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Attack-resilient Fusion of Sensor Data with Uncertain Delays

Published:23 August 2022Publication History
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Abstract

Malicious attackers may disrupt the safety of autonomous systems through compromising sensors to feed wrong measurements to the controller. This article proposes attack-resilient sensor fusion that combines local sensor readings and shared sensing information from multiple sources. The method results in higher resilience against sensor attacks through jointly considering sensing noise and uncertain communication delay. To be specific, we first identify the considerable impact of the delay on determining attacked sensors. Second, we present a novel two-dimensional abstract sensor model, where each measurement is augmented as a probabilistic interval based on the convolution of the noise and delay. Third, we propose a fusion algorithm that admits the fused value with highest joint probability distribution of the intervals to tolerate corrupted measurements. Finally, we demonstrate the effectiveness of our method in a vehicle-platoon case study using extensive simulations and testbed experiments.

REFERENCES

  1. [1] Aghili Seyed Farhad, Ashouri-Talouki Maede, and Mala Hamid. 2018. DoS, impersonation and de-synchronization attacks against an ultra-lightweight RFID mutual authentication protocol for IoT. J. Supercomput. 74, 1 (2018), 509525.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. [2] Akowuah Francis and Kong Fanxin. 2021. Physical invariant based attack detection for autonomous vehicles: Survey, vision, and challenges. In Proceedings of the 4th International Conference on Connected and Autonomous Driving (MetroCAD). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  3. [3] Akowuah Francis and Kong Fanxin. 2021. Real-time adaptive sensor attack detection in autonomous cyber-physical systems. In Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium. IEEE, 237250.Google ScholarGoogle ScholarCross RefCross Ref
  4. [4] Akowuah Francis and Kong Fanxin. 2021. Real-time adaptive sensor attack detection in autonomous cyber-physical systems. In Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  5. [5] Akowuah Francis, Prasad Romesh, Espinoza Carlos Omar, and Kong Fanxin. 2021. Recovery-by-learning: Restoring autonomous cyber-physical systems from sensor attacks. In Proceedings of the 27th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications. IEEE, 6166.Google ScholarGoogle ScholarCross RefCross Ref
  6. [6] Alipour-Fanid Amir, Dabaghchian Monireh, Zhang Hengrun, and Zeng Kai. 2017. String stability analysis of cooperative adaptive cruise control under jamming attacks. In Proceedings of the IEEE 18th International Symposium on High Assurance Systems Engineering (HASE). IEEE, 157162.Google ScholarGoogle ScholarCross RefCross Ref
  7. [7] Ashibani Yosef and Mahmoud Qusay H.. 2017. Cyber physical systems security: Analysis, challenges and solutions. Comput. Secur. 68 (2017), 8197.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. [8] Cacace Filippo, Germani Alfredo, and Manes Costanzo. 2016. State estimation and control of nonlinear systems with large and variable measurement delays. In Recent Results on Nonlinear Delay Control Systems. Springer, 95112.Google ScholarGoogle Scholar
  9. [9] Cao Yulong, Xiao Chaowei, Cyr Benjamin, Zhou Yimeng, Park Won, Rampazzi Sara, Chen Qi Alfred, Fu Kevin, and Mao Z. Morley. 2019. Adversarial sensor attack on lidar-based perception in autonomous driving. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security. 22672281.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. [10] Chen Bo, Yu Li, Zhang Wenan, and Liu Andong. 2013. Robust information fusion estimator for multiple delay-tolerant sensors with different failure rates. IEEE Trans. Circ. Syst. I-regul. Pap. 60, 2 (2013), 401414.Google ScholarGoogle ScholarCross RefCross Ref
  11. [11] Chong Michelle S., Wakaiki Masashi, and Hespanha Joao P.. 2015. Observability of linear systems under adversarial attacks. In Proceedings of the American Control Conference (ACC). IEEE, 24392444.Google ScholarGoogle ScholarCross RefCross Ref
  12. [12] Fawzi H., Tabuada P., and Diggavi S.. 2014. Secure estimation and control for cyber-physical systems under adversarial attacks. IEEE Trans. Automat. Control 59, 6 (2014), 14541467.Google ScholarGoogle ScholarCross RefCross Ref
  13. [13] Ferrari P., Flammini A., Sisinni E., Rinaldi S., Brandão D., and Rocha M. S.. 2018. Delay estimation of industrial IoT applications based on messaging protocols. IEEE Trans. Instrum. Meas. 67, 9 (2018), 21882199.Google ScholarGoogle ScholarCross RefCross Ref
  14. [14] Gopalakrishnan Ajit, Kaisare Niket S., and Narasimhan Shankar. 2011. Incorporating delayed and infrequent measurements in extended Kalman filter based nonlinear state estimation. J. Process Contr. 21, 1 (2011), 119129.Google ScholarGoogle ScholarCross RefCross Ref
  15. [15] Guo Xiaolong, Han Song, Hu X. Sharon, Jiao Xun, Jin Yier, Kong Fanxin, and Lemmon Michael. 2021. Towards scalable, secure, and smart mission-critical IoT systems: Review and vision. In Proceedings of the International Conference on Embedded Software. ACM, 110.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. [16] He Ke, He Le, Fan Lisheng, Deng Yansha, Karagiannidis George K., and Nallanathan Arumugam. 2021. Learning-based signal detection for MIMO systems with unknown noise statistics. IEEE Trans. Commun. 69, 5 (2021), 30253038.Google ScholarGoogle ScholarCross RefCross Ref
  17. [17] He Ning, Shi Dawei, and Chen Tongwen. 2018. Self-triggered model predictive control for networked control systems based on first-order hold. Int. J. Robust Nonlin. Contr. 28, 4 (2018), 13031318.Google ScholarGoogle ScholarCross RefCross Ref
  18. [18] He Qing and Liu Jinkun. 2016. Observer-based stabilisation of a class of nonlinear systems in the presence of measurement delay. Int. J. Contr. 89, 6 (2016), 11801190.Google ScholarGoogle ScholarCross RefCross Ref
  19. [19] He Tianjia, Zhang Lin, Kong Fanxin, and Salekin Asif. 2020. Exploring inherent sensor redundancy for automotive anomaly detection. In Proceedings of the 57th Design Automation Conference.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. [20] Hespanha Joo P., Naghshtabrizi Payam, and Xu Yonggang. 2007. A survey of recent results in networked control systems. Proc. IEEE 95, 1 (2007), 138162.Google ScholarGoogle ScholarCross RefCross Ref
  21. [21] Huang Jinquan and Lewis F. L.. 2003. Neural-network predictive control for nonlinear dynamic systems with time-delay. IEEE Trans. Neural Netw. 14, 2 (2003), 377389.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. [22] Huang Yi-Bo, He Yong, An Jianqi, and Wu Min. 2021. Polynomial-type Lyapunov-Krasovskii functional and Jacobi-Bessel inequality: Further results on stability analysis of time-delay systems. IEEE Trans. Automat. Control 66, 6 (2021), 29052912.Google ScholarGoogle ScholarCross RefCross Ref
  23. [23] Ivanov Radoslav, Pajic Miroslav, and Lee Insup. 2016. Attack-resilient sensor fusion for safety-critical cyber-physical systems. ACM Trans. Embed. Comput. Syst. 15, 1 (2016), 21.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. [24] Karafyllis Iasson and Krstic Miroslav. 2011. Nonlinear stabilization under sampled and delayed measurements, and with inputs subject to delay and zero-order hold. IEEE Trans. Automat. Control 57, 5 (2011), 11411154.Google ScholarGoogle ScholarCross RefCross Ref
  25. [25] Khalajmehrabadi Ali, Gatsis Nikolaos, Akopian David, and Taha Ahmad F.. 2018. Real-time rejection and mitigation of time synchronization attacks on the global positioning system. IEEE Trans. Industr. Electron. 65, 8 (2018), 64256435.Google ScholarGoogle ScholarCross RefCross Ref
  26. [26] Khaleghi Bahador, Khamis Alaa, Karray Fakhreddine O., and Razavi Saiedeh N.. 2013. Multisensor data fusion: A review of the state-of-the-art. Inf. Fusion 14, 1 (2013), 2844.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. [27] Kong Fanxin, Sokolsky Oleg, Weimer James, and Lee Insup. 2019. State consistencies for cyber-physical system recovery. In Proceedings of the 2nd Workshop on Cyber-Physical Systems Security and Resilience (CPS-SR). 37.Google ScholarGoogle Scholar
  28. [28] Kong Fanxin, Xu Meng, Weimer James, Sokolsky Oleg, and Lee Insup. 2018. Cyber-physical system checkpointing and recovery. In Proceedings of the ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2231.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. [29] Lahat Dana, Adali Tulay, and Jutten Christian. 2015. Multimodal data fusion: An overview of methods, challenges, and prospects. Proc. IEEE 103, 9 (2015), 14491477.Google ScholarGoogle ScholarCross RefCross Ref
  30. [30] Lai Chienliang and Hsu Paulo. 2010. Design the remote control system with the time-delay estimator and the adaptive smith predictor. IEEE Trans. Industr. Inform. 6, 1 (2010), 7380.Google ScholarGoogle ScholarCross RefCross Ref
  31. [31] Liu Chongyang, Loxton Ryan, Teo Kok Lay, and Wang Song. 2022. Optimal state-delay control in nonlinear dynamic systems. Automatica 135 (2022), 109981.Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. [32] Long Fei, Zhang Chuan-Ke, Jiang Lin, He Yong, and Wu Min. 2019. Stability analysis of systems with time-varying delay via improved Lyapunov–Krasovskii functionals. IEEE Trans. Syst., Man Cyber.: Syst. 51, 4 (2019), 24572466.Google ScholarGoogle ScholarCross RefCross Ref
  33. [33] Lu P., Zhang L., Park B. B., and Feng L.. 2018. Attack-resilient sensor fusion for cooperative adaptive cruise control. In Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC). 39553960.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. [34] Marzullo Keith. 1990. Tolerating failures of continuous-valued sensors. ACM Trans. Comput. Syst. 8, 4 (1990), 284304.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. [35] Mohammad Khader and Agaian Sos. 2009. Efficient FPGA implementation of convolution. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. IEEE, 34783483.Google ScholarGoogle ScholarCross RefCross Ref
  36. [36] Özkan Emre, Šmídl Václav, Saha Saikat, Lundquist Christian, and Gustafsson Fredrik. 2013. Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters. Automatica 49, 6 (2013), 15661575.Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. [37] Pajic Miroslav, Weimer James, Bezzo Nicola, Tabuada Paulo, and Pappas George J.. 2014. Robustness of attack-resilient state estimators. In Proceedings of the ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS).Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. [38] Pasqualetti F., Dörfler F., and Bullo F.. 2013. Attack detection and identification in cyber-physical systems. IEEE Trans. Automat. Control 58, 11 (2013), 27152729.Google ScholarGoogle ScholarCross RefCross Ref
  39. [39] Ray Asok, Liou L. W., and Shen J. H.. 1993. State estimation using randomly delayed measurements. J. Dynam. Syst., Meas. Contr., Trans. ASME 115 (1993), 1926.Google ScholarGoogle ScholarCross RefCross Ref
  40. [40] Sanchez Helem Sabina, Rotondo Damiano, Escobet Teresa, Puig Vicenc, Saludes Jordi, and Quevedo Joseba. 2019. Detection of replay attacks in cyber-physical systems using a frequency-based signature. J. Franklin Instit. 356, 5 (2019), 27982824.Google ScholarGoogle ScholarCross RefCross Ref
  41. [41] Schenato Luca. 2007. Optimal sensor fusion for distributed sensors subject to random delay and packet loss. In Proceedings of the 46th IEEE Conference on Decision and Control. IEEE, 15471552.Google ScholarGoogle ScholarCross RefCross Ref
  42. [42] Shoukry Yasser, Martin Paul, Yona Yair, Diggavi Suhas, and Srivastava Mani. 2015. Pycra: Physical challenge-response authentication for active sensors under spoofing attacks. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. 10041015.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. [43] Siamak Sara, Dehghani Maryam, and Mohammadi Mohsen. 2021. Dynamic GPS spoofing attack detection, localization, and measurement correction exploiting PMU and SCADA. IEEE Syst. J. 15, 2 (2021), 25312540.Google ScholarGoogle ScholarCross RefCross Ref
  44. [44] Smyth Andrew and Wu Meiliang. 2007. Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring. Mechan. Syst. Sig. Process. 21, 2 (2007), 706723.Google ScholarGoogle ScholarCross RefCross Ref
  45. [45] Sun Shuli. 2012. Optimal linear filters for discrete-time systems with randomly delayed and lost measurements with/without time stamps. IEEE Trans. Automat. Control 58, 6 (2012), 15511556.Google ScholarGoogle ScholarCross RefCross Ref
  46. [46] Tan Chang, Ji Sai, Gui Ziyuan, Shen Jian, Fu De-Sheng, and Wang Jin. 2018. An effective data fusion-based routing algorithm with time synchronization support for vehicular wireless sensor networks. Journal Supercomput. 74, 3 (2018), 12671282.Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. [47] Tipsuwan Y. and Chow Moyuen. 2003. Control methodologies in networked control systems. Contr. Eng. Pract. 11, 10 (2003), 10991111.Google ScholarGoogle ScholarCross RefCross Ref
  48. [48] Trimpe S. and D’Andrea R.. 2014. Event-based state estimation with variance-based triggering. IEEE Trans. Automat. Contr. 59, 12 (2014), 32663281.Google ScholarGoogle ScholarCross RefCross Ref
  49. [49] Wan Eric A. and Nelson Alex T.. 2001. Dual extended Kalman filter methods. Kalman Filt. Neural Netw. 123 (2001).Google ScholarGoogle ScholarCross RefCross Ref
  50. [50] Wang Ruixuan, Kong Fanxin, Sudler Hasshi, and Jiao Xun. 2021. Brief industry paper: HDAD: hyperdimensional computing-based anomaly detection for automotive sensor attacks. In Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium. IEEE, 461464.Google ScholarGoogle ScholarCross RefCross Ref
  51. [51] Welch Greg and Bishop Gary. 1995. An Introduction to the Kalman Filter. Technical Report TR 95-041, University of North Carolina, Department of Computer Science, 1995.Google ScholarGoogle Scholar
  52. [52] Wolf Marilyn and Serpanos Dimitrios. 2017. Safety and security in cyber-physical systems and internet-of-things systems. Proc. IEEE 106, 1 (2017), 920.Google ScholarGoogle ScholarCross RefCross Ref
  53. [53] Yao Yuan, Rao Lei, Liu Xue, and Zhou Xingshe. 2013. Delay analysis and study of IEEE 802.11 p based DSRC safety communication in a highway environment. In Proceedings of the IEEE INFOCOM. IEEE, 15911599.Google ScholarGoogle Scholar
  54. [54] Zeng Tengchan, Semiari Omid, Saad Walid, and Bennis Mehdi. 2019. Joint communication and control for wireless autonomous vehicular platoon systems. IEEE Trans. Commun. 67, 11 (2019), 79077922.Google ScholarGoogle ScholarCross RefCross Ref
  55. [55] Zhang Lin, Chen Xin, Kong Fanxin, and Cardenas Alvaro A.. 2020. Real-time recovery for cyber-physical systems using linear approximations. In Proceedings of the 41st IEEE Real-Time Systems Symposium (RTSS). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  56. [56] Zhang Lin, Lu Pengyuan, Kong Fanxin, Chen Xin, Sokolsky Oleg, and Lee Insup. 2021. Real-time attack-recovery for cyber-physical systems using linear-quadratic regulator. ACM Trans. Embed. Comput. Syst. 20, 5s (2021), 79:1–79:24.Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. [57] Zhao Junbo and Mili Lamine. 2017. Robust unscented Kalman filter for power system dynamic state estimation with unknown noise statistics. IEEE Trans. Smart Grid 10, 2 (2017), 12151224.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Transactions on Embedded Computing Systems
      ACM Transactions on Embedded Computing Systems  Volume 21, Issue 4
      July 2022
      330 pages
      ISSN:1539-9087
      EISSN:1558-3465
      DOI:10.1145/3551651
      • Editor:
      • Tulika Mitra
      Issue’s Table of Contents

      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].

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      Publication History

      • Published: 23 August 2022
      • Online AM: 18 April 2022
      • Revised: 1 March 2022
      • Accepted: 1 March 2022
      • Received: 1 September 2021
      Published in tecs Volume 21, Issue 4

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