In this paper we present an effective steganalyis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability and low complexity the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this paper, we present a method that overcomes this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking, and more sophisticated pattern recognition tools. Applications of our scheme include cybersecurity and cyberforensics.