Logistic regression analysis system based on vertical distribution privacy data protection
A privacy data, vertically distributed technology, applied in digital data protection, electronic digital data processing, digital data information retrieval, etc., can solve problems such as lack of practicability, high computational complexity, high communication cost, etc., to achieve fast calculation, Good safety, the effect of ensuring safety
Active Publication Date: 2019-02-22
SHANGHAI JIAOTONG UNIV
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This model approximates logistic regression and has high computational complexity and high communication costs, so it is not practical
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[0021] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.
[0022] Such as figure 1 As shown, the structural block diagram of an embodiment of the present invention includes: a privacy data processing module, a data mining learning module, and an analysis application module, wherein: the privacy data processing module uses a linear kernel function to generate a corresponding kernel training set for each partial privacy data , and output these local kernel training sets to the input of the data mining learning module; the data mining learning module first a...
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The invention provides a logistic regression analysis system based on protection of vertically distributed private data. The system comprises a private data processing module, a data mining study module and an analytical application module, wherein the private data processing module uses a linear kernel function to obtain kernel training sets of the private data of each vertical distribution mechanism; the data mining study module firstly accumulates each local kernel training set to obtain a total kernel training set, and then performs logistic regression study to the total kernel training set, and the obtained overall situation model vector is used to perform judgment and analysis in the analytical application model finally. The system of the invention ensures the safety of vertically distributed original private data while providing data sharing and mining. The special method of calculating overall situation model vector also improves the studying and solving efficiency. By using a radiation distributed structure of server-client, the system of the invention has excellent practicability and expansibility.
Description
technical field [0001] The present invention relates to a privacy-protected distributed data mining scheme, in particular to a logistic regression analysis system based on vertically distributed privacy data protection Background technique [0002] The advent of the big data era has had a major impact on experimental science. At present, an important development trend of scientific research in the field of biomedicine is data-driven, that is, to explore the laws through the study of massive data, and to directly put forward hypotheses or draw reliable conclusions. Open source and data sharing have become important drivers of biological research. However, the issue of big data privacy is a real challenge that cannot be avoided. With concerns about privacy, particularly genomic privacy, researchers may have limited access to some important information, such as personal genomic data. Therefore, how to ensure that the patient's original data is not leaked while ensuring patie...
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IPC IPC(8): G06F16/2458G06F21/62
Inventor 熊红凯蒋晓谦李勇
Owner SHANGHAI JIAOTONG UNIV