Skip to main content
SpringerLink
Log in

Map-Based Localization Under Adversarial Attacks

  • Conference paper
  • First Online:
Robotics Research

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 10))

Abstract

Due to increasing proliferation of autonomous vehicles, securing robot navigation against malicious attacks becomes a matter of urgent societal interest, because attackers can fool these vehicles by manipulating their sensors, exposing us to unprecedented vulnerabilities and ever-increasing possibilities for malicious attacks. To address this issue, we analyze in-depth the Maximum Correntropy Criterion Extended Kalman Filter (MCC-EKF) and propose a weighted MCC-EKF (WMCC-EKF) algorithm by systematically, rather than in an ad-hoc way, inflating the noise covariance of the compromised measurements based on each measurement’s quality. As a conservative alternative, we also design a secure estimator by first detecting attacks based on \(\ell _0 (\ell _1)\)-optimization assuming that only a small number of measurements can be attacked, and then employ a sliding-window Kalman filter to update the state estimates and covariance using only the uncompromised measurements—the resulting algorithm is termed Secure Estimation-EKF (SE-EKF). Both Monte-Carlo simulations and experiments are performed to validate the proposed secure estimators for map-based localization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Harris, M.: Researcher hacks self-driving car sensors. IEEE Spectrum (2015)

    Google Scholar 

  2. Charette, R.N.: Commercial drones and GPS spoofers a bad mix. IEEE Spectrum (2012)

    Google Scholar 

  3. Pasqualetti, F., Dörfler, F., Bullo, F.: Attack detection and identification in cyber-physical systems. IEEE Trans. Autom. Control. 58(11), 2715–2729 (2013)

    Article  MathSciNet  Google Scholar 

  4. Fawzi, H., Tabuada, P., Diggavi, S.: Secure estimation and control for cyber-physical systems under adversarial attacks. IEEE Trans. Autom. Control. 59, 1454–1467 (2014)

    Article  MathSciNet  Google Scholar 

  5. Mo, Y., Sinopoli, B.: Secure estimation in the presence of integrity attacks. IEEE Trans. Autom. Control. 60(4), 1145–1151 (2015)

    Article  MathSciNet  Google Scholar 

  6. Pajic, M., Weimer, J., Bezzo, N., Tabuada, P., Sokolsky, O., Lee, I., Pappas, G.: Robustness of attack-resilient state estimators. In: Proceedings of the ACM/IEEE Conference on Cyber-Physical Systems, pp. 163–174 (2014)

    Google Scholar 

  7. Shoukry, Y., Puggelli, A., Nuzzo, P., Sangiovanni-Vincentelli, A.L., Seshia, S.A., Tabuada, P.: Sound and complete state estimation for linear dynamical systems under sensor attacks using satisfiability modulo theory solving. In: American Control Conference, pp. 3818–3823. IEEE (2015)

    Google Scholar 

  8. Mo, Y., Murray, R.M.: Multi-dimensional state estimation in adversarial environment. In: Proceedings of the Chinese Control Conference, Hangzhou, China, pp. 28–30 (2015)

    Google Scholar 

  9. Langner, R.: Stuxnet: dissecting a cyberwarfare weapon. IEEE Secur. Priv. 9, 49–51 (2011)

    Article  Google Scholar 

  10. Liu, Y., Ning, P., Reiter, M.K.: False data injection attacks against state estimation in electric power grids. ACM Trans. Inf. Syst. Secur. 14, 1–33 (2011)

    Article  Google Scholar 

  11. Rutkin, A.H.: Spoofers use fake GPS signals to knock a yacht off course, Aug 2013. http://www.udel.edu/003938

  12. Pajic, M., Tabuada, P., Lee, I., Pappas, G.J.: Attack-resilient state estimation in the presence of noise. In: Conference on Decision and Control, pp. 5827–5832. IEEE (2015)

    Google Scholar 

  13. Pajic, M., Lee, I., Pappas, G.J.: Attack-resilient state estimation for noisy dynamical systems. IEEE Trans. Control. Netw. Syst. 4(1), 82–92 (2017)

    Article  MathSciNet  Google Scholar 

  14. Chong, M.S., Wakaiki, M., Hespanha, J.P.: Observability of linear systems under adversarial attacks. In: American Control Conference, pp. 2439–2444. IEEE (2015)

    Google Scholar 

  15. Bezzo, N., Weimer, J., Pajic, M., Sokolsky, O., Pappas, G.J., Lee, I.: Attack resilient state estimation for autonomous robotic systems. In: Proceedings of IEEE Conference on Intelligent Robots and Systems, pp. 3692–3698. IEEE (2014)

    Google Scholar 

  16. Hu, Q., Chang, Y.H., Tomlin, C.J.: Secure estimation for unmanned aerial vehicles against adversarial cyber attacks (2016). arXiv:1606.04176

  17. Candes, E.J., Tao, T.: Decoding by linear programming. IEEE Trans. Inf. Theory 51(12), 4203–4215 (2005)

    Article  MathSciNet  Google Scholar 

  18. Shoukry, Y., Nuzzo, P., Bezzo, N., Sangiovanni-Vincentelli, A., Seshia, S.A., Tabuada, P.: Attack detection and state reconstruction in differentially flat systems under sensor attacks using satisfiability modulo theory solving. In: Conference on Decision and Control, Osaka, Japan, pp. 15–18 (2015)

    Google Scholar 

  19. Izanloo, R., Fakoorian, S.A., Yazdi, H.S., Simon, D.: Kalman filtering based on the maximum correntropy criterion in the presence of non-gaussian noise. In: Conference on Information Science and Systems (CISS), pp. 500–505 (2016)

    Google Scholar 

  20. Liu, X., Qu, H., Zhao, J., Chen, B.: Extended kalman filter under maximum correntropy criterion. In: International Joint Conference on Neural Networks, pp. 1733–1737 (2016)

    Google Scholar 

  21. Yang, Y., Huang, G.: Map-based localization under adversarial attacks,” Tech. Rep. 2017-003, University of Delaware, Department of Mechanical Engineering, Oct 2017. Link: udel.edu/\(\sim \)ghuang/papers/tr\({}\_\)secure.pdf

    Google Scholar 

  22. Kulikova, M.: Square-root algorithms for maximum correntropy estimation of linear discrete-time systems in presence of non-gaussian noise (2016). arXiv:1610.00257

  23. Chang, Y.H., Hu, Q., Tomlin, C.J.: Secure estimation based kalman filter for cyber-physical systems against adversarial attacks. arXiv:1512.03853

  24. Roumeliotis, S.I., Burdick, J.W.: Stochastic cloning: a generalized framework for processing relative state measurements. In: Proceedings of IEEE Conference on Robotics and Automation, Washington, DC, pp. 1788–1795, May 11–15 2002

    Google Scholar 

  25. Kim, S.J., Koh, K., Lustig, M., Boyd, S., Gorinevsky, D.: An interior-point method for large-scale \(l_1\)-regularized least squares. IEEE J. Sel. Top. Signal Process. 1, 606–617 (2007)

    Article  Google Scholar 

  26. Bar-Shalom, Y., Li, X.R., Kirubarajan, T.: Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software. Wiley (2004)

    Google Scholar 

  27. Guivant, J.E., Nebot, E.M.: Optimization of the simultaneous localization and map building algorithm for real time implementation. IEEE Trans. Robot. Autom. 17, 242–257 (2001)

    Article  Google Scholar 

  28. Dellaert, F.: Factor graphs and gtsam: a hands-on introduction. Technical report (2012)

    Google Scholar 

Download references

Acknowledgements

This work was partially supported by the University of Delaware College of Engineering, UD Cybersecurity Initiative, the Delaware NASA/EPSCoR Seed Grant, the NSF (IIS-1566129), and the DTRA (HDTRA1-16-1-0039).

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Delaware, Newark, DE, 19716, USA

    Yulin Yang & Guoquan Huang

Authors
  1. Yulin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoquan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yulin Yang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Nancy M. Amato

  2. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Greg Hager

  3. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

    Shawna Thomas

  4. Department of Electrical Engineering, Pontificia Universidad CatĂłlica de Chile, Santiago, Chile

    Miguel Torres-Torriti

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yang, Y., Huang, G. (2020). Map-Based Localization Under Adversarial Attacks. In: Amato, N., Hager, G., Thomas, S., Torres-Torriti, M. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-28619-4_54

Download citation

Publish with us

Policies and ethics

Search

Navigation