An Intrusion Detection System for Drone Swarming Utilizing Timed Probabilistic Automata

Unmanned aerial vehicles (UAVs), commonly known as drones, have found extensive applications across diverse sectors, such agriculture, delivery, surveillance, and military. In recent times, drone swarming has emerged a novel field of research, which involves multiple drones working in collaboration towards shared objective. This innovation holds immense potential transforming the way we undertake tasks, including military operations, environmental monitoring, search rescue missions. However, emergence swarms also brings new security challenges, they can be susceptible to hacking intrusion. To address these concerns, propose utilizing timed probabilistic automata (TPA)-based intrusion detection system (IDS) model normal behavior identify any deviations that may indicate an IDS is particularly efficient adaptable detecting different types attacks swarming. Its ability adapt evolving attack patterns zero-day makes it invaluable tool protecting from malicious attacks.