Video Source Characterization Using Encoding and Encapsulation Characteristics
| Autor: | Enes Altinisik, Husrev Taha Sencar, Diram Tabaa |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Information Forensics and Security. 17:3211-3224 |
| ISSN: | 1556-6021 1556-6013 |
| DOI: | 10.1109/tifs.2022.3204210 |
| Popis: | We introduce a new method for camera-model identification. Our approach combines two independent aspects of video file generation corresponding to video coding and media data encapsulation. To this end, a joint representation of the overall file metadata is developed and used in conjunction with a two-level hierarchical classification method. At the first level, our method groups videos into metaclasses considering several abstractions that represent high-level structural properties of file metadata. This is followed by a more nuanced classification of classes that comprise each metaclass. The method is evaluated on more than 20K videos obtained by combining four public video datasets. Tests show that a balanced accuracy of 91% is achieved in correctly identifying the class of a video among 119 video classes. This corresponds to an improvement of 6.5% over the conventional approach based on video file encapsulation characteristics. Furthermore, we investigate a setting relevant to forensic file recovery operations where file metadata cannot be located or are missing but video data is partially available. By estimating a partial list of encoding parameters from coded video data, we demonstrate that an identification accuracy of 57% can be achieved in camera-model identification in the absence of any other file metadata. |
| Databáze: | OpenAIRE |
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