Equipment detection early warning system based on big data

Abstract

The invention discloses an equipment detection early warning system based on big data, which comprises a data acquisition module, an equipment detection module and an execution module, and is characterized in that the data acquisition module is used for acquiring data of network equipment performance parameters, and the equipment detection module is used for detecting the anti-pressure capability of equipment; the execution module is used for executing work after network equipment is detected, and the equipment detection module comprises an equipment bearing capacity calculation module, a data normalization processing module and an equipment operation state evaluation module. The equipment bearing capacity calculation module is used for carrying out quantitative evaluation calculation on the bearing capacity of network equipment when the network equipment encounters a network attack, the data normalization processing module is used for carrying out normalization processing operation on performance parameters of the equipment, and the equipment running state evaluation module is used for evaluating the current running state of the equipment. The method has the characteristics of reasonable distribution and accurate detection.

Description

technical field [0001] The invention relates to the technical field of equipment detection and early warning, in particular to a big data-based equipment detection and early warning system. Background technique [0002] In recent years, the global Internet industry has developed rapidly and its scale has grown rapidly. According to IDC data, the Internet market size is expected to reach 7.2 trillion in 2022. However, with the rapid development of the Internet of Things industry, IoT attacks occur frequently: privacy leaks, illegal intrusions , local network damage, etc. In addition, the attack technologies and methods of hackers and black industry practitioners are rapidly updated and iterative. Once our defense capabilities cannot match them and there is a technical generation difference, the equipment will be attacked, resulting in abnormal operation and affecting production. The tragedy of life will inevitably happen. [0003] At present, the existing technology can inte...

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Problems solved by technology

[0002] In recent years, the global Internet industry has developed rapidly and its scale has grown rapidly. According to IDC data, the Internet market size is expected to reach 7.2 trillion in 2022; however, with the rapid development of the Internet of Things industry, Internet of Things attacks occur frequently: privacy leaks, illegal intrusions , local network damage, etc., coupled with the rapid update and iteration of attack technologies and methods of hackers and black industry practitioners, once our defense capabilities cannot match it and there is a technical gap, the equipment will be attacked and cause abnormal operation and affect production The tragedies of life will inevitably happen

[0003] At present, there are existing technologies that can intercept some intrusions, but in the face of large-scale intrusions, the interception requires a lot of server computing power, and the attack probability, frequency, and intensity of different devices are different, so it is not accurate for network devices. Allocation of the same computing power to different devices for protection will cause uneven resource distribution. At present, there is a lack of corresponding equipment detection and early warning systems to solve related problems. Therefore, a large-scale system based on reasonable design allocation and accurate detection Data equipment detection and early warning system is necessary

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