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A mobile phone individual identification method based on bispectral features and deep learning

A technology of deep learning and recognition methods, applied in the field of communication, can solve problems such as information leakage, troublesome network management, and illegal spectrum occupation, and achieve the effects of enhancing security, saving time, and realizing flexible configuration

Active Publication Date: 2019-11-19
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the disadvantage of this technology is that the current software authentication method is easy to imitate, and this vulnerability is also easy to be exploited by malicious attackers to launch PUE (Primary User Emulation) attacks, resulting in information leakage or long-term illegal use of spectrum. Brings great trouble to network management

Method used

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  • A mobile phone individual identification method based on bispectral features and deep learning
  • A mobile phone individual identification method based on bispectral features and deep learning
  • A mobile phone individual identification method based on bispectral features and deep learning

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Embodiment

[0057] For the convenience of description, the relevant technical terms appearing in the specific implementation are explained first:

[0058] AGC (Automatic Gain Control): automatic gain control;

[0059] RIB (radial integral bispectra): radial integral bispectra;

[0060] AIB(axial integral bispectra): axial integral bispectra;

[0061] CIB (circumference integral bispectra): circular integral bispectra;

[0062] SIB(square integral bispectra): rectangular integral bispectra;

[0063] PCA (Principal Component Analysis): principal component analysis;

[0064] CNN(Convolution Neural Network): convolutional neural network;

[0065] BN (batch normalization): batch normalization;

[0066] early stopping: early termination;

[0067] validation data: validation data set;

[0068] overfitting: overfitting.

[0069] figure 1 It is a flowchart of a mobile phone individual identification method based on bispectrum features and deep learning in the present invention.

[0070] ...

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Abstract

The invention discloses a mobile phone individual identification method based on bispectral features and deep learning. After sampling and preprocessing all samples, four integral bispectrums are calculated to obtain a feature set for training a convolutional neural network. Then divide the feature set into training feature set YTrain and test feature set Ytest in proportion; use the training feature set YTrain convolutional neural network, and then use the trained convolutional neural network to classify the test feature set YTest, and finally output the mobile phone individual Recognition results.

Description

technical field [0001] The invention belongs to the field of communication technology, and more specifically relates to a mobile phone individual identification method based on bispectrum features and deep learning. Background technique [0002] Individual communication radiation source identification is to determine the individual radiation source that generates the signal by measuring the characteristics of the received signal, which is defined as "the ability to associate the unique electromagnetic characteristics of the radiation source with the individual radiation source". The individual characteristics of the radiation source are generally due to the slight differences between its internal components, such as the nonlinearity of the device, the instability of the frequency source, and the spurious output. This feature is also called the "fingerprint" of the communication signal. Refers to the feature in a communication signal used to identify the identity of the commu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W12/06G06N3/08G06N3/04G06K9/62G06K9/00
CPCH04W12/06G06N3/08G06N3/045G06F2218/18G06F2218/02G06F2218/08G06F18/214
Inventor 杨远望王炳程丁敏朱学勇李梦娜游长江
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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