SHIELD gives drones the power to detect and recover from cyberattacks mid-flight, using AI to track hardware and software anomalies.
A drone taken over by hackers can turn from an efficient flying tool into a dangerous machine. Once under rogue control, it may fly unpredictably, slow down, reverse direction, or crash.When that happens, it loses its mission completely, whether it was delivering a package, inspecting a bridge, or surveying farmland.
With drone use expanding across industries, the risk of such attacks is becoming harder to ignore.To address this, researchers at Florida International University have developed SHIELD, a new system that allows drones to detect and recover from cyberattacks while still in flight.The technology adds a crucial safety layer at a time when regulators and companies are preparing to put more drones in the sky.Unlike existing defense methods that rely mainly on sensors, SHIELD monitors a drone’s entire control system.It looks for signs of malicious activity not just in software but in the underlying hardware too. Once it detects something unusual, it identifies the type of attack and triggers a response plan designed to restore normal operation.“Without robust recovery mechanisms, a drone cannot complete its mission under attacks, because even if it is possible to detect the attacks, the mission often gets terminated as a fail-safe move,” said Mohammad Ashiqur Rahman, lead researcher and associate professor in FIU’s Knight Foundation School of Computing and Information Sciences.He added, “What’s important about our framework is that it helps the system recover, so the mission can be completed.”Why sensor defenses fall shortTraditional drone defenses focus on navigation sensors that prevent collisions and guide flight paths. But those sensors can be manipulated. In one common attack, known as GPS spoofing, hackers transmit false location data that tricks a drone into flying off course.More advanced intrusions bypass sensors completely and target a drone’s internal systems through malware.“This is why a detection and recovery system that only takes into account the sensors misses the bigger picture,” said Muneeba Asif, Ph.D. candidate in Rahman’s research group and study author. “It will be blind to other attacks that happen across the system and at different levels.”SHIELD goes deeper by tracking the drone’s physical components. Fluctuations in battery levels or an overworked processor can signal that an attack is underway. By watching these signs in real time, the system can catch attacks before they cause damage.The team used machine learning models to train SHIELD to recognize different attack patterns. In testing, the system detected cyberattacks in an average of 0.21 seconds and began recovery in 0.36 seconds.Researchers compared their approach to how doctors diagnose patients. Like sensor data, a single symptom doesn’t always show what’s wrong, but deeper physical evidence often does.Similarly, every attack leaves a distinct signature that requires its own treatment plan.Securing the future of flightThe need for such technology is growing fast. The Federal Aviation Administration has proposed expanding drone use across industries, from delivery to agriculture and disaster response.With more drones expected to operate in sensitive environments, security breaches could have wider consequences.“Reliable and secure drones are the key to unlocking future advancements,” Rahman said. “It’s our hope this work can play a role in moving the industry forward.”By giving drones the ability to detect, react, and recover mid-flight, FIU’s SHIELD system could mark a major step toward safer skies.The team presented its findings at the IEEE/IFIP International Conference on Dependable Systems and Networks, a leading event in the cybersecurity research field.
Cyberattacks Drone Cybersecurity Drone Defense System Drone Safety Hardware Security Machine Learning SHIELD
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