Industrial control network intrusion detection method based on multilayer feature fusion neural network
A neural network and industrial control network technology, applied in the field of intrusion detection of industrial control network based on multi-layer feature fusion neural network, can solve the problems of large feature layer sparsity and feature loss, and achieve the goal of solving the serious problem of feature loss and improving the accuracy rate Effect
Active Publication Date: 2020-01-21
BEIJING INSTITUTE OF TECHNOLOGYGY
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[0004] The purpose of the present invention is to provide an industrial control network intrusion detection method based on multi-layer feature fusion neural network, which can effectively solve the serious problem of feature loss caused by excessive feature layer sparsity, and improve detection accuracy
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[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. 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.
[0034] The purpose of the present invention is to provide an industrial control network intrusion detection method based on a multi-layer feature fusion neural network, which can effectively solve the serious problem of feature loss caused by excessive sparsity of the feature layer, and improve detection accuracy.
[0035] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be furt...
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The invention discloses an industrial control network intrusion detection method based on a multilayer feature fusion neural network. The method comprises the steps of obtaining original data of an industrial control network information management layer; performing numerical encoding on non-numerical features in the original data to obtain first data; performing normalization processing on numerical characteristics in the original data to obtain second data; constructing a multilayer feature fusion pyramid neural network; training and testing the neural network by using the training set and the test set to obtain a neural network model; and inputting the first data and the second data into a neural network model to obtain a detection result. According to the method, the problems of overlarge deep feature sparsity and serious detail feature loss in the neural network can be solved, and the detection precision is improved.
Description
technical field [0001] The invention relates to the technical field of industrial control network security, in particular to an industrial control network intrusion detection method based on a multi-layer feature fusion neural network. Background technique [0002] Industrial control network security is an important part of network security. Compared with Internet network security, industrial control network security issues cause even greater losses. Not only that, industrial control network security is more of an offensive and defensive war between countries. For example, the "Stuxnet" virus targeting Iran's nuclear power plant increased the damage rate of equipment by modifying parameters, causing huge losses. Under the ever-changing international situation, the international relations between countries are very complicated, and the research on industrial control network security is of great significance. [0003] At present, intrusion detection algorithms based on machin...
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IPC IPC(8): H04L29/06G06N3/08G06N3/04
CPCH04L63/1416G06N3/08G06N3/045
Inventor 柴森春程中浩张百海崔灵果姚分喜
Owner BEIJING INSTITUTE OF TECHNOLOGYGY