A Disk Anomaly Detection Method Based on Neighborhood Partitioning and Isolation Reconstruction

Abstract

An embodiment of the present invention proposes a disk anomaly detection method based on neighborhood partitioning and isolation reconstruction, including: collecting disk SMART information, filtering out effective disk feature attributes to form a data set, and performing exponential smoothing processing on it to obtain a disk training set ; Sampling the training set randomly for multiple times to obtain multiple sub-training sets, in the subset, the distance between each point and its closest point is used as the radius to construct the disk feature isolation area, and the test points that do not belong to any area are regarded as global anomalies; for non-global anomalies For the test point, the ratio of the radius of the area where the two consecutive adjacent points are located is regarded as the former abnormal value of the test point in this area; the area is reconstructed after including the test point, and the radius ratio of the area where the test point is located before and after reconstruction is used as the test point. The back abnormal value in this area; the abnormal score is obtained by combining the front and back abnormal values ​​of all the areas where the test point is located. The technical solution provided by the embodiment of the present invention can effectively improve the recall rate of abnormal disks.

Description

【Technical field】 [0001] The invention relates to an anomaly detection method in the field of machine learning, in particular to a disk anomaly detection method based on neighborhood partition and isolation reconstruction. 【Background technique】 [0002] At present, the most used computer to store data is the disk, and the operation of the disk is directly related to the security of the stored data. Data centers typically have hundreds or thousands of disks, which greatly increases the likelihood of system failure. Therefore, data centers need to adopt some mechanisms to detect disk anomalies, so as to avoid irreversible damage or loss of data. [0003] At present, the commonly used disk anomaly detection method is the threshold detection method based on SMART data. It can monitor, record and compare with the preset safety value set by the manufacturer by sending detection commands in the disk to monitor and record the hardware operation of the disk itself. If it is detec...

AI Technical Summary

Problems solved by technology

[0006] In view of this, the embodiment of the present invention proposes a disk anomaly detection method based on neighborhood partitioning and isolation reconstruction to solve the problem of precise sample positioning and special anomaly detection in the region under different density conditions

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