LAUSR

With the immensely growing rate of cyber forgery today, the integrity and authenticity of digital multimedia data are highly at stake. In this work, we deal with forensic investigation of cyber forgery in digital videos. The most common types of inter-frame forgery in digital videos are frame insertion, deletion and duplication attacks. A number of significant researches have been carried out in this direction, in the past few years. In this paper, we propose a two-step forensic technique to detect frame insertion, deletion and duplication types of video forgery. In the first step, we detect outlier frames, based on Haralick coded frame correlation; and in the second step, we perform a finer degree of detection, to eliminate false positives, hence to optimize the forgery detection accuracy. Our experimental results prove that the proposed method outperforms the state–of–the–art with an average F1 score of 0.97 in terms of inter–frame video forgery detection accuracy.