skip to main content
10.1145/3375706.3380552acmconferencesArticle/Chapter ViewAbstractPublication PagescodaspyConference Proceedingsconference-collections
research-article

CVShield: Guarding Sensor Data in Connected Vehicle with Trusted Execution Environment

Published: 16 March 2020 Publication History

Abstract

The emerging Connected Vehicle (CV) technology enables vehicles to wirelessly exchange safety and mobility information (e.g., location and speed) with traffic infrastructure and other vehicles. Existing CV applications heavily rely on sensor inputs (e.g., GPS). However, previous work has shown that the attacker can cause severe congestion or increased safety risks by compromising vehicles and broadcasting falsified sensor data. Thus, it is highly desirable to ensure the integrity of sensor data. In this paper, to prevent compromised vehicles from sending falsified sensor data, we propose a system CVShield, which utilizes the recent advances in hardware-assisted security (e.g., ARM TrustZone). CVShield can ensure the integrity of the sensor data from their reading to their transmission at the vehicle side. In general, we relocate all codes that are related to sensor data reading, processing, encapsulation, and transmission from the rich execution environment (REE) into the trusted execution environment (TEE). However, manually extracting code sections is laborious and error-prone. Also, we should minimize the size of the trusted computing base (TCB) in TEE to reduce the attack surface. To achieve these goals, we propose to leverage program slicing to automatically extract code sections and eliminating irrelevant codes in large codebases. Our initial results demonstrate that CVShield can support GPS data reading, and our optimization can eliminate the time overhead introduced by context switches of TrustZone.

References

[1]
ARM Ltd. 2019 a. Address Space Controllers -- Arm . https://tinyurl.com/uxjdnfz .
[2]
ARM Ltd. 2019 b. SMC Calling Convention - ARM Infocenter . https://tinyurl.com/y6gkrpo3 .
[3]
ARM Ltd. 2019 c. TrustZone -- Arm Developer . https://tinyurl.com/vj29ybd .
[4]
Boundary Devices. 2019 a. boundarydevices/linux-imx6 . https://tinyurl.com/w66kfkj .
[5]
Boundary Devices. 2019 b. i.MX6 ARM Development Board . https://boundarydevices.com/product/bd-sl-i-mx6/.
[6]
Stephen Checkoway, Damon McCoy, Brian Kantor, Danny Anderson, Hovav Shacham, Stefan Savage, Karl Koscher, Alexei Czeskis, Franziska Roesner, and Tadayoshi Kohno. 2011. Comprehensive Experimental Analyses of Automotive Attack Surfaces. In Proc. USENIX Security .
[7]
Qi Alfred Chen, Yucheng Yin, Yiheng Feng, Z. Morley Mao, and Henry X. Liu. 2018. Exposing Congestion Attack on Emerging Connected Vehicle based Traffic Signal Control. In Proc. NDSS.
[8]
Cohda Wireless. 2019. Cohda MK5 OBU. https://tinyurl.com/y6qepj6h .
[9]
Cross-Cutting Technical Committee. 2016. Dedicated Short Range Communications (DSRC) Message Set Dictionary? Set. SAE International (Mar. 2016).
[10]
GlobalPlatform. 2019. GlobalPlatform Homepage - GlobalPlatform . https://globalplatform.org/.
[11]
GPSD project. 2019. biiont/gpsd . https://github.com/biiont/gpsd .
[12]
John Harding, Gregory Powell, Rebecca Yoon, Joshua Fikentscher, Charlene Doyle, Dana Sade, Mike Lukuc, Jim Simons, Jing Wang, et almbox. 2014. Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application. Technical Report. https://tinyurl.com/yc579x68
[13]
IEEE 1609 Working Group. 2019. IEEE Guide for Wireless Access in Vehicular Environments (WAVE) Architecture. IEEE Std 1609.0--2019 (Revision of IEEE Std 1609.0--2013) (2019).
[14]
Karl Koscher, Alexei Czeskis, Franziska Roesner, Shwetak Patel, Tadayoshi Kohno, Stephen Checkoway, Damon McCoy, Brian Kantor, Danny Anderson, Hovav Shacham, and Stefan Savage. 2010. Experimental Security Analysis of a Modern Automobile. In Proc. IEEE S&P.
[15]
Linaro Ltd. 2019 a. OP-TEE/optee_os . https://tinyurl.com/rurhgcl .
[16]
Linaro Ltd. 2019 b. Open Portable Trusted Execution Environment - OP-TEE . https://www.op-tee.org/.
[17]
He Liu, Stefan Saroiu, Alec Wolman, and Himanshu Raj. 2012. Software abstractions for trusted sensors. In Proc. MobiSys.
[18]
Sahar Mazloom, Mohammad Rezaeirad, Aaron Hunter, and Damon McCoy. 2016. A Security Analysis of an In-Vehicle Infotainment and App Platform. In USENIX WOOT.
[19]
U.S. Department of Transportation (US DOT). 2019. Intelligent Transportation Systems - Connected Vehicle Basics . https://tinyurl.com/yxjj98vr .
[20]
Mark Weiser. 1981. Program slicing. In Proc. ICSE.
[21]
Kexiong (Curtis) Zeng, Shinan Liu, Yuanchao Shu, Dong Wang, Haoyu Li, Yanzhi Dou, Gang Wang, and Yaling Yang. 2018. All Your GPS Are Belong To Us: Towards Stealthy Manipulation of Road Navigation Systems. In Proc. USENIX Security .

Cited By

View all
  • (2024)Boosting Collaborative Vehicular Perception on the Edge with Vehicle-to-Vehicle CommunicationProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699328(141-154)Online publication date: 4-Nov-2024
  • (2024)Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle NetworksIEEE Open Journal of Vehicular Technology10.1109/OJVT.2024.34222535(869-906)Online publication date: 2024
  • (2024)In-Vehicle Digital Forensics for Connected and Automated Vehicles With Public AuditingIEEE Internet of Things Journal10.1109/JIOT.2023.331057811:4(6368-6383)Online publication date: 15-Feb-2024
  • Show More Cited By

Index Terms

  1. CVShield: Guarding Sensor Data in Connected Vehicle with Trusted Execution Environment

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        cover image ACM Conferences
        AutoSec '20: Proceedings of the Second ACM Workshop on Automotive and Aerial Vehicle Security
        March 2020
        84 pages
        ISBN:9781450371131
        DOI:10.1145/3375706
        • Program Chairs:
        • Qi Alfred Chen,
        • Ziming Zhao,
        • Gail-Joon Ahn
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Sponsors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 16 March 2020

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. connected vehicle
        2. sensor
        3. spoofing
        4. tee
        5. trustzone

        Qualifiers

        • Research-article

        Funding Sources

        • Mcity University of Michigan

        Conference

        CODASPY '20
        Sponsor:

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • Downloads (Last 12 months)60
        • Downloads (Last 6 weeks)3
        Reflects downloads up to 13 Feb 2025

        Other Metrics

        Citations

        Cited By

        View all
        • (2024)Boosting Collaborative Vehicular Perception on the Edge with Vehicle-to-Vehicle CommunicationProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699328(141-154)Online publication date: 4-Nov-2024
        • (2024)Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle NetworksIEEE Open Journal of Vehicular Technology10.1109/OJVT.2024.34222535(869-906)Online publication date: 2024
        • (2024)In-Vehicle Digital Forensics for Connected and Automated Vehicles With Public AuditingIEEE Internet of Things Journal10.1109/JIOT.2023.331057811:4(6368-6383)Online publication date: 15-Feb-2024
        • (2023)In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approachesPeerJ Computer Science10.7717/peerj-cs.16489(e1648)Online publication date: 26-Oct-2023
        • (2023)TZEAMMSecurity and Communication Networks10.1155/2023/69219602023Online publication date: 31-Jan-2023
        • (2023)SoK: A Systematic Review of TEE Usage for Developing Trusted ApplicationsProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3600169(1-15)Online publication date: 29-Aug-2023
        • (2023)Trustworthy Execution in Untrustworthy Autonomous Systems2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom60117.2023.00240(1766-1773)Online publication date: 1-Nov-2023
        • (2023)A Comprehensive Survey of V2X Cybersecurity Mechanisms and Future Research PathsIEEE Open Journal of the Communications Society10.1109/OJCOMS.2023.32391154(325-391)Online publication date: 2023
        • (2023)Context Sensitive Dynamic Slicing of Multi-Agent System2023 IEEE 20th India Council International Conference (INDICON)10.1109/INDICON59947.2023.10440680(1330-1335)Online publication date: 14-Dec-2023
        • (2022)Demystifying In-Vehicle Intrusion Detection Systems: A Survey of Surveys and a Meta-TaxonomyElectronics10.3390/electronics1107107211:7(1072)Online publication date: 29-Mar-2022
        • Show More Cited By

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        Figures

        Tables

        Media

        Share

        Share

        Share this Publication link

        Share on social media