IoT-Driven Cybersecurity Framework for Intrusion Detection in the Internet of Drones

The proposed project will deliver an AI-driven, multi-tier cybersecurity framework designed for autonomous drones operating in critical sectors such as disaster relief, search and rescue, surveillance, and medical deliveries. As drones play an increasingly crucial role in these high-risk operations, they become targets for malicious attacks that exploit vulnerabilities through hijacking, spoofing, and data breaches, potentially jeopardizing mission success and public safety. The proposed system will ensure trustworthiness and security at multiple levels within a drone network, continuously evaluating and verifying the integrity of individual drones, securing drone-to-drone and drone-to-infrastructure communication, and safeguarding cloud-based mission control systems. AI-driven anomaly detection and behavioural analysis will be at the core of the framework, enabling real-time identification and mitigation of security threats to maintain operational integrity. Unlike traditional single-tier security solutions, which are often inadequate for highly mobile, autonomous systems, this multi-tier intrusion detection and trust management approach will offer robust protection against evolving cyber risks. The framework will integrate machine learning techniques to detect unauthorised activity, ensuring resilient and tamper-proof drone operations, particularly in challenging environments where reliability is paramount. With the increasing role of drones in emergency healthcare logistics, such as delivering defibrillators and critical medical supplies, it is imperative to guarantee secure and reliable operations. The proposed system will provide next-generation cybersecurity protection, reinforcing trust, safety, and operational resilience in the rapidly evolving field of autonomous aerial systems.