<p>This research proposes a new approach of implementing machine learning models such that, when applied to a drone, it will be able to accurately identify and maintain the authenticity of the entity sending the control data to the drone. The drone will determine the average received signal strength indicator (RSSI) of incoming signals and use that average to calculate the distance between the drone and the signal source. This will be fed into an implementation of the SCluStream algorithm to assign that point to the cluster that best fits it. As the drone is flying, the clusters will showcase the natural change in distances between the drone and the signal source. Over time, these clusters will gradually change to reflect new patterns of distances. If any of the data points being fed into the algorithm is determined to be an outlier, then this indicates that the signal source is either too close or too far away from the drone to be the authorized signal source. If this is the case, then the drone can take appropriate action against this probable threat.</p>