We utilize recent advances in machine learning, game theory and control theory to improve the robustness of vehicle platoons with an end-to-end attack detection and mitigation framework.

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Authors

Guoxin Sun

Mr. Guoxin Sun received the B.S. degree in 2017 and the M.E. degree in 2019 from the University of Melbourne. He is currently pursuing the Ph.D. degree with the Electrical and Electronic Engineering Department, the University of Melbourne. His research interests lie in the domain of cyber-physical security, machine learning, game theory and system theory.

Tansu Alpcan

Prof. Tansu Alpcan’s research interests include game, control, and optimisation theories; adversarial and distributed machine learning; networked and distributed system security; applications of machine and deep learning methods to communication, IoT, and Cyber-Physical Systems; smart grid, renewable integration, and electricity markets; wireless, cognitive and software-defined networks.

Benjamin I. P. Rubinstein

Prof. Ben Rubinstein actively research topics in machine learning, security & privacy, databases such as adversarial learning, differential privacy and record linkage. Prior to joining the University of Melbourne in 2013, he enjoyed four years in the research divisions of Microsoft, Google, Intel and Yahoo!

Seyit Camtepe

Dr Seyit Camtepe is a Principal Research Scientist at CSIRO Data61. He received the PhD degree in Computer Science from Rensselaer Polytechnic Institute, New York, USA, in 2007. From 2007 to 2013, he was with the Technische Universitaet Berlin, Germany, as a Senior Researcher and Research Group Leader in Security. From 2013 to 2017, he worked as a Lecturer at the Queensland University of Technology, Australia. His research interests include topics from cyber security and ML, and applied and malicious cryptography.

Cite this work

If you find this work useful, please consider to cite the following reference paper:

@inproceedings{sun2021strategic,
  title={Strategic Mitigation Against Wireless Attacks on Autonomous Platoons},
  author={Sun, Guoxin and Alpcan, Tansu and Rubinstein, Benjamin IP and Camtepe, Seyit},
  booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
  pages={69--84},
  year={2021},
  organization={Springer}
}

Acknowledgments

We gratefully acknowledge support from the DSTG Next Generation Technology Fund and Data61 CSIRO CRP “Adversarial Machine Learning for Cyber”, and a Data61 CSIRO PhD scholarship.