{"title":"Tampering Detection of Audio-Visual Content Using Encrypted Watermarks","authors":"Ronaldo Rigoni, P. Freitas, Mylène C. Q. Farias","doi":"10.1109/SIBGRAPI.2014.50","DOIUrl":null,"url":null,"abstract":"In this paper, we present a framework for detecting tampered information in digital videos. Using the proposed technique is possible to detect several types of tampering with a pixel granularity. The framework uses a combination of temporal and spatial watermarks that do not decrease the perceived quality of the host videos. We use a modified version of Quantization Index Modulation (QIM) algorithm to store the watermarks. Since QIM is a fragile watermarking scheme, it is possible to detect local, global, and temporal tampers and also estimate the attack type. The framework is fast, robust, and accurate.","PeriodicalId":146229,"journal":{"name":"2014 27th SIBGRAPI Conference on Graphics, Patterns and Images","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 27th SIBGRAPI Conference on Graphics, Patterns and Images","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBGRAPI.2014.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we present a framework for detecting tampered information in digital videos. Using the proposed technique is possible to detect several types of tampering with a pixel granularity. The framework uses a combination of temporal and spatial watermarks that do not decrease the perceived quality of the host videos. We use a modified version of Quantization Index Modulation (QIM) algorithm to store the watermarks. Since QIM is a fragile watermarking scheme, it is possible to detect local, global, and temporal tampers and also estimate the attack type. The framework is fast, robust, and accurate.