Publication Details

Ashutosh Singandhupe, Hung La, David Feil-Seifer, Pei Huang, Linke Guo, and Ming Li. "Securing a UAV Using Individual Characteristics From an EEG Signal." In Proceedings of the IEEE Systems, Man, and Cybernetics Conference, page 2748-2753, Banff, Alberta, Oct 2017. preprint, \url{https://arxiv.org/abs/1704.04574}. doi: 10.1109/SMC.2017.8123042 ( pdf )


  • Keywords:
  • HRI
  • UAV
  • safety
  • networks
  • EEG

Abstract

Unmanned aerial vehicles (UAVs) have gained much attention in recent years for both commercial and military applications. The progress in this field has gained much popularity and the research has encompassed various fields of scientific domain. Cyber securing a UAV communication has been one of the active research field since the attack on Predator UAV video stream hijacking in 2009. Since UAVs rely heavily on on-board autopilot to function, it is important to develop an autopilot system that is robust to possible cyber attacks. In this work, we present a biometric system to encrypt the UAV communication by generating a key which is derived from Beta component of the EEG signal of a user. We have developed a safety mechanism that would be activated in case the communication of the UAV from the ground control station gets attacked. This system has been validated on a commercial UAV under malicious attack conditions during which we implement a procedure where the UAV return safely to a "home" position.

Author Details

Name: Ashutosh Singandhupe
Status: Active

Name: Hung La
Status: Active

Name: David Feil-Seifer
email: dave@cse.unr.edu
Website: http://cse.unr.edu/~dave
Phone: (775) 784-6469
Status: Active

Name: Pei Huang
Status: Inactive

Name: Linke Guo
Status: Inactive

Name: Ming Li
Status: Inactive

BibTex Reference

@inproceedings{singandhupe2017securing,
  title={Securing a UAV Using Individual Characteristics From an EEG Signal},
  author={Ashutosh Singandhupe and Hung La and David Feil-Seifer and Pei Huang and Linke Guo and Ming Li},
  year={2017},
  month={October},
  pages={2748-2753},
  address={Banff, Alberta},
  publisher={preprint, \url{https://arxiv.org/abs/1704.04574}},
  doi={10.1109/SMC.2017.8123042},
  isbn={978-1-5386-1644-4},
  booktitle={Proceedings of the IEEE Systems, Man, and Cybernetics Conference},
}

HTML Reference

<span class="authors">Ashutosh Singandhupe, Hung La, David Feil-Seifer, Pei Huang, Linke Guo, and Ming Li</span>. <span class="title">"Securing a UAV Using Individual Characteristics From an EEG Signal." </span> In <span class="booktitle">Proceedings of the IEEE Systems, Man, and Cybernetics Conference</span>, <span class="page">page 2748-2753</span>, <span class="address">Banff, Alberta</span>, <span class="month">Oct</span> <span class="year">2017</span>. <span class="ending">preprint, \url{https://arxiv.org/abs/1704.04574}.</span> <span class="doi">doi: 10.1109/SMC.2017.8123042</span>

Support

CHS: Small: Collaborative Research: Spatio-Temporal Situational Awareness in Large-Scale Disasters Using Low-Cost Unmanned Aerial Vehicles, National Science Foundation PI: David Feil-Seifer, Amount: $166,666, Jan. 1, 2016 - Dec. 31, 2017

UGV-UAV Hybrid System for Unstructured Environment Exploration, NASA PI: Hung La, co-PI: David Feil-Seifer, Paul Oh, Amount: 83,523, Sept. 1, 2016 - Aug. 31, 2017

UAV-Based Camera Vibration Reduction for Detect and Avoid Tasks, NASA EPSCoR PI: David Feil-Seifer, co-PI: Richard Kelley, Amount: $36,512, Nov. 18, 2015 - Aug. 31, 2016

Improving UAV Vehicle Safety: Algorithms for Computer Vision Based Detect and Avoid and Failure-Resistant Control, Nevada System of Higher Education PI: David Feil-Seifer, co-PI: Kostas Alexis, Amount: $280,000, June 1, 2015 - June 30, 2016