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Home > Archive>Volume 34, Issue 2, 2023 >833-848. DOI:10.13328/j.cnki.jos.006416
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Quantified Analysis of Congestion Situation in Intelligent Transportation Towards Frequency-reduced Spoofing Attack
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TP309

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    Abstract:

    With the development and openness of connected vehicle, the planning system of intelligent signal system (I-SIG system) has a big security threat from network attack. Former work has revealed that a frequency-fixed data spoofing attack to the planning weakness can cause a heavy traffic congestion. However, there is still very limited knowledge for security detection, warning, and defense, and there is no work that provides a full time-serial congestion situation quantification and analysis for various attack frequency from high to low. Targeting the open source I-SIG system and its COP planning algorithm, this study proposes a unified framework to quantify and analyze the congestion situation under multiple spoofing attack from high to low frequency. Firstly, a space-time tensor space of three ordersis constructed. Based on tensor computation, a function-dependent integrated analysis approach is implemented, in which the max-min analysis, stationarity analysis, and correlation analysis are developed. Experiments on the traffic simulation platform VISSIM show the effectiveness of quantification and analysis, and demonstrate that the results are meaningful.

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相迎宵,李轶珂,刘吉强,王潇瑾,陈彤,童恩栋,牛温佳,韩臻.面向降频污染攻击的智能交通拥堵态势量化分析.软件学报,2023,34(2):833-848

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History
  • Received:December 21,2020
  • Revised:May 08,2021
  • Online: July 15,2022
  • Published: February 06,2023
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