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A dynamic network abnormal link behavior detection method and system

A dynamic network and detection method technology, applied in transmission systems, digital transmission systems, data exchange networks, etc., can solve the problems that abnormal link identification results are not very persuasive, and the implicit relationship is insufficiently considered, so as to make up for the relationship. Insufficient and accurate identification of the effect

Active Publication Date: 2021-05-28
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Problems solved by technology

[0003] Most of the existing network abnormal link detection technologies only evaluate the relationship between nodes through the number of historical links, and do not consider the further implicit relationship between nodes in the network, and the results of abnormal link identification are not very convincing.

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  • A dynamic network abnormal link behavior detection method and system
  • A dynamic network abnormal link behavior detection method and system
  • A dynamic network abnormal link behavior detection method and system

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Embodiment Construction

[0045] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the present invention Examples, not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0046] The technical terms appearing in the embodiments of the present invention are explained below.

[0047] Dynamic Networks: Unlike static networks, dynamic networks are constantly changing over time, as nodes in the network graph and edges between nodes appear or disappear over time. A dynamic network containing n time slices is expressed as G={G 1 ,G 2 ,...,G t ,G t+1 ...

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Abstract

The invention provides a dynamic network abnormal link behavior detection method and system. The method includes: according to the previous T time slice network {G 1 ,G 2 ,...,G T‑1 ,G T}, to determine the current time slice network G T+1 historical network G history ; use the network representation learning method to the historical network G history Perform network representation learning to determine a new historical network G' history ; according to the new history network G' history The distance d between the network node pair (i,j) in ij , determine the similarity adj(i,j) between the network node pair (i,j); if it is judged that the similarity adj(i,j) is less than the preset abnormal judgment threshold, determine the current time slice network G T+1 The link link(i,j) between the node pair (i,j) in mid is abnormal link behavior. The system includes a historical network building module, a network representation learning module, a similarity determination module and an abnormal link judgment module. The present invention can obtain the similarity between nodes, and then can more accurately identify the abnormal link behavior of the dynamic network according to the similarity between nodes.

Description

technical field [0001] The invention relates to the technical field of dynamic networks, and in particular, to a method and system for detecting abnormal link behaviors in dynamic networks. Background technique [0002] In the process of dynamic network evolution, there will be link behaviors between nodes at any time. The purpose of abnormal link behavior detection is to identify which link behaviors are abnormal among many network links. Abnormal link behavior is often the direct or indirect cause of abnormal changes in the network. For example, the short circuit of some links in the power network may lead to the failure of the entire power grid. If a host in the Internet accesses a malicious website, it may be infected with network viruses and infect adjacent hosts. spread to cause greater damage. Therefore, the identification of abnormal links is very necessary. [0003] Most of the existing network abnormal link detection technologies only evaluate the relationship be...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24H04L12/26
CPCH04L41/14H04L41/145H04L43/08H04L43/0805
Inventor 刘琰孙通刘楝罗向阳南煜陶致远
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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