Imaging vehicle-to-vehicle communication using visible light

Abstract With advances in automated and connected driving, secure communication is increasingly becoming a safety-critical function. Injection of manipulated radio messages into traffic can cause severe accidents in the foreseeable future, and can currently be achieved without having to manipulate on-board vehicle systems directly, for example by hijacking cellphones instead and using these as senders. Thereby, large-scale attacks on vehicles can be executed remotely, and target relatively vulnerable devices. To mitigate remaining vulnerabilities in current automotive security architectures, this paper proposes a secondary communication channel using vehicle head and taillights. In contrast to existing approaches, this method allows both to achieve a sufficient data rate and to extract the angular position of the sender, by means of an imaging process which only requires close-to-market, cost-efficient technology. Through this, injecting false messages by masquerading as a different sender is considerably more challenging: The receiver can verify a message’s source position with the supposed position of the sender, e.g. by using on-board sensors or communicated information. Thereby, reliably faking both the communicated messages and the position of the sender will require direct manipulation of on-board vehicle systems, raising the security level of the function accordingly, and precluding low-threshold, wide-range attacks.

[1]  Recommended Practices of Modulating Current in High Brightness LEDs for Mitigating Health Risks to Viewers , 2008 .

[2]  Jin Young Kim,et al.  Indoor Positioning System using LED Lights and a Dual Image Sensor , 2015 .

[3]  Chi-Wai Chow,et al.  Visible light communication using mobile-phone camera with data rate higher than frame rate. , 2015, Optics express.

[4]  Frédo Durand,et al.  The visual microphone , 2014, ACM Trans. Graph..

[5]  J. R. Ziehn A Non-Invasive Cyberrisk in Cooperative Driving , 2017 .

[6]  Shoji Kawahito,et al.  LED and CMOS Image Sensor Based Optical Wireless Communication System for Automotive Applications , 2013, IEEE Photonics Journal.

[7]  M. Wieser,et al.  Life cycle management for cooperative groups of cognitive automobiles in a distributed environment , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[8]  Sascha Wirges,et al.  Making Bertha Cooperate–Team AnnieWAY’s Entry to the 2016 Grand Cooperative Driving Challenge , 2018, IEEE Transactions on Intelligent Transportation Systems.

[9]  S. Haruyama,et al.  High-accuracy positioning system using visible LED lights and image sensor , 2008, 2008 IEEE Radio and Wireless Symposium.

[10]  Ralf Kohlhaas,et al.  Towards Large Scale Urban Traffic Reference Data: Smart Infrastructure in the Test Area Autonomous Driving Baden-Württemberg , 2018, IAS.

[11]  Shoji Kawahito,et al.  A New Automotive VLC System Using Optical Communication Image Sensor , 2016, IEEE Photonics Journal.

[12]  Harald Haas,et al.  Using a CMOS camera sensor for visible light communication , 2012, 2012 IEEE Globecom Workshops.

[13]  Mihai Dimian,et al.  Miller code usage in Visible Light Communications under the PHY I layer of the IEEE 802.15.7 standard , 2014, 2014 10th International Conference on Communications (COMM).

[14]  Takaya Yamazato,et al.  V2X communications with an image sensor , 2017, Journal of Communications and Information Networks.

[15]  Michael Felsberg,et al.  Rolling shutter bundle adjustment , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Latif Ullah Khan,et al.  Visible light communication: Applications, architecture, standardization and research challenges , 2017, Digit. Commun. Networks.

[17]  Alexander Pretschner,et al.  Enhancement of Automotive Penetration Testing with Threat Analyses Results , 2018 .

[18]  Steven E. Shladover,et al.  Potential Cyberattacks on Automated Vehicles , 2015, IEEE Transactions on Intelligent Transportation Systems.

[19]  Eray Yağdereli,et al.  A study on cyber-security of autonomous and unmanned vehicles , 2015 .

[20]  Fuqiang Liu,et al.  Vehicular Visible Light Communications with LED Taillight and Rolling Shutter Camera , 2014, 2014 IEEE 79th Vehicular Technology Conference (VTC Spring).

[21]  Myungsik Yoo,et al.  Analysis on visible light communication using rolling shutter CMOS sensor , 2015, 2015 International Conference on Information and Communication Technology Convergence (ICTC).

[22]  Elmar Schoch,et al.  A Generic Public Key Infrastructure for Securing Car-to-X Communication , 2011 .

[23]  Christof Paar,et al.  Embedded Cryptography: Side Channel Attacks , 2006 .

[24]  André Weimerskirch,et al.  An Overview of Automotive Cybersecurity: Challenges and Solution Approaches , 2015, TrustED@CCS.

[25]  Kym Watson,et al.  Recognition of dangerous situations within a cooperative group of vehicles , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[26]  Richard Szeliski,et al.  Removing rolling shutter wobble , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[27]  William Whyte,et al.  A security credential management system for V2V communications , 2013, 2013 IEEE Vehicular Networking Conference.

[28]  Jürgen Beyerer,et al.  Collision Avoidance by Cooperative Driving Maneuvers , 2011 .

[29]  Junyi Li,et al.  Visible light communication: opportunities, challenges and the path to market , 2013, IEEE Communications Magazine.