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Address behaviour vulnerabilities in the next generation of autonomous robots

Nature Machine Intelligence volume 3, pages 927–928 (2021)Cite this article

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As service and industrial robots enter our lives, new types of cybersecurity issues emerge that involve the manipulation of a robot’s behaviour. Now is the time to develop countermeasures.

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Fig. 1: Examples of behaviour vulnerabilities exploited by non-expert attackers.

References

  1. Ackerman, E. IEEE Spect. 6, 103 (2019).

    Google Scholar 

  2. Joe, C. et al. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction 211–220 (2020).

  3. Brown, D. S. & Niekum, S. Proceedings of the AAAI Conference on Artificial Intelligence 33, 7749–7758 (2019).

    Article  Google Scholar 

  4. Bogue, R. Ind. Rob. 41, 487–492 (2014).

    Article  Google Scholar 

  5. Luckcuck, M., Farrell, M., Dennis, L. A., Dixon, C. & Fisher, M. ACM Comput. Surv. 52, 1–41 (2019).

    Article  Google Scholar 

  6. Clark, G. W., Doran, M. V. & Andel, T. R. In 2017 IEEE conference on cognitive and computational aspects of situation management 1–5 (2017).

  7. Murino, G., Armando, A. & Tacchella, A. 2019 11th International Conference on Cyber Conflict (CyCon) 900, 1–19 (2019).

    Google Scholar 

  8. Gupta, R. Kurtz, Z. T., Scherer, S. & Smereka, J. M. Preprint at https://arxiv.org/abs/1809.03565 (2018).

  9. Sánchez, C. et al. Form. Methods Syst. Des. 54, 279–335 (2019).

    Article  Google Scholar 

  10. Koller, D. & Friedman, N. (MIT press, 2009).

  11. Pang, G., van den Hengel, A., Shen, C. & Cao, L. In Proceedings of the 27th ACM SIGKDD international conference on knowledge discovery & data mining 1298–1308 (2021).

  12. Ghallab, M., Nau, D. & Traverso, P. Artif. Intell. 208, 1–17 (2014).

    Article  Google Scholar 

  13. Kaelbling, L. P. & Lozano-Pérez, T. Int. J. Rob. Res. 32, 1194–1227 (2013).

    Article  Google Scholar 

Download references

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  1. Istituto Italiano di Tecnologia (IIT), Genova, Italy

    Michele Colledanchise

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  1. Michele Colledanchise
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Correspondence to Michele Colledanchise.

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Colledanchise, M. Address behaviour vulnerabilities in the next generation of autonomous robots. Nat Mach Intell 3, 927–928 (2021). https://doi.org/10.1038/s42256-021-00415-x

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