Dhairya Jadav, M. Obaidat, S. Tanwar, Rajesh Gupta, K. Hsiao
{"title":"Amalgamation of Blockchain and AI to Classify Malicious Behavior of Autonomous Vehicles","authors":"Dhairya Jadav, M. Obaidat, S. Tanwar, Rajesh Gupta, K. Hsiao","doi":"10.1109/cits52676.2021.9618005","DOIUrl":null,"url":null,"abstract":"Blockchain is a prevalent technology whose applications are aimed towards security, privacy, traceability and trust. One such application is autonomous vehicles (AVs). The biggest concern of AVs is their safety. A malicious AV can cause accidents that may be life-threatening. We have proposed a blockchain and ensemble learning-based system to classify the vehicles as malicious to address the aforementioned safety issue. Smart contracts for AVs transaction verification have been designed to count the number of malicious activities performed by any AV. Finally, results show that the proposed model achieved the goal of this paper with an accuracy of 97.5 %.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cits52676.2021.9618005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Blockchain is a prevalent technology whose applications are aimed towards security, privacy, traceability and trust. One such application is autonomous vehicles (AVs). The biggest concern of AVs is their safety. A malicious AV can cause accidents that may be life-threatening. We have proposed a blockchain and ensemble learning-based system to classify the vehicles as malicious to address the aforementioned safety issue. Smart contracts for AVs transaction verification have been designed to count the number of malicious activities performed by any AV. Finally, results show that the proposed model achieved the goal of this paper with an accuracy of 97.5 %.