Design And Research Of Intelligent Network Penetration Testing System

With the rapid development of Internet,most of the countries in the world are in the tide of networked information.People can not only carry out real-time video and audio communication through the network,browse the news of all over the world,shopping on the internet,trading on the internet,and so on.The Internet has become a miniature of reality and virtual life,which is the Internet information age,and the network is ubiquitous.Everything has two sides.As the Internet brings us convenience,it also provides the survival for the lawless elements.These illegal elements often use network protocol,network system vulnerabilities,such as the purpose of the government,enterprises,schools,and even personal computer systems to implement penetration and control,from which they want to get the useful information.The consequences of network attacks are serious.Network penetration testing can reliably evaluate the security of information systems.Through the detection of the vulnerability of the IPt system and the unsecurity factors in the security setting of the IPt system,it can effectively prevent and protect the IPt system.More attention is paid to network security,and penetration test can effectively protect network security.Therefore,penetration testing has attracted more and more attention and attention of many scholars.This paper focuses on the core technology of independent decision and interaction mechanism,simulates the mathematical model of decision interaction through the seepage test example,uses the maximum membership degree deviation method to select the priority sequence of the scanning V_N,studies the structure type and the principle of the interaction mechanism,and gives the improvement of the ant colony algorithm.The mathematical model of ant colony optimization attack load is improved by ant colony algorithm to choose the attack load in network penetration test.The improved ant colony optimization algorithm can roughly select the optimal attack load so as to get rid of the problem of relying on artificial selective attack load.The intelligent network penetration test system is studied,and the intelligent scanning module is implemented separately.The independent decision reasoning and interaction mechanism are applied to the scanning module,and the ant colony optimization algorithm is applied to the penetration attack module.The independent decision and interactive machine and the ant colony optimization algorithm are verified by the experiment.On the basis of this,the feasibility of testing the whole system through the Metasploit platform is tested.Finally,the implementation of the intelligent network penetration test system is used for penetration test,and compared with the traditional penetration test.