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An Unknown Threat Detection Method for Big Data Platform Based on Deep Transfer Learning

A big data platform and transfer learning technology, applied in the field of unknown threat detection on big data platforms, can solve problems such as small threat sample data sets, and achieve the effects of improving prediction results, improving generalization capabilities, and improving threat detection capabilities

Active Publication Date: 2021-11-12
CHINA ELECTRONICS TECH CYBER SECURITY CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 1) How to detect unknown threats against big data platforms and solve the problem of small sample data sets of threats on big data platforms;

Method used

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  • An Unknown Threat Detection Method for Big Data Platform Based on Deep Transfer Learning
  • An Unknown Threat Detection Method for Big Data Platform Based on Deep Transfer Learning
  • An Unknown Threat Detection Method for Big Data Platform Based on Deep Transfer Learning

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Experimental program
Comparison scheme
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Embodiment Construction

[0022] 1. Implementation plan

[0023] The scheme proposed by the present invention implements a threat detection framework based on deep transfer learning, which mainly includes data collection and processing, transfer learning and deep learning threat detection. Through different calling methods, a complete big data platform threat detection system based on deep transfer learning is formed. figure 1 A schematic diagram of a threat detection scheme based on deep transfer learning is given. The following is based on figure 1 Explain how it works.

[0024] Such as figure 1 As shown, the core content of the present invention is to obtain corresponding data from the execution process of other malicious programs, construct a large-scale threat sample set in the source domain, and use the rich supervision information in the sample set to help the training of the deep learning model in the target domain.

[0025] In terms of data collection and processing, it is adopted to deplo...

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Abstract

The invention discloses a method for detecting unknown threats on a big data platform based on deep transfer learning, which includes the following steps: step 1, constructing a source field sample set; step 2, adopting the same method as step 1 to collect sample data in the target field, and then Use the data enhancement method to expand the sample data and build a sample set in the target field; Step 3: Build a threat detection model based on deep transfer learning. Compared with the prior art, the positive effects of the present invention are: 1. Through data enhancement in the target field, the problem of insufficient generalization ability of the deep learning model is improved, thereby improving the prediction effect of the deep learning model. 2. Through the transfer learning of massive threat samples on the Internet, it is possible to effectively detect unknown threats that have never appeared without reducing the detection rate of known threats. 3. Through the deep neural network of fusion features, the behavioral features of different dimensions are integrated to improve the recognition accuracy of the model.

Description

technical field [0001] The invention relates to a method for detecting unknown threats on a big data platform based on deep transfer learning. Background technique [0002] With the increasing development and popularization of Internet technology and mobile communication technology, big data platforms are also facing network threats and data security issues. The amount of information exchange between big data platforms and users has been greatly increased, and data security and risk prevention in the field of big data platforms are more complicated than traditional networks. Especially for Hadoop and other big data platforms integrated with mobile business systems, the current security protection methods are often lacking, or the security defenses adopted are insufficient, and they face security threats such as data theft, data integrity, and identity forgery, and there are few threat samples. Aiming at the deficiencies of the existing big data platform threat detection met...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/06G06N3/04G06N3/08
CPCH04L63/1416H04L63/1425H04L63/145G06N3/08G06N3/045
Inventor 孙治周玉金刘正军李春林陈剑锋徐锐饶志宏
Owner CHINA ELECTRONICS TECH CYBER SECURITY CO LTD