Secured Vehicle Life Cycle Tracking Using Blockchain and Smart Contract

【Author】 Bragadeesh, Srinivasan Ananthanarayanan; Umamakeswari, Arumugam

【Source】COMPUTER SYSTEMS SCIENCE AND ENGINEERING

【影响因子】4.397

【Abstract】Life Cycle Tracking (LCT) involves continuous monitoring and analysis of various activities associated with a vehicle. The crucial factor in the LCT is to ensure the validity of gathered data as numerous supply chain phases are involved and the data is assessed by multiple stakeholders. Frauds and swindling activities can be prevented if the history of the vehicles is made available to the interested parties. Blockchain provides a way of enforcing trustworthiness to the supply chain participants and the data associated with the various actions performed. Machine learning techniques when combined decentralized nature of blockchains can be used to develop a robust Vehicle LCT model. In the proposed work, Harmonic Optimized Gradient Descent and Lukasiewicz Fuzzy (HOGDLF) Vehicle Life Cycle Tracking in Cloud Environment is proposed and it involves three stages. First, the Progressive Harmonic Optimized User Registration and Authentication model is designed for computationally efficient registration and authentication. Next, for the authentic user, the Gradient Descent Blockchain-based SVM Data Encryption model is designed with minimum CPU utilization. Finally, Lukasiewicz Fuzzy Smart Contract Verification is performed with encrypted data to ensure accurate and precise fraudulent activity deduction. The experimental analysis shows that the proposed method achieves significant performance in terms of life cycle's prediction time, overhead, and accuracy for a different number of users.

【Keywords】Vehicle life cycle tracking; progressive harmonic optimization; blockchain; gradient descent; Lukasiewicz fuzzy; smart contract

【发表时间】2022

【收录时间】2022-08-16

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