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This research evaluates a convolutional neural network (CNN) based approachto forensic video steganalysis. A video steganography dataset is created totrain a CNN to conduct forensic steganalysis in the spatial domain. We use anoise residual convolutional neural network to detect embedded secrets since asteganographic embedding process will always result in the modification ofpixel values in video frames. Experimental results show that the CNN-basedapproach can be an effective method for forensic video steganalysis and canreach a detection rate of 99.96%. Keywords: Forensic, Steganalysis, DeepSteganography, MSU StegoVideo, Convolutional Neural Networks

Forensic Video Steganalysis in Spatial Domain by Noise Residual Convolutional Neural Network