R. Cogranne, Cathel Zitzmann, F. Retraint, I. Nikiforov, Philippe Cornu, L. Fillatre
{"title":"Statistical detection of information hiding based on adjacent pixels difference","authors":"R. Cogranne, Cathel Zitzmann, F. Retraint, I. Nikiforov, Philippe Cornu, L. Fillatre","doi":"10.5281/ZENODO.42812","DOIUrl":null,"url":null,"abstract":"This paper presents a novel methodology for statistical detection of Least Significant Bits (LSB) matching steganography. It proposes to exploit a statistical model of natural images adjacent pixels difference. In this paper, the detection problem is first addressed in a theoretical context when cover image parameters are known. The most powerful likelihood ratio test (LRT) is designed and its statistical performances are analytically expressed. Then, for a practical case of unknown image analysis, an estimation of distribution parameters is proposed to designed a test whose performance are also analytically established. Numerical results on a large image database shows the relevance of proposed methodology.","PeriodicalId":201182,"journal":{"name":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.42812","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
This paper presents a novel methodology for statistical detection of Least Significant Bits (LSB) matching steganography. It proposes to exploit a statistical model of natural images adjacent pixels difference. In this paper, the detection problem is first addressed in a theoretical context when cover image parameters are known. The most powerful likelihood ratio test (LRT) is designed and its statistical performances are analytically expressed. Then, for a practical case of unknown image analysis, an estimation of distribution parameters is proposed to designed a test whose performance are also analytically established. Numerical results on a large image database shows the relevance of proposed methodology.