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Signal noise and its relevance in adaptive steganography and steganalysis.

机译：信号噪声及其在自适应隐写术和隐写分析中的相关性。

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摘要

Steganography may serve as a viable solution for the government and military to maintain the integrity of classified and sensitive material or allow strategic communication or coordination between our internal entities or between the U.S. and our allies. However, some would use steganography with malicious intent, such as terrorist trying to secretly communicate and coordinate their horrendous attacks. There is an obvious need for more secure methods of communication and better means of detecting steganography-bearing media. Signal noise exists in all aspects of today's world. Digital imagery, for example, will always have a natural level of noise caused by quantization error during capture, unstable camera electronics, and from noisy transmission channels. Since inserting steganography into a digital image is very similar to inserting a small level of noise, by understanding noise models and the principles of noise detection, we can improve methods of inserting secret information into a digital image. A fundamental understanding of the characteristics of noise will also allow us to distinguish signal noise from 'steganography noise' and thus improve our detection accuracy. This thesis will focus on accomplishing the following 3 objectives: (1) Developing a filtering method that will accurately identify and classify image pixels corrupted by noise and appropriately filter them, (2) Develop new steganography with more embedding capacity and higher security, and (3) Develop new steganalysis techniques that can detect hidden information with a high degree of accuracy and be useful for detecting a large range of embedding methods.
机译：隐秘术可以作为政府和军方维持机密和敏感材料的完整性的可行解决方案，或者允许我们内部实体之间或美国与盟国之间进行战略性沟通或协调。但是，有些人会出于恶意目的使用隐写术，例如恐怖分子试图秘密交流和协调他们的恐怖袭击。显然，需要更安全的通信方法和更好的手段来检测隐秘媒体。信号噪声存在于当今世界的各个方面。例如，数字图像将始终具有自然水平的噪声，该噪声是由捕获期间的量化误差，不稳定的相机电子设备以及嘈杂的传输通道引起的。由于将隐写术插入数字图像与插入少量噪声非常相似，因此通过了解噪声模型和噪声检测原理，我们可以改进将秘密信息插入数字图像的方法。对噪声特性的基本了解还将使我们能够将信号噪声与“隐匿性噪声”区分开来，从而提高检测精度。本论文将着重于实现以下3个目标：（1）开发一种滤波方法，以准确地识别和分类受噪声破坏的图像像素并对其进行适当的滤波;（2）开发具有更高嵌入能力和更高安全性的新隐写术，以及（ 3）开发新的隐写分析技术，可以高度准确地检测隐藏的信息，并且对检测大量的嵌入方法很有用。

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  • 作者

    Sifuentes, Ronnie Reyes, Jr.;

  • 作者单位

    The University of Texas at San Antonio.;

  • 授予单位 The University of Texas at San Antonio.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2009
  • 页码 88 p.
  • 总页数 88
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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