Research on the Security Assessment Method for Mimetic Multivariate Systems Based on Multi-Granularity Features

Aiming at the current status quo that the security assessment of mimetic multivariate systems generally adopts a single level of assessment, which is unable to establish a security link between its internal software diversity and the overall security of mimetic multivariate systems, this paper proposes an assessment mechanism that combines two assessment methods, namely, software diversity metrics under multi-granularity characterization and risk assessment of vulnerability attacking system modeling. The experimental part of the dataset uses the GNU core toolset (coreutils 8.32), and the validity of this assessment method is verified by designing a security assessment algorithm that weights and scores the heterogeneity of the multi-granularity software diversity technique, and then by modeling an attack on the mimetic multi-variant system experiment. The experimental results show that the security assessment algorithm can effectively assess the anti-attack ability and security of the mimetic multivariate system under the multi-granularity feature, which has certain reference value for the future research on the security assessment method of the mimetic multivariate system.