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Physical layer identity authentication method based on deep support vector description method

An identity authentication and support vector technology, applied in neural learning methods, climate sustainability, sustainable communication technology, etc., can solve problems such as key leakage, increase communication resources and computing resource consumption, and decipher ciphertext.

Active Publication Date: 2021-02-23
SOUTHEAST UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional security mechanism based on modern cryptography mainly relies on the information asymmetry between legitimate users and attackers, making it impossible for attackers to decipher the ciphertext in a short time to achieve computational security.
However, with the rapid development of computing power, legitimate users have to shorten the key update time, increase the key length or increase the complexity of the encryption method to ensure the effectiveness of the security system, which will undoubtedly increase the consumption of communication resources and computing resources , bringing a huge burden to terminal devices with limited resources
At the same time, there is a risk of the key being leaked, and the degree of protection is not high

Method used

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  • Physical layer identity authentication method based on deep support vector description method
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  • Physical layer identity authentication method based on deep support vector description method

Examples

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Embodiment Construction

[0055] The physical layer identity authentication based on the deep support vector description method in the present invention is described by taking a communication scenario including one legal information sender, one legal information receiver and three attackers as an example. In this example, the number of transmit antennas of the MIMO-OFDM communication system is N T = 2, the number of receiving antennas N R =2, the number of subcarriers N S = 256. The time delay of each path and the fading at all levels of the multipath fading channel are shown in Table 1, and the signal-to-noise ratio is 1 dB.

[0056] It includes the following steps:

[0057] Step 1: Collect CSI data between legal users at T (in this example, T=2000) times as a training data set, where each record is the CSI data at time t (t=1, 2,...T) , called a training sample. The T value determines the number of training samples. Too few training samples will reduce the generalization ability of the authentic...

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PUM

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Abstract

The invention relates to a physical layer identity authentication method based on a deep support vector description method, and the method comprises the steps: enabling a data sample to be mapped to ahypersphere from a sample space through a neural network, and continuously updating the weight of the neural network through iteration at a training model stage, so that the data samples are mapped into the hypersphere as much as possible, and meanwhile, the volume of the hypersphere is ensured to be minimum; and in the authentication stage, if the data sample is mapped into the hypersphere, regarding the data sample as legal information sender information, and otherwise, regarding the data sample as attacker information. A legitimate information sender, a legitimate information receiver andan attacker exist in a communication system, and the legitimate information sender and the legitimate information receiver communicate with each other in the presence of the attacker. An attacker maybe counterfeited as a legal information sender to send a signal to a legal information attacker, while the physical layer identity authentication technology in the invention aims at helping a legal information receiver to judge whether the received signal comes from the legal information sender or the attacker.

Description

technical field [0001] The invention belongs to the field of physical layer security in wireless communication, and in particular relates to physical layer identity authentication based on a deep support vector description method. Background technique [0002] "Access security" is an important factor affecting the security of wireless networks. In traditional security mechanisms, access security mainly relies on a series of security protocols in the data link layer, network layer, transport layer, session layer and application layer in the Open System Interconnection (OSI) model. However, the traditional security mechanism based on modern cryptography mainly relies on the information asymmetry between legitimate users and attackers, which makes it impossible for attackers to decipher the ciphertext in a short time and achieve computational security. However, with the rapid development of computing power, legitimate users have to shorten the key update time, increase the key...

Claims

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Application Information

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IPC IPC(8): H04W12/06H04L1/06H04B7/06G06N3/04G06N3/08
CPCH04W12/06H04L1/0693H04B7/0626G06N3/08G06N3/045Y02D30/70
Inventor 潘志文邵旖洁刘楠尤肖虎
Owner SOUTHEAST UNIV
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