With the development and openness of connected vehicle, the planning system of intelligent signal system (I-SIG system) has a big security threat from network attack. Former work has revealed that a frequency-fixed data spoofing attack to the planning weakness can cause a heavy traffic congestion. However, there is still very limited knowledge for security detection, warning, and defense, and there is no work that provides a full time-serial congestion situation quantification and analysis for various attack frequency from high to low. Targeting the open source I-SIG system and its COP planning algorithm, this study proposes a unified framework to quantify and analyze the congestion situation under multiple spoofing attack from high to low frequency. Firstly, a space-time tensor space of three ordersis constructed. Based on tensor computation, a function-dependent integrated analysis approach is implemented, in which the max-min analysis, stationarity analysis, and correlation analysis are developed. Experiments on the traffic simulation platform VISSIM show the effectiveness of quantification and analysis, and demonstrate that the results are meaningful.