Data attack detection for an unmanned aerial vehicle control system using innovation sequences
XIAO Jia-ping
JIANG Jian-chun
SHE Chun-dong
Abstract：With rapid advances in the fields of the Internet of things and autonomous systems,the network security of cyber-physical systems has attracted considerable attention.An unmanned aerial vehicle(UAV)is an intelligent device that relies on information communication and flight control systems to achieve autonomous flight.Consequently,its security is extremely important.This study proposes a new state estimation method that uses innovation sequences based on an extended Kalman filter for the detection of data attacks on a UAV.Our method can identify data attacks on tensors and control commands.First,a cyber-physical system model for a UAV is established,and the state estimation algorithm and data attack model are introduced.Then,a scalar detection statistic is constructed for data attack detection using innovation sequences,and the minus infinity norm method is introduced to reduce the false detection of data attacks while the aircraft is being maneuvered.Finally,simulation results show that the proposed detection method can effectively detect various threat patterns under a variety of circumstances for unmanned control systems.
Keywords：unmanned aerial vehiclecyber-physical systemintrusion detectionnetwork security
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 1575-1582 )