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Robust steganographic techniques for secure biometric-based remote authentication

机译:可靠的隐写技术,用于基于生物特征的安全远程认证

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摘要

Biometrics are widely accepted as the most reliable proof of identity, entitlement to services, and for crime-related forensics. Using biometrics for remote authentication is becoming an essential requirement for the development of knowledge-based economy in the digital age. Ensuring security and integrity of the biometric data or templates is critical to the success of deployment especially because once the data compromised the whole authentication system is compromised with serious consequences for identity theft, fraud as well as loss of privacy. Protecting biometric data whether stored in databases or transmitted over an open network channel is a serious challenge and cryptography may not be the answer. The main premise of this thesis is that Digital Steganography can provide an alternative security solutions that can be exploited to deal with the biometric transmission problem.udThe main objective of the thesis is to design, develop and test steganographic tools to support remote biometric authentication. We focus on investigating the selection of biometrics feature representations suitable for hiding in natural cover images and designing steganography systems that are specific for hiding such biometric data rather than being suitable for general purpose. The embedding schemes are expected to have high security characteristics resistant to several types of steganalysis tools and maintain accuracy of recognition post embedding. We shall limit our investigations to embedding face biometrics, but the same challenges and approaches should help in developing similar embedding schemes for other biometrics. To achieve this our investigations and proposals are done in different directions which explain in the rest of this section.udReviewing the literature on the state-of-art in steganography has revealed a rich source of theoretical work and creative approaches that have helped generate a variety of embedding schemes as well as steganalysis tools but almost all focused on embedding random looking secrets. The review greatly helped in identifying the main challenges in the field and the main criteria for success in terms of difficult to reconcile requirements on embedding capacity, efficiency of embedding, robustness against steganalysis attacks, and stego image quality. On the biometrics front the review revealed another rich source of different face biometric feature vectors. The review helped shaping our primary objectives as (1) identifying a binarised face feature factor with high discriminating power that is susceptible to embedding in images, (2) develop a special purpose content-based steganography schemes that can benefit from the well-defined structure of the face biometric data in the embedding procedure while preserving accuracy without leaking information about the source biometric data, and (3) conduct sufficient sets of experiments to test the performance of the developed schemes, highlight the advantages as well as limitations, if any, of the developed system with regards to the above mentioned criteria.udWe argue that the well-known LBP histogram face biometric scheme satisfies the desired properties and we demonstrate that our new more efficient wavelet based versions called LBPH patterns is much more compact and has improved accuracy. In fact the wavelet version schemes reduce the number of features by 22% to 72% of the original version of LBP scheme guaranteeing better invisibility post embedding.udWe shall then develop 2 steganographic schemes. The first is the LSB-witness is a general purpose scheme that avoids changing the LSB-plane guaranteeing robustness against targeted steganalysis tools, but establish the viability of using steganography for remote biometric-based recognition. However, it may modify the 2nd LSB of cover pixels as a witness for the presence of the secret bits in the 1st LSB and thereby has some disadvantages with regards to the stego image quality.udOur search for a new scheme that exploits the structure of the secret face LBPH patterns for improved stego image quality has led to the development of the first content-based steganography scheme. Embedding is guided by searching for similarities between the LBPH patterns and the structure of the cover image LSB bit-planes partitioned into 8-bit or 4-bit patterns. We shall demonstrate the excellent benefits of using content-based embedding scheme in terms of improved stego image quality, greatly reduced payload, reduced lower bound on optimal embedding efficiency, robustness against all targeted steganalysis tools. Unfortunately our scheme was not robust against the blind or universal SRM steganalysis tool. However we demonstrated robustness against SRM at low payload when our scheme was modified by restricting embedding to edge and textured pixels. The low payload in this case is sufficient to embed a secret full face LBPH patterns.udOur work opens new exciting opportunities to build successful real applications of content-based steganography and presents plenty of research challenges.
机译:生物识别被公认为是最可靠的身份证明,获得服务的权利以及与犯罪有关的法证的证明。使用生物识别技术进行远程身份验证已成为数字时代发展基于知识的经济的基本要求。确保生物识别数据或模板的安全性和完整性对​​于部署成功至关重要,尤其是因为一旦数据遭到破坏,整个身份验证系统就会受到破坏,从而给身份盗用,欺诈和隐私丢失带来严重后果。保护生物识别数据,无论是存储在数据库中还是通过开放的网络通道传输,都是一个严峻的挑战,而加密技术可能并不是解决问题的办法。本文的主要前提是数字隐写术可以提供可替代的安全解决方案,可以用来解决生物特征传输问题。 ud本论文的主要目的是设计,开发和测试隐写术工具以支持远程生物特征认证。我们专注于调查适合隐藏在自然覆盖图像中的生物识别特征表示的选择,并设计专用于隐藏此类生物识别数据而非适合于一般用途的隐写系统。预计该嵌入方案具有对几种类型的隐写分析工具具有抵抗力的高安全性,并保持嵌入后的识别准确性。我们的研究将仅限于嵌入面部生物特征,但是相同的挑战和方法应有助于为其他生物特征开发类似的嵌入方案。为实现这一目标,我们在不同的方向上进行了研究和提出了建议,这将在本节的其余部分中进行解释。 ud对隐秘术的最新技术文献进行回顾后,我们发现了丰富的理论工作和创造性的方法,这些思想和方法有助于产生一种隐喻。各种各样的嵌入方案以及隐写分析工具,但几乎都集中在嵌入随机查找的秘密上。审查极大地帮助确定了该领域的主要挑战和成功的主要标准,包括难以协调的嵌入能力要求,嵌入效率,对隐写分析攻击的鲁棒性和隐秘图像质量。在生物识别方面,该评论揭示了不同面部生物特征矢量的另一个丰富来源。这项审查有助于塑造我们的主要目标,因为(1)识别具有高分辨力且易于嵌入图像的二值化脸部特征因素;(2)开发可从定义明确的结构中受益的基于内容的特殊目的密写方案嵌入程序中的面部生物特征数据,同时保持准确性而不会泄漏有关源生物特征数据的信息,并且(3)进行足够的实验集来测试已开发方案的性能,突出优势和局限性(如果有), ud我们认为,众所周知的LBP直方图人脸生物特征识别方案满足所需的特性,并且我们证明了称为LBPH模式的新的更有效的基于小波的版本要紧凑得多,并且已经进行了改进准确性。实际上,小波版本方案将特征数量减少了原始LBP方案版本的22%至72%,从而确保了更好的嵌入后隐身性。 ud我们将开发2种隐写方案。第一个是LSB-witness,它是一种通用方案,可避免更改LSB平面以确保针对目标隐写分析工具的鲁棒性,但确立了使用隐写术进行基于远程生物特征识别的可行性。但是,它可能会修改覆盖像素的第二个LSB,以作为第一个LSB​​中秘密位的出现的见证,从而在隐秘图像质量方面存在一些缺点。 ud我们正在寻找一种利用图像结构的新方案用于改善隐身图像质量的秘密面孔LBPH模式导致了第一个基于内容的隐身术方案的发展。通过搜索LBPH模式与划分为8位或4位模式的封面图像LSB位平面之间的相似性来指导嵌入。我们将展示使用基于内容的嵌入方案在改善隐秘图像质量,大大减少有效负载,降低最佳嵌入效率的下限方面的卓越好处。,针对所有目标隐写分析工具的鲁棒性。不幸的是,我们的方案对于盲目或通用SRM隐写分析工具并不强大。但是,当我们通过限制嵌入边缘和纹理像素来修改我们的方案时,我们展示了在低有效负载下针对SRM的鲁棒性。在这种情况下,低有效载荷足以嵌入一个秘密的全脸LBPH模式。 ud我们的工作为建立成功的基于内容的隐写术的实际应用打开了新的令人兴奋的机会,并提出了许多研究挑战。

著录项

  • 作者

    Rashid Rasber Dhahir;

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  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 en
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