial databases. It uses algorithms that optimize countings over time by collectively capturing frequently occurring items or rules associated with them. These improvements make it easier than previous methods like LIGO's GISAID system because they are more efficient at identifying specific types of objects within these datasets compared to older systems such as VLBI.

Problems solved by technology

Technological Problem: Current Personal Information Protection System (PPS) technologies only provide limited access control or prevention against unauthorized users accessing personal health related documents like patient recordings. These systems use complex algorithms that require significant computing resources and consume considerable amounts of memory space. There has been some attempts at developing more efficient ways to preserve these valuable details without compromising its confidentiality.

Method used

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  • Privacy protection associated rule data digging method based on multi-parameter interference
  • Privacy protection associated rule data digging method based on multi-parameter interference
  • Privacy protection associated rule data digging method based on multi-parameter interference

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0079] As shown in Table 1, the original dataset consists of 3 items and 10 data records, and the minimum support threshold is set to 2.

[0080] Table 1 Raw data set

[0081] ID

A

B

C

1

1

1

0

2

0

1

0

3

0

1

1

4

1

1

0

5

1

0

1

6

0

1

1

7

1

0

1

8

1

1

1

9

1

1

1

10

1

0

1

[0082] The specific execution steps are as follows:

[0083] (1) Set the three interference parameters as p 1 =0.4,p 2 =0.3,p 3 =0.3, for any item t∈{0, 1} in the original dataset, let f 1 =t,f 2 =1-t, f 3 =0, define a function f(t), the function value is with probability p j value is f j, j=1, 2, 3, random disturbance is performed on the original database, and the disturbed data set D′ is obtained, as shown in Table 2;

[0084] Table 2 Dataset D′ after interference

[0085] ID

...

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PUM

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Abstract

The invention relates to a privacy protection associated rule data digging method based on multi-parameter interference. The method includes: building an original data set into a two-dimensional Boolean matrix D, using data interference and inquiry limiting strategies to performing random interference on the Boolean matrix D so as to increased privacy protection degree and obtain the interfered data set D'; using the modified MASK algorithm to perform item set support degree reconstruction on the interfered data set D', and optimizing the counting process through a set principle to obtain a frequent item set and associated rules. Compared with the prior art, the method has the advantages that data interference strategy are combined with inquiry limiting strategy, the defects of each of the data interference strategy and the inquiry limiting strategy are overcome, and privacy protection degree is increased; the recurrence relation between probability inverse matrixes is discovered according to the matrix partitioning thought, the complex process which requires that the probability matrixes need to be solved before the inverse matrixes are calculated, the counting process is optimized on the basis of the set principle, exponential order time complexity during the counting process is eliminated, and the execution efficiency of the method is increased greatly.

Description

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Claims

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Application Information

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Owner TONGJI UNIV
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