发布求助
文献互助 智能选刊 最新文献

Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security最新文献

筛选
英文 中文
A Framework for Consistent and Repeatable Controller Area Network IDS Evaluation 一种一致性和可重复控制器局域网IDS评估框架
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23031
Paul Agbaje, A. Anjum, Arkajyoti Mitra, Gedare Bloom, Habeeb Olufowobi
{"title":"A Framework for Consistent and Repeatable Controller Area Network IDS Evaluation","authors":"Paul Agbaje, A. Anjum, Arkajyoti Mitra, Gedare Bloom, Habeeb Olufowobi","doi":"10.14722/autosec.2022.23031","DOIUrl":"https://doi.org/10.14722/autosec.2022.23031","url":null,"abstract":"—The landscape of automotive vehicle attack surfaces continues to grow, and vulnerabilities in the controller area network (CAN) expose vehicles to cyber-physical risks and attacks that can endanger the safety of passengers and pedestrians. Intrusion detection systems (IDS) for CAN have emerged as a key mitigation approach for these risks, but uniform methods to compare proposed IDS techniques are lacking. In this paper, we present a framework for comparative performance analysis of state-of-the-art IDSs for CAN bus to provide a consistent methodology to evaluate and assess proposed approaches. This framework relies on previously published datasets comprising message logs recorded from a real vehicle CAN bus coupled with traditional classifier performance metrics to reduce the discrepancies that arise when comparing IDS approaches from disparate sources.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124566264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Demo: Understanding the Effects of Paint Colors on LiDAR Point Cloud Intensities 演示:了解油漆颜色对激光雷达点云强度的影响
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23039
Shaik Sabiha, Keyan Guo, Foad Hajiaghajani, Chunming Qiao, Hongxin Hu, Ziming Zhao
{"title":"Demo: Understanding the Effects of Paint Colors on LiDAR Point Cloud Intensities","authors":"Shaik Sabiha, Keyan Guo, Foad Hajiaghajani, Chunming Qiao, Hongxin Hu, Ziming Zhao","doi":"10.14722/autosec.2022.23039","DOIUrl":"https://doi.org/10.14722/autosec.2022.23039","url":null,"abstract":"—Light Detection And Ranging (LiDAR) is a critical component in autonomous vehicles that aid in object detection. It generates point clouds by projecting light rays to its surround- ings. This demo studies the effect of paint colors on autonomous driving perception. The experiment results show different colors do affect LiDAR sensor’s point cloud intensity.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126336950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Demo: Security of Multi-Sensor Fusion based Perception in AD under Physical-World Attacks 演示:基于多传感器融合的AD感知在物理世界攻击下的安全性
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23038
Yulong Cao, Ningfei Wang, Chaowei Xiao, Dawei Yang, Jin Fang, Ruigang Yang, Qi Alfred Chen, Mingyan Liu, Bo Li
{"title":"Demo: Security of Multi-Sensor Fusion based Perception in AD under Physical-World Attacks","authors":"Yulong Cao, Ningfei Wang, Chaowei Xiao, Dawei Yang, Jin Fang, Ruigang Yang, Qi Alfred Chen, Mingyan Liu, Bo Li","doi":"10.14722/autosec.2022.23038","DOIUrl":"https://doi.org/10.14722/autosec.2022.23038","url":null,"abstract":"—In autonomous driving (AD) vehicles, Multi-Sensor Fusion (MSF) is used to combine perception results from multiple sensors such as LiDARs (Light Detection And Ranging) and cam- eras for both accuracy and robustness. In this work, we design the first attack that fundamentally defeats MSF-based AD perception by generating 3D adversarial objects. This demonstration will include video and figure demonstrations for the generated 3D adversarial objects and the end-to-end consequences.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115617120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
WIP: On Robustness of Lane Detection Models to Physical-World Adversarial Attacks 车道检测模型对物理世界对抗性攻击的鲁棒性研究
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23037
Takami Sato, Qi Alfred Chen
{"title":"WIP: On Robustness of Lane Detection Models to Physical-World Adversarial Attacks","authors":"Takami Sato, Qi Alfred Chen","doi":"10.14722/autosec.2022.23037","DOIUrl":"https://doi.org/10.14722/autosec.2022.23037","url":null,"abstract":"—Deep Neural Network (DNN)-based lane detection is widely utilized in autonomous driving technologies. At the same time, recent studies demonstrate that adversarial attacks on lane detection can cause serious consequences on particular production-grade autonomous driving systems. However, the gen- erality of the attacks, especially their effectiveness against other state-of-the-art lane detection approaches, has not been well stud- ied. In this work, we report our progress on conducting the first large-scale empirical study to evaluate the robustness of 4 major types of lane detection methods under 3 types of physical-world adversarial attacks in end-to-end driving scenarios. We find that each lane detection method has different security characteristics, and in particular, some models are highly vulnerable to certain types of attack. Surprisingly, but probably not coincidentally, popular production lane centering systems properly select the lane detection approach which shows higher resistance to such attacks. In the near future, more and more automakers will include autonomous driving features in their products. We hope that our research will help as many automakers as possible to recognize the risks in choosing lane detection algorithms.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129077213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Demo: Dynamic Time Warping as a Tool for Comparing CAN data 演示:动态时间扭曲作为比较CAN数据的工具
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23040
Mars Rayno, J. Daily
{"title":"Demo: Dynamic Time Warping as a Tool for Comparing CAN data","authors":"Mars Rayno, J. Daily","doi":"10.14722/autosec.2022.23040","DOIUrl":"https://doi.org/10.14722/autosec.2022.23040","url":null,"abstract":"—CAN bus traces from repeated dynamic events often do not align. Dynamic Time Warping (DTW) is a tool used to efficiently align traces by time. For this demo, multiple CAN bus traces were taken from the same vehicle performing the same maneuvers. By using DTW, the similarity of the traces was able to be quantified. Specifically, CAN bus traces were compared from a heavy truck performing the same test sequence. DTW distance score showed 661 compared to the direct Euclidean distance score of 24032; this shows that utilizing DTW can accommodate differences in time during comparison of CAN traces. DTW techniques help improve pattern matching for similar driving behaviors.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114520996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
WIP: Interrupt Attack on TEE-protected Robotic Vehicles WIP:对tee保护机器人车辆的中断攻击
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23001
Mulong Luo, G. Suh
{"title":"WIP: Interrupt Attack on TEE-protected Robotic Vehicles","authors":"Mulong Luo, G. Suh","doi":"10.14722/autosec.2022.23001","DOIUrl":"https://doi.org/10.14722/autosec.2022.23001","url":null,"abstract":"—Effective coordination of sensor inputs requires correct timestamping of the sensor data for robotic vehicles. Though the existing trusted execution environment (TEE) can prevent direct changes to timestamp values from a clock or while stored in memory by an adversary, timestamp integrity can still be compromised by an interrupt between sensor and timestamp reads. We analytically and experimentally evaluate how timestamp integrity violations affect localization of robotic vehicles. The results indicate that the interrupt attack can cause significant errors in localization, which threatens vehicle safety, and need to be prevented with additional countermeasures.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132711802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Physical Layer Data Manipulation Attacks on the CAN Bus CAN总线的物理层数据操作攻击
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23047
A. Mohammed, Yanmao Man, Ryan M. Gerdes, Ming Li, Z. Berkay Celik
{"title":"Physical Layer Data Manipulation Attacks on the CAN Bus","authors":"A. Mohammed, Yanmao Man, Ryan M. Gerdes, Ming Li, Z. Berkay Celik","doi":"10.14722/autosec.2022.23047","DOIUrl":"https://doi.org/10.14722/autosec.2022.23047","url":null,"abstract":"—The Controller Area Network (CAN) bus standard is the most common in-vehicle network that provides communication between Electronic Control Units (ECUs). CAN messages lack authentication and data integrity protection mechanisms and hence are vulnerable to attacks, such as impersonation and data injection, at the digital level. The physical layer of the bus allows for a one-way change of a given bit to accommodate prioritization; viz . a recessive bit ( 1 ) may be changed to a dominant one ( 0 ). In this paper, we propose a physical-layer data manipulation attack wherein multiple compromised ECUs collude to cause 0 → 1 (i.e., dominant to recessive) bit-flips, allowing for arbitrary bit-flips in transmitted messages. The attack is carried out by inducing transient voltages in the CAN bus that are heightened due to the parasitic reactance of the bus and non-ideal properties of the line drivers. Simulation results indicate that, with more than eight compromised ECUs, an attacker can induce a sufficient voltage drop to cause dominant bits to be flipped to recessive ones.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"367 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123458084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
GPSKey: GPS based Secret Key Establishment for Intra-Vehicle Environment GPSKey:基于GPS的车载环境密钥建立
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23023
Edwin Yang, Song Fang
{"title":"GPSKey: GPS based Secret Key Establishment for Intra-Vehicle Environment","authors":"Edwin Yang, Song Fang","doi":"10.14722/autosec.2022.23023","DOIUrl":"https://doi.org/10.14722/autosec.2022.23023","url":null,"abstract":"In order to overcome such limitations, context-based pairing schemes, where they extract secret key from common observations (e.g., visual channel [29], ambient audio [9], [14], timing of detected events [11], wireless signal strength [12], [33] and wireless channel interference [19], [22]) without requiring human interactions are proposed. However, these schemes present two shortcomings: (1) The surrounding environment may not consistently provide enough randomness for effective key generations. For example, [11] requires a user to generate additional events to reduce pairing time. (2) Some channels may not available in a normal vehicle. For example, audio signals in a vehicle can be easily interfered with by noises and vibrations.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122618856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Generating 3D Adversarial Point Clouds under the Principle of LiDARs 基于激光雷达原理的三维对抗点云生成
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23026
Bo Yang, Yushi Cheng, Zizhi Jin, Xiaoyu Ji, Wenyuan Xu
{"title":"Generating 3D Adversarial Point Clouds under the Principle of LiDARs","authors":"Bo Yang, Yushi Cheng, Zizhi Jin, Xiaoyu Ji, Wenyuan Xu","doi":"10.14722/autosec.2022.23026","DOIUrl":"https://doi.org/10.14722/autosec.2022.23026","url":null,"abstract":"—Due to the booming of autonomous driving, in which LiDAR plays a critical role in the task of environment perception, its reliability issues have drawn much attention recently. LiDARs usually utilize deep neural models for 3D point cloud perception, which have been demonstrated to be vulnerable to imperceptible adversarial examples. However, prior work usually manipulates point clouds in the digital world without considering the physical working principle of the actual LiDAR. As a result, the generated adversarial point clouds may be realizable and effective in simulation but cannot be perceived by physical LiDARs. In this work, we introduce the physical principle of LiDARs and propose a new method for generating 3D adversarial point clouds in accord with it that can achieve two types of spoofing attacks: object hiding and object creating. We also evaluate the effectiveness of the proposed method with two 3D object detectors on the KITTI vision benchmark.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122648580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Demo: Hijacking Connected Vehicle Alexa Skills 演示:劫持连接车辆Alexa技能
Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security Pub Date : 1900-01-01 DOI: 10.14722/autosec.2022.23041
Wenbo Ding, Long Cheng, Xianghang Mi, Ziming Zhao, Hongxin Hu
{"title":"Demo: Hijacking Connected Vehicle Alexa Skills","authors":"Wenbo Ding, Long Cheng, Xianghang Mi, Ziming Zhao, Hongxin Hu","doi":"10.14722/autosec.2022.23041","DOIUrl":"https://doi.org/10.14722/autosec.2022.23041","url":null,"abstract":"—Current voice assistant platforms allow users to interact with their cars through voice commands. However, this convenience comes with substantial cyber-risk to voice-controlled vehicles. In this demo, we show a “malicious” skill with unwanted control actions on the Alexa system could hijack voice commands that are supposed to be sent to a benign third-party connected vehicle skill.","PeriodicalId":399600,"journal":{"name":"Proceedings Fourth International Workshop on Automotive and Autonomous Vehicle Security","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123562310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
下一页 尾页
0
×
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
请完成安全验证×
相关产品
×
本文献相关产品
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信