Reliable Security Algorithm for Drones Using Individual Characteristics From an EEG Signal
Open Access
- 17 April 2018
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. 6, 22976-22986
- https://doi.org/10.1109/access.2018.2827362
Abstract
Unmanned aerial vehicles (UAVs) have been applied for both civilian and military applications; scientific research involving UAVs has encompassed a wide range of scientific study. However, communication with unmanned vehicles are subject to attack and compromise. Such attacks have been reported as early as 2009, when a Predator UAV’s video stream was compromised. Since UAVs extensively utilize autonomous behavior, it is important to develop an autopilot system that is robust to potential cyber-attack. In this work, we present a biometric system to encrypt communication between a UAV and a computerized base station. This is accomplished by generating a key derived from a user’s EEG Beta component.We first extract coefficients from Beta data using Legendre’s polynomials.We perform encoding of the coefficients using BCH encoding and then generate a key from a hash function. The key is used to encrypt the communication between XBees. Also we have introduced scenarios where the communication is attacked. When communication with a UAV is attacked, a safety mechanism directs the UAV to a safe “home” location. This system has been validated on a commercial UAV under malicious attack conditions.Keywords
Funding Information
- National Aeronautics and Space Administration (NASA) issued through the Nevada NASA Space (NNX10AN23H)
- Nevada NASA Research Infrastructure Development Seed Grant (NNX15AI02H)
- National Science Foundation (IIS-1528137)
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