Blockchain and Machine Learning Integrated Secure Driver Behavior Centric Electric Vehicle Insurance Model

被引:3
|
作者
Sahu, Brijmohan Lal [1 ]
Chandrakar, Preeti [1 ]
Kumari, Saru [2 ]
Chen, Chien-Ming [3 ]
Amoon, Mohammed [4 ]
机构
[1] Natl Inst Technol, Dept Comp Sci & Engn, Raipur 492010, Chhattisgarh, India
[2] Chaudhary Charan Singh Univ, Dept Math, Meerut 250001, Uttar Pradesh, India
[3] Nanjing Univ Informat Sci & Technol, Sch Artificial Intelligence, Nanjing 210044, Peoples R China
[4] King Saud Univ, Community Coll, Dept Comp Sci, Riyadh 11437, Saudi Arabia
关键词
Insurance; Blockchains; Vehicles; Electric vehicles; Sensors; Data models; Smart contracts; Accidental damage detection; blockchain; driver driving score; electric vehicular network; electric vehicle insurance; machine learning; PRIVACY;
D O I
10.1109/TITS.2024.3439822
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Traditional insurance policy models involve cumbersome multiparty verification and processing, leading to a prolonged and time-consuming procedure resulting in claim leakage. The existing insurance and blockchain-based systems have no module specifically for electric vehicles to cover physical damage. This becomes particularly significant in electric vehicles (EVs), where insurance is essential due to the high cost of vehicle parts and the vehicles themselves. Electric vehicles with various sensors and IoT devices are susceptible to physical damage and attacks. To address these challenges and provide robust financial support to policyholders, an enhanced blockchain-based electric vehicle insurance policy (BE-VIP) is proposed to cover vehicle damages. BE-VIP leverages sensory and telemetry data from vehicle sensors, IoT devices, and drivers' behavior for a more comprehensive analysis. However, the insecure nature of the public network in the internet of electric vehicles (IoEV) exposes it to various security threats and attacks. Recognizing this, BE-VIP emphasizes implementing a lightweight privacy-preserving and efficient authentication protocol to enhance network security. A secure driver-driving score (DDS) is proposed to reward and punish the vehicle based on driving behavioral data and easy insurance policy transfer from the previous owner to the current owner. To prevent fraudulent accidental claims, a YOLOv8 model-based damage detection model is combined with IPFS to create permanent evidence of an accident. The feasibility of the BE-VIP model is rigorously evaluated through a comprehensive analysis, considering factors such as computational complexity and gas consumption required for execution over the Ethereum blockchain network.
引用
收藏
页码:19073 / 19087
页数:15
相关论文
共 50 条
  • [31] Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management
    Wong, Simon
    Yeung, John-Kun-Woon
    Lau, Yui-Yip
    So, Joseph
    SUSTAINABILITY, 2021, 13 (15)
  • [32] Secure and transparent energy management using blockchain and machine learning anomaly detection: A case study of the Ausgrid dataset
    Moumni, Nourchen
    Chaabane, Faten
    Drira, Fadoua
    Boutaleb, Youssef
    COMPUTERS & INDUSTRIAL ENGINEERING, 2025, 203
  • [33] A Blockchain-Based Model Migration Approach for Secure and Sustainable Federated Learning in IoT Systems
    Zhang, Cheng
    Xu, Yang
    Elahi, Haroon
    Zhang, Deyu
    Tan, Yunlin
    Chen, Junxian
    Zhang, Yaoxue
    IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (08) : 6574 - 6585
  • [34] Blockchain for Emergency Vehicle Routing in Healthcare Services: An Integrated Secure and Trustworthy System
    Kaurav, Ramakant Singh
    Rout, Rashmi Ranjan
    Vemireddy, Satish
    2021 INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS & NETWORKS (COMSNETS), 2021, : 623 - 628
  • [35] Electric vehicle routing problem with machine learning for energy prediction
    Basso, Rafael
    Kulcsar, Balazs
    Sanchez-Diaz, Ivan
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2021, 145 : 24 - 55
  • [36] Blockchain-Integrated Deep Learning for Secure Health Data Sharing and Consent Management
    K Deepthika
    Shobana, G.
    Reddy, Kumbam Venkat
    Srimathi, S.
    Kumar, Binod
    Upadhyay, Shrikant
    2024 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT CYBER PHYSICAL SYSTEMS AND INTERNET OF THINGS, ICOICI 2024, 2024, : 101 - 106
  • [37] Vehicle insurance model using telematics system with improved machine learning techniques: A survey
    Kanta Reddy T.M.
    Premamayudu B.
    Ing. Syst. Inf., 2019, 5 (507-512): : 507 - 512
  • [38] Blockchain and Machine Learning Inspired Secure Smart Home Communication Network
    Menon, Subhita
    Anand, Divya
    Kavita
    Verma, Sahil
    Kaur, Manider
    Jhanjhi, N. Z. M.
    Ghoniem, Rania
    Ray, Sayan Kumar
    SENSORS, 2023, 23 (13)
  • [39] Design of Blockchain-based Secure Electric Vehicle Charging System Using ECC
    Dwivedi, Sanjeev Kumar
    Amin, Ruhul
    Vollala, Satyanarayana
    2022 INTERNATIONAL CONFERENCE ON COMPUTER, INFORMATION AND TELECOMMUNICATION SYSTEMS, CITS, 2022, : 36 - 40
  • [40] Learning and Unlearning to Operate Profitable Secure Electric Vehicle Charging
    Lee, Sangyoon
    Choi, Dae-Hyun
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (09) : 11213 - 11223