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Anomaly Data Detection Method for Wireless Sensor Networks Based on Weighted Mixed Isolation Forest

An anomaly data detection and forest technology, which can be applied in specific environment-based services, reasoning methods, network topology, etc., and can solve problems such as unseen and low applicability of anomaly detection in concave datasets.

Active Publication Date: 2021-03-02
JIANGNAN UNIV
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Problems solved by technology

The advantages of this method are simple principle, low algorithm complexity and ideal detection accuracy, but its applicability to anomaly detection of some concave data sets is low, and it ignores the influence given by each tree in the forest to the calculation of the final anomaly score. The contribution of the method should be different, which has not been seen in the application of anomaly data detection in wireless sensor networks

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  • Anomaly Data Detection Method for Wireless Sensor Networks Based on Weighted Mixed Isolation Forest
  • Anomaly Data Detection Method for Wireless Sensor Networks Based on Weighted Mixed Isolation Forest
  • Anomaly Data Detection Method for Wireless Sensor Networks Based on Weighted Mixed Isolation Forest

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[0043] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0044] see figure 1 , an anomaly data detection method based on isolation forest, including:

[0045] Step 1: Use the training data set in the data set to build the sub-model in Whiforest, that is, the isolated tree, including the parameter bootstrap sampling number ψ, forest size T, weight coefficient threshold μ, verification sample set Val_W size and known abnormal sample addition rate ratio settings;

[0046] Step 2: Randomly select a small number of known abnormal samples and add them to the already trained Itrees;

[0047] Step 3: Calculate the training sample center Cen-s in the le...

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Abstract

The invention relates to a wireless sensor network abnormal data detection method based on weighted mixed isolated forest. The method utilizes the historical data set collected by the sensor node, and first constructs a certain scale isolated tree set iforest based on the isolated forest algorithm, and in each leaf node The distance information between the sample to be tested and its various sample centers is introduced above, and the weight coefficient of the isolated tree is set in combination with the diversity measure. Finally, the improved isolated forest algorithm is used to judge the abnormal situation of the wireless sensor network data. Through experiments on the data sets of each sensor node, the results show that the algorithm proposed by the invention improves the accuracy of anomaly detection and has broad application prospects.

Description

technical field [0001] The invention relates to the field of wireless sensor network data reliability, in particular to a wireless sensor network abnormal data detection method based on a weighted hybrid isolated forest. Background technique [0002] As the carrier in wireless sensor networks, data usually has a lot of useful information, especially the hint of potential more information in abnormal data (except for the failure of the node itself). Therefore, if you want to understand the changing laws of various things, you must Find out abnormal data through various anomaly detection techniques, and obtain information knowledge that is helpful to us through them. Anomaly detection technology in various fields is a relatively in-depth research problem in recent years. The unique characteristics and strict constraints of wireless sensor networks make the research of this problem more challenging. For the detection of abnormal data in wireless sensor networks, there are many...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W24/06H04W84/18
CPCH04W24/06H04W84/18H04W4/38H04W24/04G06N20/20G06N5/01G06N5/04
Inventor 李光辉许欧阳
Owner JIANGNAN UNIV
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