Heterogeneous Blockchain and AI-Driven Hierarchical Trust Evaluation for 5G-Enabled Intelligent Transportation Systems

【Author】 Wang, Xiaoding; Garg, Sahil; Lin, Hui; Kaddoum, Georges; Hu, Jia; Hassan, Mohammad Mehedi

【Source】IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

【影响因子】9.551

【Abstract】The fifth-generation (5G) wireless communication technology enables high-reliability and low-latency communications for the Intelligent Transportation System (ITS). However, the growingly sophisticated attacks against 5G-enabled ITS (5G-ITS) might cause serious damages to the valuable data generated by various ITS applications. Therefore, establishing a secure 5G-ITS through trust evaluation against potential threats has become a key objective. Furthermore, as a distributed shared ledger and database, Blockchain has the characteristics of non-tampering, traceability, openness and transparency, can support both trust storage and trust verification for trust evaluation. In this paper, we propose a heterogeneous Blockchain based Hierarchical Trust Evaluation strategy, named BHTE, utilizing the federated deep learning technology for 5G-ITS. Specifically, the trusts of ITS users and task distributers are evaluated using the federated deep learning and hierarchical incentive mechanisms are designed for reasonable and fair rewards and punishments. Moreover, the trusts of ITS users and task distributers are stored on heterogeneous and hierarchical blockchains for trust verification. The extensive experiment results show that: (i) the proposed BHTE can achieve reasonable and fair trust evaluations on both ITS users and task distributers; (ii) the BHTE performs excellently with high system throughput and low latency.

【Keywords】Task analysis; Blockchains; Transportation; Trust management; Privacy; Intelligent transportation systems; 5G mobile communication; Blockchain; trust evaluation; 5G; intelligent transportation systems; federated learning

【发表时间】

【收录时间】2022-01-01

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