Unmanned Aircraft Systems (UAS)have raised a great concern on privacy recently. A practical method to protect privacy is needed for adopting UAS in civilian airspace. This thesis examines the privacy policies, filtering strategies, existing techniques, then proposes a new method based on encrypted video stream and cloud-based privacy servers. In this scheme, all video surveillance images are initially encrypted, then delivered to a privacy server. The privacy server decrypts the video using the shared key with the camera, and filters the image according to the privacy policy specified for the surveyed region. The sanitized video is delivered to the surveillance operator and anyone on the Internet who is authorized. In a larger system composed of multiple cameras and multiple privacy servers, the keys can be distributed using Kerberos protocol.
With this method the privacy policy can be changed on demand in real-time and there is no need for a costly on-board processing unit. By utilizing cloud-based servers, advanced image processing algorithms and new filtering algorithms, this method can be applied immediately without camera software upgrade. This method is cost-efficient and promotes video sharing among multiple subscribers, thus it can spur wider adoption
