Research on Terminal Fingerprint Extraction and Temperature Adaptability Based on CAN Bus

Wei Fang, Jiabao Yu, Yanjun Ding, Xiaozhong Hu, Sheng Li, Aiqun Hu
{"title":"Research on Terminal Fingerprint Extraction and Temperature Adaptability Based on CAN Bus","authors":"Wei Fang, Jiabao Yu, Yanjun Ding, Xiaozhong Hu, Sheng Li, Aiqun Hu","doi":"10.1109/ICCT56141.2022.10073172","DOIUrl":null,"url":null,"abstract":"Controller Area Network (CAN) is a bus standard commonly used in the automotive industry. A large number of researches have been carried out on the identity authentication and intrusion detection technology of the in-vehicle network for attacks. This paper presents a method to extract the voltage of CAN bus terminal to obtain the equipment fingerprint. The method identifies different ECUs by measuring the voltage difference on the vehicle network, selects features only from the time domain and detects based on a single frame. This paper mainly focuses on the influence of temperature on the fingerprint of CAN bus terminal. By using a high and low temperature test chamber to simulate different temperature environments during vehicle operation, a large number of CAN frames have been collected for fingerprint extraction. By studying the relationship between temperature and CAN bus terminal fingerprint, the influence of temperature on fingerprint has been compensated. After temperature linear compensation, the recognition rate of voltage-based CAN bus terminal fingerprint extraction increases from 71.2% to 87.6% at 0–80 °C.","PeriodicalId":294057,"journal":{"name":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","volume":"26 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT56141.2022.10073172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Controller Area Network (CAN) is a bus standard commonly used in the automotive industry. A large number of researches have been carried out on the identity authentication and intrusion detection technology of the in-vehicle network for attacks. This paper presents a method to extract the voltage of CAN bus terminal to obtain the equipment fingerprint. The method identifies different ECUs by measuring the voltage difference on the vehicle network, selects features only from the time domain and detects based on a single frame. This paper mainly focuses on the influence of temperature on the fingerprint of CAN bus terminal. By using a high and low temperature test chamber to simulate different temperature environments during vehicle operation, a large number of CAN frames have been collected for fingerprint extraction. By studying the relationship between temperature and CAN bus terminal fingerprint, the influence of temperature on fingerprint has been compensated. After temperature linear compensation, the recognition rate of voltage-based CAN bus terminal fingerprint extraction increases from 71.2% to 87.6% at 0–80 °C.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于CAN总线的终端指纹提取及温度自适应研究
控制器局域网(CAN)是汽车工业中常用的总线标准。针对车载网络攻击的身份认证和入侵检测技术已经进行了大量的研究。提出了一种提取CAN总线终端电压以获取设备指纹的方法。该方法通过测量车辆网络上的电压差来识别不同的ecu,仅从时域中选择特征,并基于单帧进行检测。本文主要研究温度对CAN总线终端指纹的影响。利用高低温试验箱模拟车辆运行过程中不同的温度环境,采集了大量CAN帧进行指纹提取。通过研究温度与CAN总线终端指纹的关系,补偿了温度对指纹的影响。温度线性补偿后,电压型CAN总线终端指纹提取在0 ~ 80℃的识别率由71.2%提高到87.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Anomaly Detection Method For Interactive Data of Third-Party Load Aggregation Platform Based on Multidimensional Feature Information Fusion Stable and Robust Improvement of AMP for Supporting Massive Connectivity Power Allocation and Beamforming Vectors Optimization in STAR-RIS Assisted SWIPT Joint Identification of Modulation and Channel Coding Based on Deep Learning Geometric Feature Detection of Space Targets Based on Color Space
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1