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The field of intelligent connected in modern vehicles continues to expand,and the functions of vehicles become more and more complex with the developmentof the times. This has also led to an increasing number of vehiclevulnerabilities and many safety issues. Therefore, it is particularly importantto identify high-risk vehicle intelligent connected systems, because it caninform security personnel which systems are most vulnerable to attacks,allowing them to conduct more thorough inspections and tests. In this paper, wedevelop a new model for vehicle risk assessment by combining I-FAHP with FCAclustering: VSRQ model. We extract important indicators related to vehiclesafety, use fuzzy cluster analys (FCA) combined with fuzzy analytic hierarchyprocess (FAHP) to mine the vulnerable components of the vehicle intelligentconnected system, and conduct priority testing on vulnerable components toreduce risks and ensure vehicle safety. We evaluate the model on OpenPilot andexperimentally demonstrate the effectiveness of the VSRQ model in identifyingthe safety of vehicle intelligent connected systems. The experiment fullycomplies with ISO 26262 and ISO/SAE 21434 standards, and our model has a higheraccuracy rate than other models. These results provide a promising new researchdirection for predicting the security risks of vehicle intelligent connectedsystems and provide typical application tasks for VSRQ. The experimentalresults show that the accuracy rate is 94.36%, and the recall rate is 73.43%,which is at least 14.63% higher than all other known indicators.

VSRQ: Quantitative Assessment Method for Safety Risk of Vehicle Intelligent Connected System