Enhancing Byzantine-Fault-Tolerant Consensus in Permissioned Blockchain-Empowered Vehicle-to-Everything (V2X) Network Via Multitask Learning: A Review - Hussaini, Dan’azumi; Umar Zambuk, Fatima; Iman Ya’u , Badamasi; Auwal, Ajiya (BIMA JOURNAL OF SCIENCE AND TECHNOLOGY GOMBE, 2024)
This research work discusses the improvement of a specific consensus mechanism called Byzantine Fault-Tolerant (BFT) within a permissioned blockchain-based network designed for Vehicle-to-Everything (V2X) communication. The main objective is to make the consensus protocols of this network more robust in the face of attacks from malicious participants. A method to achieve this improvement by using a robust adversarial training technique known as the Fast Gradient Sign Method is suggested. This technique aims to counteract the negative effects of malicious nodes within the V2X network. The research work also delves into the recent advancements in the fields of distributed systems, blockchain technology, and consensus mechanisms. This exploration is conducted to improve and strengthen the security and reliability of communication networks used in V2X scenarios. The significance of ensuring the resilience and ability to withstand adversarial actions in environments involving vehicles, where the stability and resistance to malicious behavior are of utmost importance is emphasized. Our work has open future direction for interested researchers in this area.