  Drones, also known as mini-unmanned aerial vehicles, have attracted
increasing attention due to their boundless applications in communications,
photography, agriculture, surveillance and numerous public services. However,
the deployment of amateur drones poses various safety, security and privacy
threats. To cope with these challenges, amateur drone surveillance becomes a
very important but largely unexplored topic. In this article, we firstly
present a brief survey to show the state-of-the-art studies on amateur drone
surveillance. Then, we propose a vision, named Dragnet, by tailoring the recent
emerging cognitive internet of things framework for amateur drone surveillance.
Next, we discuss the key enabling techniques for Dragnet in details,
accompanied with the technical challenges and open issues. Furthermore, we
provide an exemplary case study on the detection and classification of
authorized and unauthorized amateur drones, where, for example, an important
event is being held and only authorized drones are allowed to fly over.
