Research on Non-Self-Intrusion Forensics of Computer Network Based on Adaptive Immunity

In order to realize the ability of intrusion and evidence collection of computer data center network, a non-self-intrusion evidence collection method of computer network based on adaptive immunity is proposed. The statistical analysis model of non-self-intrusion sequence of computer data center network is constructed, the feature matching method of intrusion information is used to analyze the fusion of non-self-intrusion big data of computer data center network, the statistical feature quantity of network non-self-intrusion is constructed, and the feature matching and information mining of non-self-intrusion signal of computer data center network are carried out by using autocorrelation feedback adjustment method. The correlation feature quantity of non-self-intrusion signal in computer data center network is extracted, and the multi-mode intrusion sequence feature matching of computer data center network is realized by using adaptive immune method, and the non-self-intrusion evidence of network is realized according to the result of feature matching. The simulation results show that this method has high accurate probability, strong anti-attack ability and good ability of network non-self-intrusion information mining and feature identification.