Video content stored in Video Event Data Recorders (VEDRs) are used as important evidence when certain events such as vehicle collisions occur. However, with sophisticated video editing software, assailants can easily manipulate video records to their advantage without leaving visible clues. Therefore, the integrity of video content recorded through VEDRs cannot be guaranteed, and the number of related forensic issues increases. Existing video integrity detection methods use the statistical properties of the pixels within each frame of the video. However, these methods require ample time, because they check frames individually. Moreover, the frame can easily be replaced and forged using the appropriate public software. To solve this problem, we propose an integrity checking mechanism using the structure of ordered fields in a video file, because existing video editing software does not allow users to access or modify field structures. In addition, because our proposed method involves checking the header information of video content only once, much less detection time is required compared with existing methods that examine the entire frames. We store an ordered file structure of video content as a signature in the database using a customized automated tool. The signature appears according to the video editing software. Then, the suspected video content is compared to a set of signatures. If the file structure matches with a signature, we recognize a manipulated video file by its corresponding editing software. We tested five types of video editing software that cover 99% of the video editing software market share. Furthermore, we arranged 305,981 saving options for all five video editing suites. As a result, we obtained 100% detection accuracy using stored signatures, without false positives, in a collection of 305,981 video files. The principle of this method can be applied to other video formats. (C) 2016 Elsevier Ltd. All rights reserved.