  Unmanned Aircraft Vehicles (UAVs) are becoming a crucial tool in modern
warfare, primarily due to their cost-effectiveness, risk reduction, and ability
to perform a wider range of activities. The use of autonomous UAVs to conduct
strike missions against highly valuable targets is the focus of this research.
Due to developments in ledger technology, smart contracts, and machine
learning, such activities formerly carried out by professionals or remotely
flown UAVs are now feasible. Our study provides the first in-depth analysis of
challenges and preliminary solutions for successful implementation of an
autonomous UAV mission. Specifically, we identify challenges that have to be
overcome and propose possible technical solutions for the challenges
identified. We also derive analytical expressions for the success probability
of an autonomous UAV mission, and describe a machine learning model to train
the UAV.
