{"title":"A Novel Approach to Detect the Presence of LSB Steganographic Messages","authors":"Zongyuan Deng, Xi Shao, Zhen Yang","doi":"10.1109/SNPD.2007.303","DOIUrl":null,"url":null,"abstract":"Digital steganography introduces statistical distortion to some extent. Thus, steganalysis can be used to classify an object with or without hidden information. In this paper, we present a novel approach to detect the presence of LSB (least significant bit) steganographic messages in the voice secure communication system. A distance measure, which has been proved to be sensitive to LSB steganography by ANOVA (analysis of variance), is denoted to estimate the difference between the host signal and the stego signal. Then a MI (maximum likelihood) decision is combined to form the classifier. Statistical experiments show that the proposed approach has highly accurate rate and low computational complexity.","PeriodicalId":197058,"journal":{"name":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","volume":"360 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2007.303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Digital steganography introduces statistical distortion to some extent. Thus, steganalysis can be used to classify an object with or without hidden information. In this paper, we present a novel approach to detect the presence of LSB (least significant bit) steganographic messages in the voice secure communication system. A distance measure, which has been proved to be sensitive to LSB steganography by ANOVA (analysis of variance), is denoted to estimate the difference between the host signal and the stego signal. Then a MI (maximum likelihood) decision is combined to form the classifier. Statistical experiments show that the proposed approach has highly accurate rate and low computational complexity.