Securing vehicle network suspension control: lightweight homomorphic encryption with fuzzy rules

With the rapid development of the internet of vehicles, electromagnetic suspension systems, which ensure ride comfort and handling stability by adjusting stiffness and damping based on sensor data, face critical data tampering threats. Malicious manipulation of data can lead to improper adjustments, excessive vibration, component wear, or even instability. Balancing real-time control, limited onboard resources, and data security is a challenging task. This study proposes an anti-tampering scheme integrating lightweight torus fully homomorphic encryption and fuzzy rule-based control. The torus fully homomorphic encryption method encrypts sensor data in transit, utilising torus fully homomorphic encryption, to ensure confidentiality and integrity while enabling real-time computations. Fuzzy rules handle uncertainty, allowing adaptive decisions on encrypted data. Simulations show that the scheme reduces sprung mass vertical acceleration by 35% compared to unprotected systems, with a total processing latency of 25.8 ms, meeting real-time requirements. It achieves robust tampering resistance, enhanced security.