A dynamic security evaluation model for vehicular edge computing information system

The deep integration of Internet of Vehicles (IoV) and edge computing technologies brings new requirements for the Vehicular Edge Computing (VEC) information system security evaluation. Facing the two core problems of resource-constrained scenarios and dynamic security evaluation, the GFCIV-CGTOPSIS model for VEC information system dynamic security evaluation is proposed. In the model, subjective and objective evaluation indexes are considered and calculated separately to improve operability. An improved grey correlation F-statistics clustering and index validity combination index screening (GFCIV) method is proposed in order to improve the operational efficiency of the traditional grey F-statistics rough set (GFRS) index screening method. The CRITIC method is used to determine the subjective and objective comprehensive index set weights, and the grey TOPSIS method is used to realize the dynamic security evaluation. Experimental results demonstrate that the GFCIV-CGTOPSIS model, compared to the pre-improved GFRS-CGTOPSIS model, achieves reduced index tree redundancy and efficient dynamic security evaluation while exhibiting less information loss and lower evaluation result deviation due to index screening.