Reliable Pooled Steganalysis Using Fine-Grained Parameter Estimation and Hypothesis Testing

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• 关键词：Steganalysis ; Steganography ; Parameter estimation ; Hypothesis testing
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10082
• 期：1
• 页码：550-563
• 丛书名：Digital Forensics and Watermarking
• ISBN：978-3-319-53465-7
• 卷排序：10082

文摘

Despite the state-of-the-art steganalysis can detect highly undetectable steganography, it is too unreliable to implement in the real world due to its false alarm rate. In pooled steganalysis scenario, multiple objects are intercepted and a reliable collective decision is required. To control the reliability, the confidence intervals of the detectors’ false rates are estimated as a parameter and hypothesis testing technology is used to determine the threshold of stego rates. In view of the fact that the false rate is vulnerable to some image properties (e.g. image size, and texture complexity), we propose a novel fine-grained scheme where test sets are divided by its texture measure in both parameter estimation and hypothesis testing processes. The demonstration on public image sets shows the proposed scheme achieves higher reliability in most cases. It confirms that the priori knowledge of image properties is conductive to a accurate threshold and reliable decision.