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A Generalized Linear Regression Method Under Privacy Preservation

A generalized linear regression and privacy protection technology, applied in the field of generalized linear regression, can solve the problems of low precision and low efficiency of generalized linear regression, and achieve the effect of minimizing errors and overcoming the low accuracy of iterations

Active Publication Date: 2020-09-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem of low efficiency and low precision of implementing generalized linear regression under encryption when the cloud is untrustworthy in the outsourcing of calculations in the prior art. This application provides an efficient and high-precision privacy-protected The generalized linear regression method of

Method used

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  • A Generalized Linear Regression Method Under Privacy Preservation
  • A Generalized Linear Regression Method Under Privacy Preservation
  • A Generalized Linear Regression Method Under Privacy Preservation

Examples

Experimental program
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Effect test

Embodiment 1

[0072] target data set

[0073] D.

[0074]= (574 425 404 615 315 573 151; 109 772 734 250 520 394 403; 105 766734 237 794 386 391; 105 766 730 237 1000 380 384; 71 580 553 750 383 628 66; 684 100 931 690 208; 33 0 873 1000 109 122 812; 63 0 911 550 109 225 961; 704 0 538 675 109 546 311; 33 549 523 600 383 125927; 46 564 534 412 178 175 1000; 21 673 642 687 109 109 109 78 747; 915 0 0 925 109 734192; 1000 0 0 375 178 892 342; 92 601 573 187 726 716 303; 67 0 919 500 109 859166; 666 549 523 575 452 122 479; 670; 6700; 6700; 502 0 737 315655 169; 708 518 0 450 383 734 246; 729 0 550 725 383 231 625; 46 932 0 287 452772 445; 37 922 0 400 452 739 414; 21 673 642 175 452 51552; 12 663 630 287520 4766666 514; 721 575 546 712 383 219 173; 666 549 523 600 109 476 35; 679 554526 512 109 497 55; 746 0 619 587 109 418 445; 776 0 630 375 41 473 510; 9666 09 225 307; 719 387 178 339 445; 578 461 442 525 315 149 713; 0865 823 825 109 0 445; 582 512 488 300 589 298 571; 485 393 373 425 2...

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Abstract

The invention discloses a generalized linear regression method under privacy protection, aiming to solve the problem of low efficiency and low precision of generalized linear regression under encryption when the cloud is untrustworthy when computing outsourcing in the prior art. In combination with encryption algorithm, linear regression method and gradient descent method, the generalized linear regression after data set encryption is realized, that is to say, when the cloud is untrustworthy, data processing can still be performed under encryption protection, etc., realizing real computing outsourcing , realizing the mutual correspondence between the calculation of plaintext and the calculation of ciphertext, and overcoming the technical problems of low accuracy and slow calculation speed of the traditional gradient descent method under ciphertext iteration; this application is applicable to the related fields of vector homomorphic calculation.

Description

technical field [0001] The invention relates to the related field of vector homomorphic calculation, in particular to a generalized linear regression method under privacy protection. Background technique [0002] Today, with the explosive growth of data, using machine learning and data mining technology to maximize the output value of data has become the actual demand of people. However, due to the extremely limited computing resources, international IT giants such as Google, Microsoft, and IBM are developing their own cloud computing platforms for commercial use. However, cloud security has always been a bottleneck in the development of cloud computing. Eight Internet giants in the United States jointly opposed the U.S. government surveillance project, which once again brought the security issues of cloud computing to people's attention. However, it is far from enough to protect cloud security only from the policy point of view, and it cannot dispel people's concerns abou...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L9/00H04L9/08
Inventor 杨浩淼何伟超黄云帆梁绍鹏师兆森鲁冰儿
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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