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Encipherment protection system and method for artificial neural network model

An artificial neural network and protection system technology, applied in biological neural network models, neural learning methods, digital data protection, etc.

Active Publication Date: 2018-10-09
CHENGDU PANOAI INTELLIGENT TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the above-mentioned defects of the existing artificial neural network protection mechanism, the present invention provides an encryption protection system for the artificial neural network model

Method used

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  • Encipherment protection system and method for artificial neural network model
  • Encipherment protection system and method for artificial neural network model
  • Encipherment protection system and method for artificial neural network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] A kind of encryption protection system for artificial neural network model comprises data input module 1, encryption module 2, encrypted data input module 3, artificial neural network model module 4 and data output module 5, and described data input module 1 and encryption module 2 signal The encryption module 2 is connected to the encrypted data input module 3 by signal, the encrypted data input module 3 is connected to the artificial neural network model module 4 by signal, and the artificial neural network model module 4 is connected to the data output module 5 by signal.

[0051] The data input module 1 is used to provide the original input data D to the encryption module 2 .

[0052] The encryption module 2 is used to encrypt the original input data D provided by the data input module 1, and output the encrypted input data D , Described encryption module 2 is by one group of password group S that has N digits as control amount, all original input data D that data i...

Embodiment 2

[0061] A kind of encryption protection method for artificial neural network model, it is characterized in that: comprise the following steps:

[0062] A. Provide raw input data D;

[0063] S. Encrypt the original input data D to generate encrypted input data D , ;

[0064] B. will encrypt the input data D. , Input to the artificial neural network model, and the artificial neural network model encrypts the input data D , perform calculations and obtain results;

[0065] C. Output the calculated results.

[0066] Described step S specifically comprises:

[0067] S1. Provide a group of cipher group S with N digits as the control amount, the cipher group S specifically defines the encryption process for the original input data D; wherein, the length of the cipher group S is determined by the encryption method and encryption requirements in the encryption process Defined; each of the N digits of the password group S is selected from one of the Arabic numerals 0-9;

[0068] S...

Embodiment 3

[0079] For a system structure diagram of an encryption protection system 100 for an artificial neural network model, please refer to the appendix figure 1 , the system 100 includes an encryption module 2, the encryption module 2 is set before the artificial neural network model module 4, the original input data D provided by the data input module 1 first enters the encryption module 2 for encryption processing, and generates encrypted input data D , , and output to the encrypted data input module 3, the artificial neural network model module 4 is based on the encrypted input data D provided by the encrypted data input module 3 , Perform calculations. The encryption module 2 is controlled by a group of cipher groups S with N digits, and adjusts the original input data D in a unified manner, wherein the length of the cipher group S is determined by the encryption method and the encryption method in the encryption process implemented by the encryption module 2 Restricted by the ...

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PUM

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Abstract

The invention belongs to the field of artificial neural network protection mechanisms, and particularly relates to an encipherment protection system and method for an artificial neural network model.The encipherment protection system comprises a data input module, an encipherment module, an encipherment data input module, an artificial neural network model module and a data output module, whereinthe data input module is in signal connection with the encipherment module; the encipherment module is in signal connection with the encipherment data input module; the encipherment data input moduleis in signal connection with the artificial neural network model module; the artificial neural network model module is in signal connection with the data output module. Compared with the prior art, under the condition that the calculated amount is not significantly increased, and the performance of an artificial neural network is maintained, by means of the method, a protective password can be embedded into the artificial neural network model so that after the artificial neural network model is released, the protective password cannot be affected by any copying or secondary development or modification.

Description

technical field [0001] The invention belongs to the field of artificial neural network protection mechanisms, and in particular relates to an encryption protection system and method for artificial neural network models. Background technique [0002] Deep learning is the main technical solution for current artificial intelligence applications. The artificial neural network model trained with deep learning technology is the result of the labor of the original developers. However, in the process of publishing and applying the artificial neural network model, its network structure and node weights will be completely exposed to the outside world. After the artificial neural network model is released and / or applied by a third party, it is easy to be copied, re-developed or modified, resulting in damage to the rights and interests of the original developer. The protection schemes applicable to artificial neural network models in the prior art mainly include overall network encryp...

Claims

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Application Information

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IPC IPC(8): G06F21/60G06N3/08
CPCG06F21/602G06N3/08G06N3/084
Inventor 尹愚
Owner CHENGDU PANOAI INTELLIGENT TECH CO LTD