Intrusion Detection Scheme in Vehicular Ad-hoc Complex Network
编号:209 访问权限:仅限参会人 更新:2022-09-13 09:27:51 浏览:119次 张贴报告

报告开始:2021年12月17日 09:42(Asia/Shanghai)

报告时间:1min

所在会场:[P1] Poster2020 [P1T1] Track 1 Advanced Transportation Information and Control Engineering

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摘要
Based on principal component analysis and Apriori association rule mining algorithm, a method of using big data technology to study the intrusion detection scheme and operational vulnerability of Vehicular Ad-hoc Network (VANET) was proposed. The data comes from the China Automotive Test Cycle (CATC) and Natural Science Foundation of Inner Mongolia (2019MS07021), to mine key evaluation indicators from big data using principal component analysis method; for key indicators, parallel association rule model is used to mine strong association rules and then find out the main influencing factors; Finally, based on the artificial neural network prediction method and historical data, the main influencing factor values were input, and the key evaluation index values were output, and a case study was carried out to predict the reliability indicators of future VANET operation. The results showed that the proposed method was more accurate.
关键词
VANET;intrusion detection;big data;Apriori
报告人
Hong Zhang
Inner Mongolia University

Zhang Hong was born in Inner Mongolia Autonomous Region. She got her Bachelor’s degree in Transportation and Master’s degree in Transportation Planning and Management in the School of Transportation Science and Engineering, Harbin Institute of Technology, China, from 2001 to 2007, and Doctor’s degree in Management Science and Engineering in the School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, China, from 2012 to 2015. Doctoral thesis: Research of Vehicular Ad Hoc Network Based on Complex Network Theory. She is an Associate Professor at Transportation Institution of Inner Mongolia University, China (2016–present). Her research interest includes Intelligent Network of Vehicles: Vehicular Ad Hoc Network, Complex Network and Transportation: Transportation Planning and Management. Her study was financially supported by Natural Science Foundation of Inner Mongolia (2019MS07021) and Transportation Department of Inner Mongolia Autonomous Region (NJ-2017-8).

稿件作者
HONG ZHANG Inner Mongolia University
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重要日期
  • 会议日期

    12月17日

    2021

    12月20日

    2021

  • 12月16日 2021

    报告提交截止日期

  • 12月24日 2021

    注册截止日期

主办单位
Chinese Overseas Transportation Association
Chang'an University
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