面向降频污染攻击的智能交通拥堵态势量化分析
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TP309

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中央高校基本科研业务费专项资金(2021JBM006); 国家自然科学基金(61972025, 61802389, 61672092, U1811264, 61966009); 国家重点研发计划(2020YFB1005604, 2020YFB2103802)


Quantified Analysis of Congestion Situation in Intelligent Transportation Towards Frequency-reduced Spoofing Attack
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    摘要:

    随着网联车辆的快速发展和开放化, 智能信号灯规划系统承受着巨大的网络攻击风险. 已有相关研究发现, 定频数据污染对规划脆弱性的攻击造成了交通拥堵爆增, 但缺乏对降频污染攻击的全时序拥堵态势量化与分析, 在检测预警与持续对抗方面有一定的局限性. 将开源智能信号灯规划系统I-SIG及其规划算法COP作为研究对象, 提出一种面向多个降频污染攻击的统一拥堵态势量化与分析框架, 构造态势发展的时空序列三阶张量空间, 并设计极值分析、平稳性分析和关联性分析, 实现基于函数依赖关系的一体化分析方法. 在交通模拟环境VISSIM平台上, 验证了该量化分析的有效性并报告新发现.

    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,,():1-16

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  • 收稿日期:2020-12-21
  • 最后修改日期:2021-05-08
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  • 在线发布日期: 2022-07-15
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