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汽車(chē)CAN總線入侵檢測(cè)算法性能模糊測(cè)試方法研究
信息技術(shù)與網(wǎng)絡(luò)安全 4期
田韻嵩1,,李中偉1,譚 凱1,,洪 晟2,,劉 勇1,金顯吉1
(1.哈爾濱工業(yè)大學(xué) 電氣工程及自動(dòng)化學(xué)院,,黑龍江 哈爾濱150001,; 2.北京航空航天大學(xué) 網(wǎng)絡(luò)空間安全學(xué)院,北京100191)
摘要: 針對(duì)目前汽車(chē)CAN總線入侵檢測(cè)算法性能模糊測(cè)試方法因測(cè)試用例覆蓋率低,、針對(duì)性差而導(dǎo)致的測(cè)試結(jié)果可信度不高的問(wèn)題,,提出一種改進(jìn)的汽車(chē)CAN總線入侵檢測(cè)算法性能模糊測(cè)試方法。針對(duì)是否已知CAN總線協(xié)議規(guī)范的情況分別基于字段權(quán)重和改進(jìn)Wasserstein生成對(duì)抗網(wǎng)絡(luò)(WGAN-GP)生成模糊測(cè)試用例,,對(duì)KNN算法和AdaBoost算法進(jìn)行了測(cè)試,,測(cè)試結(jié)果表明,AdaBoost算法的檢測(cè)性能優(yōu)于KNN算法,。試驗(yàn)驗(yàn)證了所提出的測(cè)試方法用于測(cè)試入侵檢測(cè)算法的性能能夠得到可信度較高的試驗(yàn)結(jié)果,,達(dá)到了為汽車(chē)CAN總線入侵檢測(cè)算法的選用提供參考依據(jù)的目的。
中圖分類號(hào): TP306.2
文獻(xiàn)標(biāo)識(shí)碼: A
DOI: 10.19358/j.issn.2096-5133.2022.04.005
引用格式: 田韻嵩,,李中偉,,譚凱,等. 汽車(chē)CAN總線入侵檢測(cè)算法性能模糊測(cè)試方法研究[J].信息技術(shù)與網(wǎng)絡(luò)安全,,2022,,41(4):32-38.
Research on fuzzy test method of the detection ability of in-vehicle CAN bus intrusion detection algorithm
Tian Yunsong1,Li Zhongwei1,,Tan Kai1,,Hong Sheng2,Liu Yong1,,Jin Xianji1
(1.School of Electrical Engineering and Automation,,Harbin Institute of Technology,Harbin 150001,,China,; 2.School of Cyber Science and Technology,Beihang University,,Beijing 100191,,China)
Abstract: The test results of the current vehicle CAN bus intrusion detection algorithm performance fuzzy test method are not highly reliable, due to the low test case coverage and poor pertinence. Aiming at this problem,an improved in-vehicle CAN bus intrusion detection algorithm performance fuzzy test method was proposed. According to whether the CAN bus protocol specification was known or not, fuzzy test cases were generated based on field weights or improved Wasserstein Generative Adversarial Network(WGAN-GP). The generated test cases were used to test the KNN algorithm and the AdaBoost algorithm. The test results showed that the detection performance of the AdaBoost algorithm was better than that of the KNN algorithm. The test verified that the test method proposed in this paper can obtain the test results with high reliability when used to test the performance of the intrusion detection algorithm, and achieved the purpose of providing a reference for the selection of the intrusion detection algorithm of the in-vehicle CAN bus.
Key words : intrusion detection algorithm,;detecting ability test,;Controller Area Network(CAN);Generative Adversarial Network(GAN),; fuzzy test

0 引言

現(xiàn)代汽車(chē)智能化功能越來(lái)越豐富,,汽車(chē)與外部的信息交互越來(lái)越頻繁,,汽車(chē)網(wǎng)絡(luò)被入侵的風(fēng)險(xiǎn)越來(lái)越高[1]。而入侵檢測(cè)算法被應(yīng)用于汽車(chē)CAN總線網(wǎng)絡(luò)安全防御中,,其檢測(cè)惡意攻擊的能力將對(duì)汽車(chē)CAN總線網(wǎng)絡(luò)的安全性產(chǎn)生影響,。

入侵檢測(cè)算法能夠識(shí)別外部針對(duì)網(wǎng)絡(luò)資源的惡意操作,也能夠檢測(cè)內(nèi)部用戶的違規(guī)或未授權(quán)的非法行為,。目前,,入侵檢測(cè)算法從檢測(cè)技術(shù)的角度可分為以下3類:(1)基于規(guī)則的入侵檢測(cè)算法;(2)基于統(tǒng)計(jì)的入侵檢測(cè)算法,;(3)基于機(jī)器學(xué)習(xí)的入侵檢測(cè)算法[2],。其中基于機(jī)器學(xué)習(xí)的入侵檢測(cè)算法能夠利用龐大的已有數(shù)據(jù)進(jìn)行學(xué)習(xí),發(fā)現(xiàn)內(nèi)在規(guī)律,,實(shí)現(xiàn)網(wǎng)絡(luò)攻擊行為檢測(cè)的智能化,。并且機(jī)器學(xué)習(xí)具備預(yù)測(cè)能力,,對(duì)未知模式的攻擊也具備一定的檢測(cè)能力,,是目前熱門(mén)的入侵檢測(cè)算法研究領(lǐng)域,。



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作者信息:

田韻嵩1,,李中偉1,,譚  凱1,,洪  晟2,,劉  勇1,,金顯吉1

(1.哈爾濱工業(yè)大學(xué) 電氣工程及自動(dòng)化學(xué)院,,黑龍江 哈爾濱150001;

2.北京航空航天大學(xué) 網(wǎng)絡(luò)空間安全學(xué)院,,北京100191)


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