A detection method for intrusion data

A detection method and data technology, applied in digital transmission systems, instruments, computing, etc., can solve the problems of high recognition rate of most types of sample points, reduce information prevention of minority types, reduce service performance, etc., and reduce the average false negative rate. , the effect of reducing the imbalance between classes and making up for the lack of quantity

Active Publication Date: 2022-05-27
ZHEJIANG GONGSHANG UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

The consequences of DDOS attacks may damage the entire network, reduce service performance, block terminal services, and unauthorized access to remote hosts will lead to hosts being controlled to conduct illegal and criminal activities, etc.
The existing classification methods have a high recognition rate of sample points for most categories, so the minority categories are misclassified, which causes a big problem and reduces the information protection for the minority categories

Method used

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  • A detection method for intrusion data
  • A detection method for intrusion data
  • A detection method for intrusion data

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Embodiment Construction

[0037] Specific embodiments are given below to further illustrate the present invention.

[0038] like Figure 1 to Figure 4 As shown, a detection method for intrusion data specifically includes the following steps:

[0039] 1) The steps of obtaining a balanced data set: Use the coarse clustering method to calculate the distance from the sample point to the cluster center point from the training data according to the Euclidean distance, and divide it into multiple cluster subsets, which will contain fewer sample points and longer distances. The clustered subsets of the intrusion data are regarded as noise points, and these noise data are deleted; then different categories of intrusion data are randomly sampled and dimensionality reduction is carried out to reduce the overfitting of different categories of intrusion data models, and the training set is adjusted by the oversampling method. Perform intra-class equalization, increase the number of samples in some categories, and ...

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Abstract

The invention discloses a detection method for intrusion data, which specifically includes the following steps: 1) a step of obtaining a balanced data set, 2) a step of classifying data, and 3) a step of evaluating a classifier; A detection method for intrusion data with optimized performance.

Description

technical field [0001] The invention relates to the technical field of information reduction intrusion detection, and more particularly, to a detection method for intrusion data. Background technique [0002] With the development of the Internet industry, preventing information from being invaded has become one of the important issues, among which the uneven distribution of data is one of the problems that cannot effectively improve information protection. Unbalanced distribution of data means that the number of samples of one or several categories in the data set far exceeds the number of samples of other types. The category with a smaller proportion of data is called the minority category, and the category with a larger proportion of the data is called the majority category. There are various types of network attacks, some of which are very common, such as DDOS, brute force cracking, and ARP spoofing. Some attack types appear less frequently, such as unauthorized access ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L9/40H04L41/142G06K9/62
CPCH04L63/1416H04L63/20H04L41/142G06F18/214G06F18/24
Inventor 任午令张晓冰
Owner ZHEJIANG GONGSHANG UNIVERSITY
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