Deployment of the AI-Driven HoneyDroneSystem for Modern Battlefield and Cybersecurity Defense

Abstract

With the rapid advancements in Artificial Intelligence (AI) and Unmanned Aerial Vehicle (UAV) technology, the fields of national defense and cybersecurity are entering a new era of intelligent defense mechanisms. HoneyDrone, an innovative integration of honeypot technology and deception-based UAV defense, possesses autonomous learning and adaptive capabilities, enabling effective countermeasures against cybersecurity threats such as Distributed Denial-of-Service (DDoS) attacks, GPS spoofing, and relay attacks.
This study examines the core technological framework of HoneyDrone and evaluates its advantages and challenges in defense applications. By leveraging Deep Reinforcement Learning (DRL) for tactical optimization, Computer Vision for enhanced environmental perception, and Game Theory for computing optimal defense strategies, HoneyDrone dynamically adjusts its deception mechanisms and countermeasures based on adversarial behavior patterns. Additionally, it employs Swarm Intelligence to facilitate multi-drone collaboration, enabling real-time intelligence sharing and improving overall operational efficiency.
Through an analysis of recent international cases—including UAV electronic warfare in the Russia-Ukraine conflict, cyberattacks on critical U.S. infrastructure, and Advanced Persistent Threats (APT) in the Asia-Pacific region—this research validates HoneyDrone’s strategic value in modern warfare and cybersecurity. As AI and UAV technologies continue to evolve, HoneyDrone not only enhances autonomous defense capabilities but also offers a forward-looking solution for safeguarding critical infrastructure.