Intelligent Connected Vehicle Data Security Protection Scheme Based on Federated Learning and Blockchain
Year: 2025
Type: conference-paper
Abstract: While Intelligent Connected Vehicles (ICV) improve travel convenience, they also bring new security risks, especially how to achieve data security protection for the Internet of Vehicles (IoV), which has become a key bottleneck restricting the development of ICV and has received widespread attention from academic and industrial circles at home and abroad. Based on a comprehensive analysis of the data security risks faced by ICV, this article conducts a comprehensive comparative study of relevant solutions at home and abroad, and proposes an ICV data security protection model framework based on Federated Learning (FL) and blockchain technology. FL is used to solve the privacy leakage risk caused by raw data sharing in traditional architecture of IoV, while differential privacy technology is used to protect model parameters, and blockchain technology is used to address risks such as single point failures in FL. This framework provides a new idea for data security protection for ICV.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Awards: G3106563813, G3985989773
OpenAlex ID: W4411846438