Energy-efficient malware detection for UAVs
For SecureUAV the goal is to develop a platform and framework for increased cybersecurity protection and end-user awareness of cyberthreats in unmanned aerial vehicles (UAV) through the use of AI and human-understandable decision support models
Project Information
- Project ID
- NGI-ATLANTIC:OC05-385
- Contact
- Dr Andrii Shalaginov (Høyskolen Kristiania – Ernst G Mortensens stiftelse)
- Countries
- norway, united states
Related Products
Software or product(s) created or improved through this project
Additional Information
SecureUAV project’s vision is to enhance the overall operational UAVs security as well as Linux-based and similar mainboards that run mission-critical functionality process video streams and maintain communication with drone operators through sophisticated remote controllers Such communication is usually maintained with the help of AES-256 or similar standards while transmitting altitude distance GPS location velocities battery level and temperature However there is no low-threshold information about the drone system cybersecurity status or if there are any virus infection or attack happening So modern UAV system needs a toolkit to provide an insight into cyber-physical cybersecurity awareness and telemetry Even though there are available commercial cybersecurity solutions to guard Linux such as anti-virus (AV) or intrusion detection systems (IDS) energy consumption aspects make them nearly inapplicable
End-User Relevance
This experiment will improve the security of Unmanned Aerial Vehicles (UAV)s by detecting malicious activities and cyber-physical threats to ensure a timely incident response by drone operator
Disclaimer: This experiment is currently underway
Community Discussion 3 comments
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