Blockchain-based Privacy-Preserving Driver Monitoring for MaaS in the Vehicular IoT

Abstract : Driving behaviors are highly relevant to automotive statuses and on-board safety, which offer compelling shreds of evidence for mobility as a service (MaaS) providers to develop personalized rental prices and insurance products. However, the direct dissemination of driving behaviors may lead to violations of identity and location privacy. In this paper, our proposed mechanism first achieves the verifiable aggregation and immutable dissemination of performance records by exploiting a blockchain with the proof-of-stake (PoS) consensus. Moreover, to acquire a driver's aggregated performance record from the blockchain, the proposed scheme first realizes quick identification with a Bloom filter and further approaches the target performance record through an oblivious transfer (OT) protocol. A performance evaluation shows that during the acquisition of the records, the computational complexity of our scheme is only related to the scale of the records contained in one transaction. However, the computational complexity of one traditional scheme without a Bloom filter depends on the scale of the records generated during each time slot. Furthermore, the computational complexity of another traditional scheme without aggregation relies on the scale of the records contained in one transaction, as well as the length of a driver's performance history. We also investigate the trade-off between the privacy level and computational complexity, and we determine the optimal number of data records in each transaction.

 EXISTING SYSTEM :

 ? The existing technologies, blockchain is the most promising one to meet these new security requirements and reshape the 5G communication landscape. ? Despite growing interest in blockchain and 5G, the focus of existing survey works is on each of the specific technologies. ? With the help of innovative blockchain designs, 5G is expected to overcome the existing challenges and open up new opportunities to empower blockchain 5G-based services and applications. ? The existing 5G technology infrastructure has remained unsolved challenges in terms of security, networking and computing performance degradation due to its centralized architecture.

 DISADVANTAGE :

 ? The IoV has the potential to solve various traffic and road safety problems effectively in order to prevent fatal crashes. ? In order to overcome these challenges, this work is adapting Blockchain technology for real time application (RTA) to solve Vehicle-to-Everything (V2X) communications problems. ? These allow an AI system to learn how to solve problems that cannot be specified, or whose solution method cannot be described by symbolic reasoning rules. ? On the other hand, for the public sector MaaS services may be seen as an option to battle some of their mobility, sustainability and urban space problems.

 PROPOSED SYSTEM :

 • To achieve these objectives, several underlying wireless technologies have been proposed to enable future 5G networks, including cloud computing, edge computing, Software Defined Networking (SDN), Network Function Virtualization (NFV), Network Slicing, and D2D communication. • The study proposed a cloud-centric IoT framework enabled by smart contracts and blockchain for secure data provenance. • The proposed scheme contains three tiers with an IoT sensor network, a federation of multiple clouds, and a service platform. • Multiple SDN controllers in this proposed approach can communicate each other and interact with blockchain which enables secure information exchanges between them.

 ADVANTAGE :

 ? Algorithms can also replace human actions and decisions for individual agents in the logistics chain. It is expected that self-learning algorithms (AI) can improve decisions and therewith the performance of the logistics chain based on big data from sensors a lot. ? The main objectives of C-ITS applications are to improve traffic safety and/or transport efficiency (including reduction of congestion) and/or environmental performance. ? With a decrease of movements needed because of efficiency increase and occupancy rates, less energy is needed to reach the same performance. ? Smart agents are optimising their performance based on local information and local intelligence.