A network security test system based on embedded artificial intelligence and an implementation method

Abstract

The invention relates to the technical field of computer application, and discloses a network security test system based on embedded artificial intelligence and an implementation method. The network security test system comprises a distributed computing module based on middleware, an analyzer component, an intranet network layer penetration test component, a Web and operation system penetration test component and a report display component. According to the invention, embedded artificial intelligence is introduced to take over and automatically execute related safety test processes. Compared with conventional artificial intelligence, related equipment of the embedded artificial intelligence does not need to access a cloud data center through networking to carry out large-scale calculationto realize the artificial intelligence, all AI algorithms are executed locally, data processing requests with high throughput can be better coped with, and real-time human-computer interaction and decision control can be carried out; In addition, due to the fact that software and hardware are successfully integrated, the embedded artificial intelligence is easy and convenient to operate, the threshold of a safety test can be better lowered, and data processing requirements under various severe environment conditions can be better met.

Description

technical field [0001] The invention belongs to the field of computer application, and in particular relates to an implementation method of a network security testing system based on embedded artificial intelligence. Background technique [0002] In traditional network security testing, the general process is "clarification of goals -> information collection -> vulnerability detection -> vulnerability verification -> information analysis -> acquisition required -> information sorting -> report formation", and the corresponding process operations require security Testers have certain industry technical knowledge, and the test results are often different due to the knowledge reserve, professional sensitivity and vulnerability information database data volume of security testers. Therefore, traditional manual network security testing may fail to detect in time. The possibility of potential security problems and affect the accuracy of the detection results; ...

AI Technical Summary

Problems solved by technology

[0002] For traditional network security testing, the general process is "clear target->information collection->vulnerability detection->vulnerability verification->information analysis->obtain what is needed->information collation->form a report", and the corresponding process operation needs to be safe Testers have certain industry technical knowledge, and the detection results are often different due to the different knowledge reserve, professional sensitivity and vulnerability information database data volume of security testers. Therefore, traditional manual network security testing may not be able to detect in time. Possibility of potential security issues, and affect the accuracy of detection results; In addition, related security testing process such as manual execution, compared with automated security testing, the former may mean more time overhead, which is not conducive to security Fast completion of the testing process and vulnerability discovery

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