Detecting and preventing rogue drone behaviour using digital twins
The drone sector expects huge growth over the next five to ten years. However, through extensive research and market validation, experts in cyber technology at Queen’s University Belfast have identified market needs and potential fears, including a significant risk of collateral damage.
Attacks on drones are relatively easy to carry out, thus providing a need to investigate any potential attacks as well as detect and prevent them. Existing approaches rely on expensive technology and heavy equipment, both complex to deploy and unable to distinguish threat type.
D-RON leverages AI and digital twin technology to deliver a resilient, cost-effective platform that offers swarm movement detection, pattern tracing and individual movement tracking of drones. It will also provide better observation and reporting, faster response times, and fewer false positives.
The technology offers real-time anomaly detection as well as group authentication, self-checking logic and peer-to-peer observations. This solution could be useful in investigating whether drone swarms have fallen victim to cyber attack.
- Anti-drone companies
- Military and commercial
- Building owners who want to avoid drone fly-overs
Status & Needs
- Proof of Concept ready
- Require resources to take MVP to market
- Seeking engineering support