Cyber-Attack Detection for Autonomous Driving Using Vehicle Dynamic State Estimation

Dong Zhang1, Chen Lv1, Tianci Yang1, Peng Hang1
1School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore

Tóm tắt

Từ khóa


Tài liệu tham khảo

Lv, C., Cao, D., Zhao, Y., Auger, D.J., Sullman, M., Wang, H., Dutka, L.M., Skrypchuk, L., Mouzakitis, A.: Analysis of autopilot disengagements occurring during autonomous vehicle testing. IEEE CAA J. Autom. Sin. 5(1), 58–68 (2018)

Cao, Y., Xiao, C., Cyr, B., Zhou, Y., Park, W., Rampazzi, S., Chen, Q.A., Fu, K., Mao, Z.M.: Adversarial sensor attack on lidar-based perception in autonomous driving. In: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, London, pp. 2267–2281

Lv, C., Xing, Y., Zhang, J., Na, X., Li, Y., Liu, T., Cao, D., Wang, F.Y.: Levenberg–Marquardt backpropagation training of multilayer neural networks for state estimation of a safety-critical cyber-physical system. IEEE Trans. Ind. Inf. 14(8), 3436–3446 (2017)

Liu, Q., Mo, Y., Mo, X., Lv, C., Mihankhah, E., Wang, D.: Secure pose estimation for autonomous vehicles under cyber attacks. In: 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, 10–12 June 2019, pp. 1583–1588

Yang, T., Murguia, C., Kuijper, M., Nešić, D.: A robust circle-criterion observer-based estimator for discrete-time nonlinear systems in the presence of sensor attacks. In: 2018 IEEE Conference on Decision and Control (CDC), Florida, 17–19 Dec 2018, pp. 571–576

Humphreys, T.E., Ledvina, B.M., Psiaki, M.L., O'Hanlon, B.W., Kintner, P.M.: Assessing the spoofing threat: development of a portable GPS civilian spoofer. In: Radionavigation laboratory conference proceedings, 2008

Porter, M., Hespanhol, P., Aswani, A., Johnson-Roberson, M., Vasudevan, R.: Detecting generalized replay attacks via time-varying dynamic watermarking. IEEE Trans. Autom. Control (2020). arXiv:1909.08111

Cui, L., Hu, J., Park, B.B., Bujanovic, P.: Development of a simulation platform for safety impact analysis considering vehicle dynamics, sensor errors, and communication latencies: assessing cooperative adaptive cruise control under cyber attack. Transp. Res. Part C Emerg. Technol. 97, 1–22 (2018)

Khan, S.K., Shiwakoti, N., Stasinopoulos, P., Chen, Y.: Cyber-attacks in the next-generation cars, mitigation techniques, anticipated readiness and future directions. Accid. Anal. Prev. 148, 105837 (2020)

Case, D.U.: Analysis of the cyber attack on the Ukrainian power grid. Electr. Inf. Shar. Anal. Center 18, 388 (2016)

Weerakkody, S., Sinopoli, B., Kar, S., Datta, A.: Information flow for security in control systems. In: 2016 IEEE 55th Conference on Decision and Control (CDC), Las Vegas, 12–14 Dec 2016, pp. 5065–5072

Weerakkody, S., Ozel, O., Griffioen, P., Sinopoli, B.: Active detection for exposing intelligent attacks in control systems. In: 2017 IEEE Conference on Control Technology and Applications (CCTA), Kohala Coast, 27–30 Aug 2017, pp.1306–1312

Porter, M., Joshi, A., Hespanho, P., Aswani, A., Johnson-Roberson M., Vasudevan R.: Simulation and real-world evaluation of attack detection schemes. In: 2019 American Control Conference (ACC), Philadelphia, 10–12 Jul. 2019, pp. 551–558

Li, Q., Li, R., Ji, K., Dai, W.: Kalman filter and its application. In: 2015 8th International Conference on Intelligent Networks and Intelligent Systems (ICINIS) , Tianjin, 1 Nov 2015, pp. 74–77

Auger, F., Hilairet, M., Guerrero, J.M., Monmasson, E., Orlowska-Kowalska, T., Katsura, S.: Industrial applications of the Kalman filter: a review. IEEE Trans. Ind. Electron. 60(12), 5458–5471 (2013)

Antonov, S., Fehn, A., Kugi, A.: Unscented Kalman filter for vehicle state estimation. Veh. Syst. Dyn. 49(9), 1497–1520 (2011)

Guo, H., Cao, D., Chen, H., et al.: Vehicle dynamic state estimation: state of the art schemes and perspectives. IEEE CAA J. Autom. Sin. 5(2), 418–431 (2018)

Lv, C., Liu, Y., Hu, X., Guo, H., Cao, D., Wang, F.Y.: Simultaneous observation of hybrid states for cyber-physical systems: a case study of electric vehicle powertrain. IEEE Trans. Cybern. 48(8), 2357–2367 (2018)

Reina, G., Messina, A.: Vehicle dynamics estimation via augmented Extended Kalman Filtering. Measurement 133, 383–395 (2019)

Huang, Z., et al.: Multi-modal sensor fusion-based deep neural network for end-to-end autonomous driving with scene understanding. IEEE Sens. J. 21(10), 11781–11790 (2020)

Wischnewski, A., Stahl, T., Betz, J., Lohmann, B.: Vehicle dynamics state estimation and localization for high performance race cars. IFAC-PapersOnLine. 52(8), 154–161 (2019)

Ok, M., Ok, S., Park, J.H.: Estimation of vehicle attitude, acceleration and angular velocity using convolutional neural network and dual extended Kalman Filter. Sensors 21(4), 1282 (2021)

Zhang, Y., Leng, B., Xiong, L., Yu, Z., Zeng, D.: Distributed drive electric vehicle longitudinal velocity estimation with adaptive Kalman Filter: theory and experiment (No. 2019-01-0439). SAE Technical Paper (2019)

Hubert, M., Vandervieren, E.: An adjusted boxplot for skewed distributions. Comput. Stat. Data Anal. 52(12), 5186–5201 (2008)

Mousavinejad, E., Yang, F., Han, Q.L., Vlacic, L.: A novel cyber attack detection method in networked control systems. IEEE Trans. Cybern. 48(11), 3254–3264 (2018)