%A Chengbin ZHANG,Hui ZHAO,Zongyu CAO %T The vulnerability mining method for KWP2000 protocol based on deep learning and fuzzing %0 Journal Article %D 2019 %J Journal of Shandong University(Engineering Science) %R 10.6040/j.issn.1672-3961.0.2018.340 %P 17-22 %V 49 %N 2 %U {http://gxbwk.njournal.sdu.edu.cn/CN/abstract/article_1804.shtml} %8 2019-04-20 %X

A kind of vehicle-onboard diagnosis Protocol standard, keyword protocol 2000 (KWP2000) KWP2000, was investigated in details. KWP2000 was widely used in the automobile industry and the loophole of possible communication Protocol. We analyzed the current situations of the fuzzing, and based on this, we proposed a generative adversarial networks (GAN) by deep learning neural network for automobile body network KWP2000 protocol hole mining method. The forward feedback network was closeted as the generation model, and the support vector machine was used as the discriminant model. We used the neural network model to train the test case data of the KWP2000 protocol data, the fuzzing of KWP2000 was carried out by using these test case data. Through experiments, we found that the target protocol KWP2000 had long loopholes, coding errors and other vulnerabilities. Experimental results showed that this fuzzing method was efficient and safe.