This study aims to address cyberattack issues on the connected automated vehicle (CAV) by regarding a CAV platoon as a spring-mass system from the perspective of vibration mechanics. With the similarities between cyberattacks on the CAV platoon system and an external force on spring-mass systems, we further proposed a Fourier analysis approach to formulate cyberattacks into longitudinal vehicle dynamical models based on the fundamental physical law of the springs-mass systems. The proposed approach is applied to general car-following models with various amplitudes and frequencies attacking patterns to generate insights into the cyberattack effects. Then this study applies the intelligent driver model to uncover the characteristics of traffic flow dynamics under cyberattacks. Simulation results demonstrate that attacking amplitude, frequency and attacking duration can cause stop-and-go waves and traffic accidents, and reveal the oscillation mechanism of traffic under different attacking patterns. The findings shed light on innovative solutions against cyberattack and contribute to reducing congestions and eliminating traffic safety concerns.

CICTP