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DGA domain name detection method using deep residual network and character-level sliding window

A sliding window and domain name detection technology, applied in neural learning methods, biological neural network models, electrical components, etc., can solve problems such as the difficulty of discovering botnet command and control servers

Active Publication Date: 2021-11-23
天翼安全科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
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Problems solved by technology

This makes it harder to spot botnet command and control servers

Method used

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  • DGA domain name detection method using deep residual network and character-level sliding window
  • DGA domain name detection method using deep residual network and character-level sliding window
  • DGA domain name detection method using deep residual network and character-level sliding window

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Embodiment Construction

[0100] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0101] 1 Introduction

[0102] 1.1 Background

[0103] The bots that form the botnet are programmed into the designed DGA algorithm in advance, and the algorithm is used to generate a large number of DGA domain names and periodically generate a list of domain names. When certain conditions are met (within a certain period of time), the controller of the botnet will register certain domain names as the access domain names of the command and control server of the botnet. Then, the bot program on the infected bot host connects to the doma...

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Abstract

The present invention proposes a DGA domain name detection method using a deep residual network and a character-level sliding window, comprising the following steps: S1, obtaining domain name data, and preprocessing the obtained domain name data; S2, processing the domain name data in step S1 The data is subjected to original feature extraction processing; S3, the data processed in step S2 is input to the deep residual network layer for deeper feature extraction; S4, the data processed in step S3 is subjected to batch normalization processing; S5, the Its domain name is classified. The invention can classify domain names.

Description

technical field [0001] The invention relates to the field of DGA domain name detection, in particular to a DGA domain name detection method using a deep residual network and a character-level sliding window. Background technique [0002] Botnet refers to the use of one or more means of transmission to infect a large number of hosts with bot program (bot program) viruses, thereby forming a one-to-many controllable network between the controller and the infected hosts. The construction of botnets mainly utilizes the loopholes of software or hardware devices, and social engineering (using the weakness of human nature to complete the target tasks), etc., so that the victim hosts can be infected with malicious bots without realizing it, and use one-to-many command and control (C&C) channel to control the zombie host to complete the specified attack behavior sent by the control host. With the increase of Internet users and the lack of user security awareness, botnets are one of t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/12H04L29/06G06N3/04G06N3/08
CPCH04L63/1416G06N3/08H04L61/4511G06N3/045
Inventor 刘小洋苗琛香刘加苗
Owner 天翼安全科技有限公司
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