Citizen journalism videos increasingly complement or even replace the professional news coverage through direct reporting by event witnesses. This raises questions of the integrity and credibility of such videos. We introduce Vamos, the first user transparent video "liveness" verification solution based on video motion, that can be integrated into any mobile video capture application without requiring special user training. Vamos' algorithm not only accommodates the full range of camera movements, but also supports videos of arbitrary length. We develop strong attacks both by utilizing fully automated attackers and by employing trained human experts for creating fraudulent videos to thwart mobile video verification systems. We introduce the concept of video motion categories to annotate the camera and user motion characteristics of arbitrary videos. We share motion annotations of YouTube citizen journalism videos and of free-form video samples that we collected through a user study. We observe that the performance of Vamos differs across video motion categories. We report the expected performance of Vamos on the real citizen journalism video chunks, by projecting on the distribution of categories. Even though Vamos is based on motion, we observe a surprising and seemingly counterintuitive resilience against attacks performed on relatively "static" video chunks, which turn out to contain hard-to-imitate involuntary movements. We show that the accuracy of Vamos on the task of verifying whole length videos exceeds 93% against the new attacks.
