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A Self-Diagnosis Method for Detecting UAV Cyber Attacks Based on Analysis of Parameter Changes
- Source :
- Sensors, Vol 21, Iss 509, p 509 (2021), Sensors, Volume 21, Issue 2, Sensors (Basel, Switzerland)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- We consider how to protect Unmanned Aerial Vehicles (UAVs) from Global Positioning System (GPS) spoofing attacks to provide safe navigation. The Global Navigation Satellite System (GNSS) is widely used for locating drones and is by far the most popular navigation solution. This is because of the simplicity and relatively low cost of this technology, as well as the accuracy of the transmitted coordinates. Nevertheless, there are many security threats to GPS navigation. These are primarily related to the nature of the GPS signal, as an intruder can jam and spoof the GPS signal. We discuss methods of protection against this type of attack and have developed an experimental stand and conducted scenarios of attacks on a drone&rsquo<br />s GPS system. Data from the UAV&rsquo<br />s flight log were collected and analyzed in order to see the attack&rsquo<br />s impact on sensor readings. From this we identify a new method for detecting UAV anomalies by analyzing changes in internal parameters of the UAV. This self-diagnosis method allows a UAV to independently assess the presence of changes in its own subsystems indicative of cyber attacks.
- Subjects :
- Spoofing attack
Computer science
UAV
GPS
Real-time computing
ComputerApplications_COMPUTERSINOTHERSYSTEMS
Satellite system
spoofing
02 engineering and technology
lcsh:Chemical technology
GPS signals
01 natural sciences
Biochemistry
Article
Analytical Chemistry
0202 electrical engineering, electronic engineering, information engineering
lcsh:TP1-1185
Electrical and Electronic Engineering
Instrumentation
business.industry
010401 analytical chemistry
020206 networking & telecommunications
Self-diagnosis
cyber threats
Atomic and Molecular Physics, and Optics
Drone
0104 chemical sciences
GNSS applications
Global Positioning System
anomalies
entropy
business
cyber attacks
Subjects
Details
- ISSN :
- 14248220
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....1dbb0e96094c21861b9695556a70e6b0