Muniraj, Devaprakash (Virginia Polytechnic Institute and State University), Farhood, Mazen (Virginia Tech)

A Framework for Detection of Sensor Attacks on Small Unmanned Aircraft Systems

Scheduled for presentation during the "UAS Applications - VI" (ThC4), Thursday, June 15, 2017, 15:40−16:00, Lummus Island

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 24, 2024

Abstract

The work presented in this paper is part of an overall effort to design a secure autopilot, resilient against malicious attacks on both the cyber and physical layers, for a small unmanned aircraft system (UAS). This paper specifically deals with identification of malicious attacks on the sensors of a small UAS. A framework is presented wherein techniques from statistical analysis are used in a probabilistic setting to detect sensor attacks. The paper describes in detail the design of anomaly detectors and the Bayesian network. A case study involving detection of a spoofing attack on the GPS is used throughout the paper to illustrate the proposed approach. The anomaly detectors are designed based on a simulation dataset, and are re-tuned based on flight tests conducted on a small fixed-wing UAS platform. The performances of the detectors are studied under different external disturbances and conclusions are drawn.