Detection method of abnormal data of embedded intelligent terminal, and embedded intelligent terminal

Abstract

The invention provides a detection method of abnormal data of an embedded intelligent terminal, and the embedded intelligent terminal. The detection method comprises: receiving data to be tested, wherein the data to be tested comprises the abnormal data; determining an object in the data to be tested, a k neighbor of each object and a k neighbor relationship between the objects; constructing a k neighbor directed graph according to the k neighbor relationship between the objects; constructing a k-clustering graph according to the k neighbor directed graph, and marking a clustering cluster in the k-clustering graph; and when a part of clustering clusters in the clustering cluster is meet preset conditions, outputting the data to be tested in the part of clustering clusters as the abnormal data. By adoption of the method, small-scale abnormal data mining can be performed in the environment of the embedded intelligent terminal by using a graph clustering method in the case that the computing resources of a terminal device are limited, the detection efficiency is high, the operation efficiency is high, and meanwhile the false alarm rate is reduced.

Description

technical field [0001] The present invention relates to the field of network security, and in particular to an embedded intelligent terminal abnormal data detection method and an embedded intelligent terminal. Background technique [0002] With the continuous development of Internet technology, network security has gradually become a hot topic, and new security threats are generated almost every day. Faced with such increasingly large-scale and varied types of attacks, it has gradually become a mainstream trend to apply machine learning or data mining technology to train and identify tens of thousands of new types of security threats. [0003] In the embedded environment, it is necessary to perform anomaly detection on some collected data, and many methods in the field of data mining can only show advantages when the data scale is large, such as neural networks, for environments with limited computing resources, The methods in the field of data mining appear to be more comp...

AI Technical Summary

Problems solved by technology

[0005] The present invention provides an embedded intelligent terminal abnormal data detection method and an embedded intelligent terminal, which solves the problem of low efficiency of abnormal data detection under the environment of limited computing resources

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