TP-IoAV: A tri-party cloud data protection scheme for Internet of Autonomous Vehicle coupled with chaotic biometric cryptography

Ze Yu, Zhenlong Man, Jiahui Yu, Zhang Yong Qin

Abstract: As driverless technology advances, an immense amount of data will be generated, shared, and used between vehicles, users, and the cloud. This includes road conditions, GPS data, biometric data, which raises significant privacy concerns. This paper presents a secure authentication protocol and privacy protection framework based on chaotic biological cryptography for data sharing and storage in the Internet of Autonomous Vehicles(IoAV) framework. A biometric key generator is designed using single-modal multi-fingerprint feature-level reconstruction, allowing users to generate personalized private key pools. This protects biometric data in the cloud while ensuring revocability. By incorporating a nonlinear control function into the traditional three-dimensional Rucklidge chaotic system, a 4D-Yoz hyperchaotic system is created, ensuring secure key distribution and adherence to the ``one time pad'' principle. To verify the effectiveness of the chaos creature password and ensure the security of cloud-stored images, proposes an image encryption-storage algorithm based on the ``$L_\infty$'' metric and the semi-tensor product of the matrix, introducing the chaotic biological key. Experimental simulations and performance analysis show that this algorithm effectively secures image data in the Internet of Vehicles.