A secure flexible and tampering-resistant data sharing system for vehicular social networks - SUN, Jianfei (Institutional Knowledge at Singapore Management University, 2020)
Vehicular social networks (VSNs) have emerged as the promising paradigm of vehicular networks that can improve traffic safety, relieve traffic congestion and even provide comprehensive social services by sharing vehicular sensory data. To selectively share the sensory data with other vehicles in the vicinity and reduce the local storage burden of vehicles, the vehicular sensory data are usually outsourced to vehicle cloud server for sharing and searching. However, existing data sharing systems for VSNs can neither provide secure selective one-to-many data sharing and verifiable data retrieval over encrypted data nor ensure that the integrity of retrieved data. In this paper, we propose FTDS, a secure flexible and tampering-resistant data sharing system for VSNs by introducing a novel secure key-aggregate search encryption scheme and a tampering-resistant blockchain technology. With the proposed FTDS system for VSNs, the vehicular sensory data can be selectively shared and retrieved in a fine-grained way. Besides, our system allows vehicle data users to detect any unauthorized manipulation. Then, we present the detailed security analysis to prove that the proposed data sharing system can achieve both selective security and verifiability. We also evaluate its performance and demonstrate that it is efficient and practical for the VSNs scenarios.