Location Privacy Protection of Data Elements in ICVs: A Key Update Mechanism for Defending Against Chosen-Ciphertext Attacks

In intelligent connected vehicles (ICVs) system, driving users connect to service providers (SPs) to obtain location-based services (LBS). Users transmit large volumes of encrypted sensitive information related to their itineraries to SPs to access value-added services. Attackers may launch chosen-ciphertext attacks (CCA) against SPs by exploiting the malleability of homomorphic encryption. This enables adversaries to infer or steal private key information, thereby threatening the long-term privacy of user data. Furthermore, existing key management technologies in ICVs system predominantly rely on passive defense strategies and suffer from limitations such as single protection mechanisms, delayed updates, and limited adaptability. To address these issues, this paper proposes an adaptive key update security mechanism based on a differential game framework. This mechanism treats the cumulative information leakage of the private key as a contested resource to construct a differential game model. Based on the feedback Nash equilibrium (NE), the mechanism adaptively derives the optimal homomorphic private key update frequency in response to the attack frequency, thereby maximizing the defense benefit. Finally, numerical simulations validate the correctness of the proposed model and demonstrate the effectiveness of the mechanism.