Network detection method and device, computer equipment, readable storage medium and program product

By using preset topological resource association information, traffic information and large language models for alarm analysis in network operation and maintenance, the problem of difficulty in identifying the root cause of network alarms in traditional methods is solved, and efficient and accurate network detection and management are achieved.

CN119696995AActive Publication Date: 2025-03-25CHINA TELECOM CORP LTD TECHNOLOGY INNOVATION CENTER +1
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Patent Information

Application Number
CN202411966324.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-30
Publication Date
2025-03-25
Estimated Expiration
2044-12-30

AI Technical Summary

Technical Problem

When traditional network operation and maintenance methods face large-scale cloud computing, Internet of Things and big data platforms, it is difficult to effectively identify and screen the root causes of network alarms, resulting in high false alarm and missed response rates, affecting the accuracy of network security management.

Method used

By obtaining the target network's preset topological resource association information, traffic information and first alarm information of multiple alarm types, the target abnormal score corresponding to each first alarm information is calculated, and the root cause alarm is identified, the target alarm information and its dependencies are extracted, and the root cause alarm analysis is performed through the large language model to obtain the network detection results.

Benefits of technology

Accurate identification, efficient screening and intelligent analysis of network alarms is achieved, false alarms and missed reports are reduced, and the accuracy of target alarm information identified as the fundamental alarm cause and the accuracy of network detection results are improved.

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Abstract

The invention relates to a network detection method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring preset topology resource association information, flow information and first alarm information of a plurality of alarm types of a target network; calculating a target anomaly score corresponding to each piece of first alarm information, and performing preliminary screening on the first alarm information based on the target anomaly score to obtain second alarm information; performing root cause alarm identification on the second alarm information based on the preset topological resource association information and the target abnormal score corresponding to the second alarm information, and extracting to obtain the target alarm information and a dependency relationship corresponding to the target alarm information; and performing root cause alarm analysis processing on the traffic information, the target alarm information and the dependency relationship according to a preset large language model to obtain a network detection result. By adopting the method, the accuracy of a network detection result can be improved.
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