Augmented IoT Cooperative Vehicular Framework Based on Distributed Deep Blockchain Networks

This paper presents the augmented Internet of Things (AIoT) framework for cooperatively distributed deep blockchain-assisted vehicle networks. AIoT framework splits the vehicle application into various tasks while executing them on different computing nodes. The vehicle application has different constraints, such as security, time, and accuracy, which are considered during processing them on parallel computing nodes (e.g., fog and cloud). We propose a partitioned AIoT scheme, dividing vehicular tasks into local and remote tasks. The objective is to minimize delays and efficiently execute urgent tasks such as vehicle, pedestrian, and traffic signals on local vehicles. The existing blockchain technologies suffer from many security issues, such as anonymous node issues and malware attacks in blockchain blocks. This is why we present the combined deep convolutional neural network (DCNN)-assisted proof-of-trust miner (PoTM) scheme. It safely handles tasks in different blocks. The smart contract is a human-written piece of code in blockchain technologies so that malicious code can be integrated into blockchain blocks during the registration of vehicles among nodes. The main limitation of smart contracts is that they are not changeable and cannot be changed once executed for any block. To avoid this situation, we present an augmented adaptive Trust Management Credibility Score Scheme (TMCSS) scheme that registers the vehicles before starting any services at blockchain miners. These registration certificates are changeable once DCNN detects any malicious activity in the vehicle data. Simulation results show that the proposed schemes improved delays by 35%, reduced the failure ratio of transactions by 39%, and enhanced overall transactions with the minimum failure compared to existing blockchain technologies for road-cooperation services in networks.