Fault diagnosis method and system based on network traffic data
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A technology for network traffic and fault diagnosis, which is applied in digital transmission systems, transmission systems, data exchange networks, etc., and can solve problems such as abnormal link traffic fault detection
Active Publication Date: 2019-01-04
NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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The fault diagnosis method based on network traffic data provided by the present invention can effectively solve problems such as link traffic abnormality fault detection, status collection, and fault cause diagnosis in the era of big data, and has been effectively verified in practical applications
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Embodiment 1
[0067] figure 1 It is a flowchart of a fault diagnosis method based on network traffic data in the present invention, including:
[0068] S1. Based on the pre-built abnormal link traffic fault propagation model, find all the network devices to be analyzed that may cause the abnormal link traffic fault event of the faulty network device;
[0069] S2. Based on the network traffic data and the pre-built link traffic anomaly detection model, obtain the abnormal link traffic fault event of the network device to be analyzed;
[0070] S3. Obtain the cause network equipment and the cause network failure based on the abnormal link traffic failure event occurring in the network equipment to be analyzed.
[0071] The state library in the present invention can be constructed in advance, and can also be constructed each time a fault diagnosis is performed, and the pre-constructed process includes:
[0072] Search based on the network topology data and link traffic abnormal fault cause tr...
Embodiment 2
[0136] Based on the same inventive concept, this embodiment also provides a fault diagnosis system based on network traffic data, including:
[0137] The first search module is used to search for all network devices to be analyzed that may cause abnormal link flow fault events to occur in the faulty network device based on a pre-built abnormal link traffic fault propagation model;
[0138] The second search module is used to obtain abnormal link traffic failure events of the network equipment to be analyzed based on the network traffic data and the pre-built link traffic anomaly detection model;
[0139] The analysis module is used to obtain the cause network equipment and the cause network failure based on the abnormal link traffic failure event of the network equipment to be analyzed.
[0140] In an embodiment, the first search module includes:
[0141] The intermediate state library sub-module is used for the pre-built link traffic abnormal fault propagation model to filte...
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Abstract
The invention discloses a fault diagnosis method and system based on network traffic data. The method includes the following steps: searching all to-be-analyzed network equipment that may cause occurrence of a link traffic abnormality event of a fault network device based on a pre-built propagation model of a link traffic abnormal failure; obtaining the link traffic abnormality event occurring onthe to-be-analyzed network equipment based on the network traffic data and a pre-built link traffic anomaly detection model; and obtaining reason network equipment and a reason network failure based on the link traffic abnormality event occurring on the to-be-analyzed network equipment. Based on network link traffic monitoring data and network topology data, the method and the system achieve an analysis processing framework for automatic detection and reason analysis diagnosis of the network link traffic abnormal failure, and based on the framework, automatic analysis and discovery of mass abnormal traffic data and automatic diagnosis of reasons can be achieved.
Description
technical field [0001] The invention relates to the technical field of data analysis and mining, in particular to a fault diagnosis method and system based on network flow data. Background technique [0002] With the increasing scale of the network and the increasing number of business types, the development of the Internet has brought great convenience to people; Greater challenge. Network traffic anomaly analysis is a key part of network monitoring, and it is very important to detect anomalies accurately and timely to improve network availability and reliability. Large-scale network traffic is characterized by multiple dimensions, fast speed, and large scale. However, the existing statistical analysis based on time series and wavelet analysis based on signals have limited processing capabilities for such data and cannot meet the current needs. At the same time, the causes of network traffic anomalies are varied and dynamically changing. In the context of big data and com...
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