Self-organizing Feature Data Mining and Analysis Framework of Computer Network Considering Edge Information

This paper studies the self-organizing feature data mining and general analysis framework of computer network considering edge information. A significant feature of the Markov decision process is that it has no aftereffect, that is, the state of the system at the next moment only depends on the current state and decision behavior, and has nothing to do with the history of the system. Hence, in the designed model, the new statistical Markov decision chain will be applied. Security loopholes in computer networks are a problem that computer users cannot avoid. In a sense, it is unrealistic to absolutely reject loopholes. In order to better protect the security of computers, it is necessary to then strengthen computer network security management, especially in enterprises. Institutions must also establish a sound management system to prevent information leakage. In the designed scenario, the edge information is also consideredto test the robustness.