Multi-objective decision algorithm-based network flow anomaly scene optimal handling method

Abstract

The invention discloses a multi-objective decision algorithm-based network flow anomaly scene optimal handling method, which comprises the following steps of: A, network flow anomaly detection: carrying out network flow anomaly detection by using an S-H-ESD algorithm, and giving an alarm when detecting that the flow suddenly drops or suddenly rises; step B, multi-objective decision making: finding an optimal solution in a network flow abnormal scene; and step C, network flow abnormal scene processing. The invention provides the multi-objective decision algorithm-based network flow anomaly scene optimal handling method, and the optimal handling scheme can be provided for operation and maintenance personnel under the conditions that a network fault occurs, the influence degree is relatively large, the anomaly needs to be quickly recovered, and certain security can be ensured at the same time.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a multi-objective decision-making algorithm-based optimal handling method for abnormal network traffic scenarios. Background technique [0002] With the continuous deepening of information system construction, the network structure is becoming more and more complex and the number of systems is increasing. An abnormal network traffic may often cause the entire regional network to be interrupted, and a large number of business systems cannot provide services normally, affecting the daily operation of the company. However, due to the complex architecture and numerous devices involved in the fault scenario caused by abnormal network traffic, the operation and maintenance personnel cannot quickly deal with it, so that the business cannot be quickly restored. [0003] At this stage, the handling of abnormal network traffic scenarios not only needs to consider recovery speed, but a...

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Problems solved by technology

[0002] With the continuous deepening of information system construction, the network structure is becoming more and more complex and the number of systems is increasing. An abnormal network traffic may often cause the interruption of the entire regional network, and a large number of business systems cannot provide services normally, affecting the daily operation of the company.

Due to the complexity of the structure and the large number of devices involved in the fault scenario caused by abnormal network traffic, the operation and maintenance personnel cannot quickly deal with it, so that the business cannot be quickly restored.

[0003] At this stage, the handling of abnormal network traffic scenarios not only needs to consider recovery speed, but also many factors such as security protection during and after handling. It is a multi-objective and multi-constrained optimization decision-making problem. At present, multi-objective decision-making algorithms are rarely applied to this in the scene

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