Statistical Analysis of threatening IP in Universities Based Automated Script

Abstract

The operation of cyber security has gradually become a significant part of informatization in the process of smart campus construction. However, universities rely too much on physical security devices in the current network security operation process, and lack of self-defined statistical analysis automation program. The current network logs have the following problems: difficult to gather data-sets of different application systems, difficult to unify attribute names of different data-sets, difficult to count the number of records with attacker and victim as the only items, and besieged to do repetitive work daily. In order to solve the above problems, this paper proposes an automatic statistical threatening IP algorithm, which can uniquely locate the attacker and victim and process other data through a programmatic way. Finally, it is used to report statistical data to departments related to cyber security. The results of experiment show that the proposed algorithm can effectively complete the statistical work of network attack threatening IP details.