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引用次数: 3

摘要

数字隐写术在一定程度上引入了统计失真。因此,隐写分析可以用来对有或没有隐藏信息的对象进行分类。本文提出了一种检测语音安全通信系统中存在的LSB(最低有效位)隐写信息的新方法。用方差分析(ANOVA)证明了对LSB隐写很敏感的距离度量来估计宿主信号和隐写信号之间的差异。然后结合最大似然决策形成分类器。统计实验表明,该方法具有较高的准确率和较低的计算复杂度。
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A Novel Approach to Detect the Presence of LSB Steganographic Messages
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.
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