图像信息隐藏关键技术研究
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摘要
互联网和无线网络为信息传递和交换提供了广泛渠道。由于互联网的兴起,信息安全成为了信息科学和通讯中最重要的因素之一。信息隐藏也被应用于军事、情报机构、非法和犯罪活动、卫生保健和其他重视数据安全的领域。互联网中有大量图像可以用于隐藏信息。好的信息隐藏算法具有较高的不易察觉性和信息隐藏量,较好的对于图像修改(图像压缩等)的鲁棒性。在图像中隐藏信息可能会有损图像质量。然而,用合适的技术能够增加信息隐藏量而不会对图像内容造成明显的损失。
信息隐藏的想法可以追溯到几千年前。在实践中通过简单加密使内容模糊的方法并不足够。在竞争情况下,隐藏沟通的存在是用于避免对手的嫌疑,字面意思是“隐秘”,它源于希腊和今天仍然在使用的“覆盖的写作”。隐蔽通信的许多故事已经过几代人的实践,但他们主要用于军方和情报机构。隐写术是科学,涉及通信秘密数据在适当的多媒体载体,例如,图像,音频和视频文件。假设下,如果该功能是可见的,攻击点是显而易见的,因此,这里的目标是嵌入式的数据总是以隐藏的方式存在。
不是玩用语,本文使用三个方面的加密技术,信息隐藏和数字水印。嵌入的数据,通常被称为水印(次),用途广泛,其中每一个与之不同的鲁棒性,安全性和嵌入容量要求。与其他解决方案相比,隐藏数据的主要优点是它能够以无缝的方式与主媒体辅助数据关联。稍后我们将看到在这篇论文中,无缝连接在许多应用中是可取的。例如,嵌入的水印可以与主机媒体运行,并承担其保护功能,即使在解密后,唯一的例外是二级数据预期是潜移默化的。
三种技术是相通的,隐秘,水印和加密技术,信息隐藏一词的标准和概念“所见即所得(WYSIWYG)",我们有时会遇到打印图像或其他材料的同时,不再是精确的,不会是速记式加密,因为它并不是总成立的。图像可以是更多速记式加密比我们所看到的与我们人类视觉系统(HVS),因此,他们仅仅可以传达超过1000字。直观地看,这项工作使得使用由隐秘和水印社区的常用的一些术语。在整个本文的术语“封面图像”将被用于描述指定的图像进行嵌入的位。嵌入的数据,这里称为有效载荷中的图像被称为“隐写图像”。此外“隐写”或“攻击”是指不同的图像处理和统计分析方法,旨在破坏或攻击隐写算法。
从这个简短的概述,已经可以注意到隐秘和水印的另一个根本区别。隐藏的水印系统的信息总是与被保护对象或数字,它的主人,是隐藏的隐秘系统内的任何信息。“鲁棒性”的标准也不同,因为隐秘关注的主要是检测隐藏的消息,同时关注潜在的去除水印。最后,隐蔽通信通常是点至点(在发送者和接收者之间),而数字水印技术通常是一到多。
隐藏技术,对数据进行分类的方法有很多。一个简单的分类是根据小学多媒体源的类型来划分,为我们的数据隐藏系统提供感性和非感性来源。本论文关注的是感性的来源,包括二进制图像和彩色或灰度图像。在数字信号源,非感性和感性的非数据之间的主要区别是,非感性的数据,如文本和可执行代码,通常需要无损处理,传输和存储。翻转单位,可能会导致不同的含义。感知的数据,但是,有一个感性的公差范围内,允许微小的变化,之前被人类注意到。这种感性的属性使感性降解可控量。
感知性方面,数据隐藏技术可分为两组；感知并觉察不到隐藏。可察觉的水印主要用于图像和视频。甲视觉上有意义的图案,如徽标,覆盖在图像或视频,这本质上是一个图像编辑或合成的问题。可见水印明确表现出版权,所有权信息或访问控制政策,以阻止滥用的水印图像
半透明的标志通常通过广播网络电视节目和预览图像通过万维网访问受版权持有人。当前的数据大部分研究关注隐藏与潜移默化的水印。正如我们前面提到的,感知模型需要加以探讨,以确保由一个嵌入系统强加的改变是潜移默化地保留感知质量和价值的多媒体来源。
应用程序域是另一种标准数据隐藏技术的分类。经典应用包括所有权保护,身份验证,指纹识别,复制/门禁和注释。我们将简要地解释每个应用程序的设计要求：
1.所有权保护：表示所有权水印嵌入多媒体源。水印,只有版权持有人,预计生存共同处理和故意攻击,让主人可以显示水印,存在争议的情况下,以证明他／她的所有权。检测应尽可能的不能有一点含糊和误报。总的嵌入容量,小的错误概率,可以嵌入和提取的比特数,即不具有在大多数情况下要高。
2.身份验证／篡改检测：次要数据的一组预先嵌入在多媒体源,是用来确定主机媒体是否被篡改或去除水印的鲁棒性对或使其无法察觉的是不是一个问题,从攻击者的角度来看,有没有这样的刺激。然而,必须防止在未经授权或篡改的媒体源锻造一个有效的认证水印。在实际应用中,这也是可取的定位篡改,以及其他一些变化(如内容篡改)区分的一些变化(如非内容的变化所产生的适度的有损压缩)。嵌入容量一般要高,以适应这些需求。应进行检测,没有原始水印的复制,因为这原来是不可用或尚未建立其完整性。这种检测通常被称为非相干检测或盲检测。
3.指纹或标签：在这个应用程序中的水印是用来跟踪的起源或多媒体源的特定副本收件人。例如,不同的水印嵌入多媒体来源不同的副本,然后再分发到多个接收者。稳健反对抹杀和能力传达一个不平凡的比特数是必需的。
4.复制控制和访问控制嵌入的水印在这种情况下,代表一定的的拷贝控制或访问控制策略。水印检测器通常集成在一个记录／重放系统中,像拟议的DVD拷贝控制和持续SDMI活动的。经检测,在政策执行指挥某些硬件或软件的行动中,如启用或禁用记录模块。反对拆除,盲检测的能力,有能力传达一个不平凡的比特数的鲁棒性是必需的。
5.注释：在这个应用程序中嵌入的水印预计传达尽可能不使用原始无人盯防的副本检测多达位。虽然免受蓄意攻击的鲁棒性不是必需的,对常见的处理,有一定程度的鲁棒性,可以有损压缩。
视觉密码是一种方法,在一组的参与者中,其中某些组的参与者定义为合格,并结合自己的股份,以获得原始秘密图像的秘密图像共享一个秘密图像,但其他某些群体被定义为禁地,即使他们结合知识及其零部件的秘密图像,他们无法获得任何信息的原始秘密图像。黑白像素组成的图像。像素是最广泛使用的数字图像表示元素的术语。进行编码的秘密的图像中,每个像素被分成m个子像素,其中一些是黑色的,其中有一些是白色的。这些子像素是如此之小,他们的眼睛的平均一些的灰色阴影,被称为空间频率分辨率。每个参与者的股份(透明度)的图像看起来黑色和白色像素的随机分布。参与者只需叠加透明胶片。参数m称为的像素膨胀,使得此参数小装置节省存储空间,并减少传输时间。
有趣的是,视觉密码解密,因为不需要计算,而是通过人的视觉系统。图像重建相结合,一个合格的组参与者的股份,与秘密图像是不相同的。秘密图像的像素,白色比黑色的图像的像素是一个打火机的灰色阴影,在黑暗的黑色和白色像素的差异是一个参数,称为对比度。在理想的情况下,最高的对比度在分化黑色和白色区域的术语能给出较好的结果。
共享方案的安全性依赖于信息,可以从每个单一股份或任何禁组参与者的股份中获得秘密图像。这涉及到多远的子像素随机分布在每个份额,产生的图像合并。
对温和派的处理如压缩,不可见性,鲁棒性和能力(能够隐藏多少位)是许多数据隐藏应用程序的基本而是相互冲突的要求。此外,在实践中遇到的其他一些重要问题,如图像和嵌入容量不均的二进制图像的感知模型,很少受到关注文学。视觉需求模型,被称为神奇的三角形。第一个要求,容量也嵌入的有效负载,确定嵌入在每个盖像素的比特的数量。较高的容量允许的更机密的数据被插入到封面图像。第二个要求,名为“不可感知性,通常是计算峰值信号信噪比(PSNR)。当封面图像和隐写图像之间的差异小时,PSNR值是高的。因此,隐写图像质量被认为是好的时,不可见性高。至目前为止,要求被称为鲁棒性,从而防止从图像中被攻击或被盗的秘密数据。然而,只有持有添加复杂的图像的一部分的信息。原因有很多隐藏的数据,但他们都归结为防止未经授权的人员存在知悉消息的欲望。
数字信息的许多优点,产生了新的挑战和新的机遇创新。互联网提供无处不在的提供和交换信息的渠道。多媒体数据,以及快速传送多媒体内容的各种最终用户／设备数量和安全保证使用的安全性和公平是重要而又具有挑战性的课题。这些问题的解决方案将不仅有助于我们了解这个快速移动的复杂的技术,而且还提供了探索的新的经济机会。随着互联网和数字媒体的广泛使用,已经成为信息隐藏通信秘密或未经授权的复制保护他人的数字作品感兴趣的人尤其重要。信息隐藏包括隐秘,不愿透露姓名的覆盖渠道和版权标记等不同的主题。这些主题大多有着悠久的历史,发现他们的方式融入日常的生活和流行文化。已经提出了许多技术的各种应用。数据隐藏也可作为一般的多媒体通信中的发送方信息的工具来实现额外的功能或提高性能。
有几个原因限制调查仅适用于图像信息隐藏。图像在互联网上广泛存在,并有提高的可能,可作为载体对象。他们有很多格式, JPEG和GIF是使用的最广泛。(反之,音频文件通常是MPEG3格式,视频是MPEG1或MPEG2格式)。最后,大多数的图像文件是相当大的,有对很多没有明显损坏的图像内容进行修改的能。
类型的图像数据被划分为两个主要的类别：位图和矢量。位图图像(也称为光栅图像),可以通过图像模型I(R,C),每个像素数据具有一些文件格式存储在一个相应的亮度值。矢量图像是指代表直线,曲线和形状的方法存储的关键点(这主要是用计算机图形,而不是自然的图像)。这些关键点是足以定义的形状,并把它们转变成一个图像,其过程被称为渲染。已经被渲染的图像之后,就可以认为是作为位图的格式,其中每个像素具有与它相关联的特定值。
部分的位图图像的压缩,这样,I(R,C)的值是不能直接使用,直到该文件被解压缩。在一般情况下,这些类型的图像包含的标题信息和原始像素数据。标头必须包含有关的行数(高度),(高度)的行数,列的数目(宽度),频段的数量,每个像素的位数,该文件类型的数目。此外,与一些更复杂的文件格式中,标头可包含有关下列内容的信息的使用的压缩类型和其他必要的参数来创建图像,I(R,C)。简单的文件格式是BIN和PPM文件格式。BIN格式是简单的原始图像数据(R,C)。该文件不包含报头信息,用户必须知道必要的参数大小,band数和每像素比特使用作为图像文件。
PPM格式的广泛使用,是免费提供的一组转换实用程序(bmpplus)。他们基本上都含有原始图像数据,尽可能用最简单的头。的PPM格式包括家禽副产品粉(二进制),PGM(灰度级),PPM(颜色),和PNM处理任何上述类型的。这些图像文件格式的标头包含一个神奇的数字,用于标识文件类型,图像的高度和宽度的带的数量,和最大亮度值(它决定了所需的每个频带的每个像素的比特数)。
JPEG文件交换格式(JFIF)正迅速成为一种标准,可被用在许多不同的计算机平台,用JPEG算法压缩的图像。
JFIF文件有图片(SOI)和应用程序标记,作为一个文件头开始。在万维网上被广泛使用的JPEG图像压缩,有望成为许多应用程序的标准。两种格式最初是电脑特有的,但整个行业已经成为常用的,是太阳光栅和SGI(硅图形公司)文件格式。
Sun光栅文件格式比SGI更是无处不在,但在国家的最先进的图形电脑,SGI已经成为领导者。SGI格式处理多达1600万色,支持RLE压缩。
SGI的图像标头是512字节(与大多数不使用时,大概是为将来的扩展字节),然后由图象数据。太阳光栅格式的定义,以允许任何数量的位每像素并且还支持RLE压缩和色彩的LUT。它具有一个32字节的标头,然后由图象数据
虽然隐写术是一门古老的学科,它往往被赋予了现代科学,其中两名囚犯希望通信秘密孵化逃生计划提出的囚犯的问题。所有的沟通通过舍监扔在禁闭,她应该怀疑任何秘密通信。监狱长有权检查所有犯人之间的通信交换,可以是被动或主动。被动状态时,监狱长只是考察,并确定它是否可能包含机密信息的通信。如果她怀疑包含隐藏的信息通信,消极的看守注意到的检测隐蔽通信的报道,这一些外部人士,并没有阻止它让消息。另一方面,积极的看守,将尝试改变沟通与涉嫌故意隐藏信息,以删除信息
几乎所有的数字文件格式可用于隐写术,但更适合的格式,是那些具有高的冗余度。冗余度可以被定义为提供精度远远大于所需的对象的使用和显示的一个对象,该对象的位。冗余比特的一个目的是可以很容易被检测到的变化,改变那些比特。图像和音频文件,尤其符合这一要求,同时研究还发现了其他的文件格式,可以用于信息隐藏。
隐藏文本信息是隐秘历史上最重要的方法。一个明显的方法是在每一条短信的每一个字的第n个字母隐藏着什么秘密消息。这只是因为互联网的开始和所有的不同的数字文件格式,已减少其重要性。使用数字文件的文本隐写不经常使用,因为文本文件,有一个非常小的冗余数据量。由于数字图像的扩散,特别是在互联网上,给定的图像中的数字表示存在大量的冗余比特,图象隐写术的最热门的遮蔽物。
要隐藏音频文件中的信息,类似的技术被用来为图像文件。不同的技术,独特的音频隐秘掩码,它利用了人耳的特性,无形中隐藏信息。一个微弱的,但发声,声音变得听不见另一个更响亮的声音的存在。此属性创建一个隐藏信息渠道。虽然几乎相等的图像隐写的潜力,使用图像不及尺寸较大的有意义的音频文件受欢迎。
基本上,加密技术和隐秘的目的是提供保密通信。然而,隐秘作为密码学是不一样的。加密隐藏了一个秘密消息的内容免受恶意攻击,而隐秘,甚至掩盖了存在的消息。隐写术不能与加密技术相混淆,我们改造的消息,以便使其含义晦涩拦截恶意攻击者。因此,破坏系统的定义是不同的。在密码学中,系统被打破时,攻击者可以阅读秘密信息。打破了隐写系统需要攻击者检测到已经使用的隐写,他有这个能力,能够读取嵌入的消息。
在密码学中,一个消息的结构,加扰,使其毫无意义的,难以理解的,除非所述解密密钥是可用的。它没有试图掩饰或隐藏编码的消息。基本上,加密提供的能力的方式,防止第三者从读取的人之间的信息发送。还可以提供加密验证某人或某事的身份认证。与此相反,隐写术不改变秘密消息的结构,但它不能看到一个隐藏图片中的内容。密文中的消息,例如,可能引起怀疑的收件人而隐写方法不会创建一个“看不见”的消息。换句话说,隐秘防止意外的数据存在怀疑收件人。另外,经典的隐写系统的安全性依赖于数据编码系统的保密性。一旦在编码系统是已知的,隐写系统就被击败。
这是将可能的结合的技术进行加密,使用加密消息,然后隐藏在加密的邮件中使用隐写术。由此产生的隐写图像可以传输,没有透露秘密信息。此外,即使攻击者打败隐写技术,检测从目标消息,他仍然需要加密解码破译加密的消息。
敏感信息的保护是有效和安全的通信系统或网络存储系统的首要任务。然而,它也是重要的,任何信息的过程,以保证数据不被篡改。加密方法是一种流行的方法,以确保受保护的信息的完整性和保密性。然而,一个加密技术的关键脆弱性的保护的信息暴露。为了解决这些可靠性问题,尤其是信息量大的项目,如秘密图像(卫星照片或医疗图像),图像秘密共享方案(SSS)是一个很好的替代解决这些漏洞的类型。
假设银行的金库必须每天开放。尽管银行雇用三名高级出纳员,管理层并不想委托任何个人相结合。因此,银行管理层希望三名高级出纳员需要任意两个的储藏库访问系统。这个问题是可以解决的,使用秘密共享方案称为两外的三道坎计划。
秘密共享方案是一个智力的候选人,以确保秘密如加密密钥通过互联网传输。有许多应用领域需要共享秘密。这些应用领域中的某些部分如下：
1.公钥密码的密钥托管。
2.撤销匿名电子货币。
3.关键业务的授权
有很多标准进行分类秘密共享方案。在这些标准是基于不同的秘密,回收过程中,回收的秘密的精度和质量。这种分类可以根据：
1.揭秘型号
在此分类中,有两种类型的秘密共享方案：旧的传统的秘密共享：在这里,这个秘密只能代表数量。复苏的秘密涉及计算。自1979年发明以来,秘密共享方案已经得到了广泛的应用。特别是,大量的工作是秘密的大小相对于股份上完成所需要的长度。,众所周知一个秘密共享的基本事实是秘密本身的大小,大部分工作调查可以达到或不同种方案必须超过下限。有股秘密的大小是不是一个严重的问题,因为只要这些秘密很短,如短的密钥,作为最传统的应用需要。但是,这种影响参与者之间的分布式环境的信息复制是非常节省空间,沟通效率高,如果这个秘密是一个大型的机密文件,长的要发送的消息不可靠的链接,或秘密数据的基础上,由几台服务器共享。像这样的应用程序变得越来越有必要。
秘密共享方案：秘密代表图像。该计划的第一次是1994年引进。
2.恢复图像质量恢复的秘密图像的精度和质量视觉秘密共享方案进行分类,可分为两类：
无损可视秘密共享方案：必须从合格的一套股份恢复图像的原始秘密图像相同。
有损视觉秘密共享方案：有关计划试图消除图像潜移默化信息,并尽量减少带宽和存储空间的大小
3.解码股份的计算能力
根据这一标准,一般视觉秘密计划下降主要分为三类：
(1)视觉密码(基于VC++)视觉秘密共享方案：秘密图像共享,称为视觉密码的秘密图像恢复过程不需要计算。
(2)延伸视觉密码解码采用较低的计算操作(例如,逻辑AND, OR,XOR)的Variant视觉式秘密分享(基于VVSS):恢复的秘密图像质量得到显着改善。
(3)插值方法(基于IM)计划：秘密共享计划,在这个类别的编码和解码图像使用的计算能力(与上述两类相比)信息隐藏主要是用在以下应用领域：
在商业世界中,隐写术可以用来隐藏一个秘密化学公式或一个新发明的计划。隐写术也可用于非商业部门,以保持数字信息保护秘密数据隐藏和版权保护的目的,如一些私人。它可用于数据验证,确保验证的数据可用性学术使用,监测数据的盗版,电子数据／内容,所有权识别标签,提供机密性和完整性增强控制的电子数据盗版等不显眼的通信需要由军方和情报机构.
即使内容是加密的,现代战场上的信号检测可能迅速导致求救人的攻击。出于这个原因,军事通信的使用技术,如扩频调制或流星散射传输信号不易于敌人侦测到。
于犯罪分子也很有价值,他们的首选技术为隐蔽通信,包括预付费移动电话和公司开关板,通过它可以拨打和接听电话。但有一个副作用,执法和反情报机构有机会了解这些技术和他们的弱点,从而检测和跟踪隐藏消息。
信息隐藏技术,也强调许多“多级安全”的军事组织所使用的系统的攻击。病毒或其他恶意代码传播自身,从“安全性低”到“安全性高”的水平,然后在操作系统中使用一个隐蔽通道的信号数据向下或直接的数据可能被解密隐藏信息。
信息隐藏技术也可以用在必需的情况下,似是而非的。似是而非的动机明显是从事某种非法的活动,而当通信双方,他们希望避免被抓,但更合理的动机包括公平的投票权,个人隐私,或限制责任。
匿名通信,包括匿名邮件转发器和Web代理,都必须由合法用户,私下在网上选举投票,使政治主张,消耗性材料,保护网上言论自由,或使用数字现金。但是,相同的技术可能会被滥用,诽谤,勒索,或不请自来的商业邮件。在信息隐藏游戏的玩家的伦理立场也不是很清楚,因此,提供这类设施的设计技术可能被滥用,这是明显需要仔细思考的。
医疗保健行业,尤其是医疗成像系统,可能会受益于信息隐藏技术。他们使用的标准,如DICOM(在医学数字成像和通信),分离从字幕的图像数据,如病人姓名,日期,和医生姓名。有时图像和患者之间的链路丢失,因此,嵌入在图像中的患者的名字可能是一个有用的安全措施。另一个新兴技术相关的医疗保健行业的DNA序列中隐藏消息。这可以用来保护知识产权的医学,分子生物学或遗传学。在多媒体应用程序的上下文中,已经提出了一些其他应用程序的信息隐藏。在许多情况下,他们可以使用已开发的技术版权直接打标,在其他国家,他们可以使用调整计划或有趣的光棚上的技术问题。信息隐藏的应用包括受版权保护的材料上自动监控网络,自动无线电传输,数据增强,防篡改的审计
互联网中有大量图像可以用于隐藏信息。好的信息隐藏算法具有较高的不易察觉性和信息隐藏量,较好的对于图像修改(图像压缩等)的鲁棒性。在图像中隐藏信息可能会有损图像质量。然而,用合适的技术能够增加信息隐藏量而不会对图像内容造成明显的损害。本文主要研究了图像信息隐藏、估计隐藏量和可视密码共享方法。本文的主要贡献如下：
第一,为了提高信息安全,我们提出一种新的有效的可视密码共享方法(VSS)。这种方法基于伪随机数发生器(PRNG)。PRNG需要很长时间来确定不重复的模式,能够满足随机性的已知条件。我们设计的随机数发生器具有的新特性包括应用了可变交叉、除非线性函数之外的线性反馈移位寄存器。本方法的目标是高准确度(即任何被禁用的子集都不包含共享秘密信息)。在我们的系统中,所有的共享信息都不会泄露任何关于密码图像的信息。本文方法能够达到最优像素扩展度,这将大大缩减存储共享信息的空间,提高数字信息传输的速度。可视密码共享方法主要应用于无线数字网络。由于共享数据很小所以能够节省存储空间提高传输速度。
第二,提出了一种图像加密算法。这种算法通过改变DCT系数在频率域隐藏信息并增加信息隐藏量。用DCT变换把源图像块从空间域变换到频率域用Huffman编码对秘密图像进行编码,然后把它嵌入到频率域,用四层存储过程增加秘密图像的安全度。LSB嵌入机制能够能够较好地避开HVS检测；然而,它的鲁棒性不高。我们在频率域用(Consistent Bit Length)嵌入机制可以增加嵌入信息量而不影响安全度和源图像的质量.关于信息隐藏的基本问题：由于感知源是静态的,各个区域的可嵌入的信息量也不同。均匀的信息嵌入量对于高信息嵌入量是不利的。这种给图像嵌入等量信息的方法不仅浪费高隐藏区域的隐藏空间而且使低隐藏区产生明显的修改痕迹。本文的方法通过在源图像的DCT系数嵌入不固定的荷载比特位来最大化信息隐藏量。
最后,我们估计了估计了图像空间域最大水印荷载量估计了荷载量与嵌入强度、图像大小、图像精细度、视觉敏感度等因素的关系。这将有利于选择合适的源图像和秘密图像的嵌入方式研究了不同强度情况下的最大荷载量并用实验进行验证。这项工作的目标是为信息隐藏工作提供荷载量参考。我们研究了与最大荷载量相关的因素,除了嵌入强度之外还有图像大小、图像精细度、视觉敏感度等。
本文改进了现有信息隐藏技术,这将提高很多实际系统的性能。
Internet and wireless networks offer ubiquitous channels to deliver and to exchange information. Since the rise of the Internet, one of the most important factors of information technology and communication has been the security of information. The applications of information hiding are used by military and intelligence agencies, illicit and criminal activities, and healthcare and by other parties where data security is important. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. Imperceptibility, robustness against moderate processing such as image compression, and capacity (the amount of data that can be hidden inside the image) are the basic but rather conflicting requirements for many data hiding applications. Hiding information inside the image may damage the image quality; however, using appropriate techniques may increase the embedding capacity without noticeable damage to the image content.
The ideas of information hiding can be traced back to a few thousand years ago. Simply obscuring the content of messages by encryption is not always adequate in practice. In many rivalry environments, concealing the existence of communication is desirable to avoid suspicion from adversaries. The word "steganography", which originated from Greek and is still in use today, literally means "covered writing". Many stories of covert communications have been passed for generations, but they were mainly used by military and intelligence agencies. Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is to always conceal the very existence of the embedded data.
Rather than playing with the terminologies, this thesis uses the three terms Cryptography, Steganography and Watermarking. The embedded data, usually called watermark(s), can be used for various purposes, each of which is associated with different robustness, security, and embedding capacity requirements. The principal advantage of data hiding versus other solutions is its ability to associate secondary data with the primary media in a seamless way. As we shall see later in this thesis, the seamless association is desirable in many applications. For example, compared with cryptographic encryptions, the embedded watermarks can travel with the host media and assume their protection functions even after decryption. With the only exception of visible watermarks, the secondary data are expected to be imperceptible.
Three techniques are interlinked; steganography, watermarking and cryptography, under the term of information hiding. The standard and concept of "What You See Is What You Get(WYSIWYG)", which we encounter sometimes while printing images or other materials, is no longer precise and would not fool a steganographer as it does not always hold true. Images can be more than what we see with our Human Visual System (HVS); hence, they can convey more than merely1000words. Intuitively, this work makes use of some terms commonly used by steganography and watermarking communities. The term "cover image" will be used throughout this dissertation to describe the image designated to carry the embedded bits. The image with embedded data, called herein payload, is known as a "stegoimage". Further "steganalysis" or "attacks" refer to different image processing and statistical analysis approaches that aim to break or attack steganography algorithms.
From this brief overview the reader may have already noticed another fundamental difference between steganography and watermarking. The information hidden by a Watermarking system is always associated to the digital object to be protected or to its owner while steganographic systems just hide any information. The "robustness" criteria are also different, since steganography is mainly concerned with detection of the hidden message while watermarking concerns potential removal by a pirate. Finally, steganographic communications are usually point-to-point (between sender and receiver) while watermarking techniques are usually one-to-many.
There are many ways to categorize data hiding techniques. A straightforward classification is according to the type of primary multimedia sources, giving us data hiding systems for perceptual and non-perceptual sources. This thesis is concerned with perceptual sources, including, binary image, and color or grayscale image. Among digital sources, the major difference between perceptual and non-perceptual data is that the non-perceptual data, like text and executable codes, usually requires lossless processing, transmission and storage. Flipping a single bit may lead to different meaning. Perceptual data, however, has a perceptual tolerance range, which allows minor change before being noticed by humans. This perceptual property enables controllable amount of perceptual degradation.
In terms of perceptibility, data hiding techniques can be classified into two groups; perceptible and imperceptible hiding. Perceptible watermarks are mainly used in image and video. A visually meaningful pattern, such as a logo, is overlaid on an image or video, which is essentially an image editing or synthesis problem. The visible watermarks explicitly exhibit the copyright, ownership information, or access control policies so as to discourage the misuse of the watermarked images
Semitransparent logos are commonly added to TV programs by broadcasting networks and to the preview images accessible via World Wide Web by copyright holders. The majority of current data hiding research concerns with imperceptible watermarking. As we mentioned earlier, perceptual models need to be explored to ensure the changes imposed by an embedding system are imperceptible to retain the perceptual quality and value of the multimedia sources.
Application domain is another criterion to categorize data hiding techniques. Classic applications include ownership protection, authentication, fingerprinting, copy/access control, and annotation. We shall briefly explain the design requirement of each application:
1. Ownership Protection:a watermark indicating ownership is embedded in the multimedia source. The watermark, known only to the copyright holder, is expected to survive common processing and intentional attack so that the owner can show the presence of this watermark in case of dispute to demonstrate his/her ownership. The detection should have as little ambiguity and false alarm as possible. The total embedding capacity, namely, the number of bits that can be embedded and extracted with small probability of error does not have to be high in most scenarios.
2. Authentication or Tampering Detection:a set of secondary data is embedded in the multimedia source beforehand, and later is used to determine whether the host media is tampered or not. The robustness against removing the watermark or making it undetectable is not a concern as there is no such incentive from the attacker's point of view. However, forging a valid authentication watermark in an unauthorized or tampered media source must be prevented. In practical applications, it is also desirable to locate the tampering, and to distinguish some changes (such as the non-content change incurred by moderate lossy compression) from some other changes (such as content tampering). The embedding capacity has to be high in general to accommodate these needs. The detection should be performed without the original unwatermarked copy because either this original is unavailable or its integrity has not been established yet. This kind of detection is usually called non-coherent detection or blind detection.
3. Fingerprinting or labeling:the watermark in this application is used to trace the originator or recipients of a particular copy of multimedia source. For example, different watermarks are embedded in different copies of multimedia sources before distributing to a number of recipients. The robustness against obliterating and the ability to convey a non-trivial number of bits are required.
4. Copy Control&Access Control:the embedded watermark in this case represents certain copy control or access control policy. A watermark detector is usually integrated in a recording/playback system, like the proposed DVD copy control and the on-going SDMI activities. Upon detection, the policy is enforced by directing certain hardware or software actions such as enabling or disabling a recording module. The robustness against removal, the ability of blind detection, and the capability of conveying a non-trivial number of bits are required.
5. Annotation:the embedded watermark in this application is expected to convey as many bits as possible without the use of original unmarked copy in detection. While the robustness against intentional attack is not required, a certain degree of robustness against common processing, like lossy compression, may be desired.
Visual cryptography is a method of sharing a secret image among a group of participants, where certain group of participants are defined as qualified and may combine their shares of the secret image to obtain the original secret image, but certain other groups are defined as forbidden, even if they combine knowledge about their parts of secret image, they cannot obtain any information on the original secret image. The image is composed of black and white pixels. Pixel is the term most widely used to denote the elements of a digital image. To encode the secret image, each pixel is divided into m sub-pixels, some of which are black and some of which are white. These sub-pixels are so small that the eye averages them to some shade of grey and that is called spatial frequency resolution. Each participant's share of the image (transparency) looks as a random distribution of black and white pixels. To combine shares, participants simply stack their transparencies. The parameter m is called the pixel expansion, making this parameter small means saving storage space and reduction in the transmission time.
Visual cryptography is interesting because decryption requires no computation, but instead is done by the human visual system. The image is reconstructed by combining shares of a qualified group of participants and is not identical to the secret image. The pixels of the secret image that were white are a lighter shade of grey than the pixels of the image that were black, and the difference in the darkness of the black and white pixels is a parameter called contrast. Ideally, highest contrast gives better results in term of ease of differentiation the black and white areas.
The security of the sharing scheme depends on the information that can be obtained about the secret image from each single share or from any forbidden set of participant's shares. This involves how far the sub pixels are randomly distributed in each share and in the resulting image of combined forbidden shares.
Imperceptibility, robustness against moderate processing such as compression, and capacity (the ability to hide many bits) are the basic but rather conflicting requirements for many data hiding applications. In addition, a few other important problems encountered in practice, such as the uneven embedding capacity for image and the perceptual models for binary images, have received little attention in literature. The visual requirements model, which is called magic triangle. The first requirement, called capacity or also embedding payload, is determined by the number of secret bits embedded in each cover pixel. A higher capacity allows much more secret data to be inserted into the cover image. The second requirement, named imperceptibility, is usually calculated by peak signal-to-noise ratio (PSNR). When the difference between the cover image and the stegoimage is small, the PSNR value is high. Thus, the stegoimage quality is considered to be good when the imperceptibility is high. The last requirement is called robustness, which prevents the secret data from being attacked or stolen from the image. However, only the complex part of the image holds added information. There are many reasons to hide data but they all boil down to the desire to prevent unauthorized persons from becoming aware of the existence of a message.
The many advantages of digital information have generated new challenges and new opportunities for innovation. Internet offers ubiquitous channels to deliver and to exchange information. The security and fair use of the multimedia data, as well as the fast delivery of multimedia content to a variety of end users/devices with guaranteed quantity and security are important yet challenging topics. The solutions to these problems will not only contribute to our understanding of this fast moving complex technology, but also offer new economic opportunities to be explored. With the advent of the Internet and the widespread use of digital media, information hiding has become especially important to people interested in either communicating secretly or protecting their digital works from unauthorized copying. Information hiding comprises such diverse topics as steganography, anonymity, cover channels and copyright marking. Most of these topics have a long history and have found their way into everyday life and the popular culture. Many techniques have been proposed for a variety of applications. Data hiding is also found useful as a general tool to send side information in multimedia communications for achieving additional functionalities or enhancing performance.
There are several reasons for limiting survey of information hiding to images only. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. They come in many formats, although JPEG and GIF are most dominant.(Conversely, audio files are usually in the MPEG3format and videos are in either MPEG1or MPEG2formats.). Finally, most image files are quite large and have a lot of capacity for modification without noticeable damage to the image content.
Types of image data are divided into two primary categories:bitmap and vector. Bitmap images (also called raster images) can be presented by image model I(r,c), each pixel data has a corresponding brightness value stored in some file format. Vector images refer to methods of representing lines, curves, and shapes by storing only the key points (This is mainly used with computer graphic rather than natural images). These key points are sufficient to define the shapes, and the process of turning these into an image is called rendering. After the image has been rendered, it can be thought of as being in bitmap format where each pixel has specific values associated with it.
Some of the bitmap images are compressed, so that the I(r, c) values are not directly available until the file is decompressed. In general, these types of images contain both header information and the raw pixel data. The header must contain information regarding to the number of rows (height), the number of rows (height), the number of columns (width), the number of bands, the number of bits per pixel, the file type. Additionally, with some of the more complex file formats, the header may contain information about the type of compression used and other necessary parameters to create the images, I(r, c).
The simplest file formats are the BIN and the PPM file formats. The BIN format is simply the raw image data I(r, c). This file contains no header information; the user must know the necessary parameters-size, number of bands, and bits per pixel-to use the file as image. The PPM formats are widely used, and a set of conversion utilities is freely available (bmpplus). They basically contain raw image data with the simplest header possible. The PPM format includes PBM (binary), PGM (gray-scale), PPM (color), and PNM (handles any of the previous types). The headers for these image file formats contain a magic number that identifies the file type, the image height and width, the number of bands, and the maximum brightness value (which determines the required number of bits per pixel for each band).
JPEG File Interchange Format (JFIF) is rapidly becoming a standard that allows images compressed with the JPEG algorithm to be used in many different computer platforms. The JFIF files have a Start of Image (SOI) and an application marker that serve as a file header. JPEG image compression is being used extensively on the WWW and is expected to become the standard for many applications.
Two formats that were initially computer specific, but have become commonly used throughout the industry, are the Sun Raster and the SGI (Silicon Graphic, Inc.) file formats. The Sun Raster file format is much more ubiquitous than the SGI, but SGI has become the leader in state-of-the-art graphics computers. The SGI format handles up to16million colors and supports RLE compression. The SGI image header is512byte (with the majority of the bytes not used, presumably for future extensions) followed by the image data. The Sun Raster format is defined to allow for any number of bits per pixel and also support RLE compression and color LUTs. It has a32-byte header, followed by the image data
Although steganography is an ancient subject, the modern formulation of it is often given in terms of the prisoner's problem proposed by Simmon, where two inmates wish to communicate in secret to hatch an escape plan. All of their communication passes through a warden who will throw them in solitary confinement should she suspect any covert communication.
The warden, who is free to examine all communication exchanged between the inmates, can either be passive or active. A passive warden simply examines the communication to try and determine if it potentially contains secret information. If she suspects a communication to contain hidden information, a passive warden takes note of the detected covert communication, reports this to some outside party and lets the message through without blocking it. An active warden, on the other hand, will try to alter the communication with the suspected hidden information deliberately, in order to remove the information.
Almost all digital file formats can be used for steganography, but the formats that are more suitable are those with a high degree of redundancy. Redundancy can be defined as the bits of an object that provide accuracy far greater than necessary for the object's use and display. The redundant bits of an object are those bits that can be altered without the alteration being detected easily. Image and audio files especially comply with this requirement, while research has also uncovered other file formats that can be used for information hiding.
Hiding information in text is historically the most important method of steganography. An obvious method was to hide a secret message in every nth letter of every word of a text message. It is only since the beginning of the Internet and all the different digital file formats that is has decreased in importance. Text steganography using digital files is not used very often since text files have a very small amount of redundant data. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography.
To hide information in audio files similar techniques are used as for image files. One different technique unique to audio steganography is masking, which exploits the properties of the human ear to hide information unnoticeably. A faint, but audible, sound becomes inaudible in the presence of another louder audible sound. This property creates a channel in which to hide information. Although nearly equal to images in steganographic potential, the larger size of meaningful audio files makes them less popular to use than images.
Basically, the purpose of cryptography and steganography is to provide secret communication. However, steganography is not the same as cryptography. Cryptography hides the contents of a secret message from malicious people, whereas steganography even conceals the existence of the message. Steganography must not be confused with cryptography, where we transform the message so as to make it meaning obscure to a malicious people who intercept it. Therefore, the definition of breaking the system is different. In cryptography, the system is broken when the attacker can read the secret message. Breaking a steganographic system needs the attacker to detect that steganography that has been used and he has the ability to be able to read the embedded message.
In cryptography, the structure of a message is scrambled to make it meaningless and unintelligible unless the decryption key is available. It makes no attempt to disguise or hide the encoded message. Basically, cryptography offers the ability of transmitting information between persons in a way that prevents a third party from reading it. Cryptography can also provide authentication for verifying the identity of someone or something. In contrast, steganography does not alter the structure of the secret message, but hides it inside a coverimage so it cannot be seen. A message in cipher text, for instance, might arouse suspicion on the part of the recipient while an "invisible" message created with steganographic methods will not. In other word, steganography prevents an unintended recipient from suspecting that the data exists. In addition, the security of classical steganography system relies on secrecy of the data encoding system. Once the encoding system is known, the steganography system is defeated.
It is possible to combine the techniques by encrypting message using cryptography and then hiding the encrypted message using steganography. The resulting stegoimage can be transmitted without revealing that secret information is being exchanged. Furthermore, even if an attacker was to defeat the steganographic technique and detect the message from the stegoobject, he would still require the cryptographic decoding key to decipher the encrypted message.
An effective and secure protection of sensitive information is the primary concern in communication systems or network storage systems. Nevertheless, it is also important for any information process to ensure data is not being tampered with. Encryption methods are one of the popular approaches to ensure the integrity and confidentiality of the protected information. However, one of the critical vulnerabilities of encryption techniques is protecting the information from being exposed. To address these reliability problems, especially for large information content items such as secret images (satellite photos or medical images), an image secret sharing schemes (SSS) is a good alternative to remedy these types of vulnerabilities
Suppose a bank vault must be opened every day. Although the bank employs three senior tellers, management does not want to entrust any individual with the combination. Hence, bank management would like a vault-access system that requires any two of the three senior tellers. This problem can be solved using a secret sharing scheme called two-out-of-three threshold scheme.
A secret sharing scheme is an intellectual candidate for ensuring secrets as cryptographic keys transmit via internet. There are many application areas where secrets need to be shared. Some of these application areas are the following:
1. Key escrow in public key cryptosystems.
2. Revocable anonymity in electronic money.
3. Authorization for critical operations, i.e. missile launches, etc.
There are many criteria to classify secret sharing schemes. These criteria are based on the type of the secret, process of recovery, and the accuracy and quality of the recovered secret. This classification can be based on:
1. Secret Type.
In this classification, there are two types of secret sharing schemes: The old traditional secret sharing:Here, the secret can only represent number. The recovery of the secret involves computations. Since the invention in1979, secret sharing schemes have been extensively investigated. In particular, much work was done on the required length of the shares relative to the secret size. It is a well known basic fact that shares of a secret have to be at least of the size of the secret itself, and most of the work on share sizes investigates when this lower bound can be achieved or must be exceeded for different kinds of schemes. Having shares of the size of the secret is not a serious problem as long as these secrets are short, e.g. short secret key, as most traditional applications require. However, this effect of information replication among the participants of a distributed environment can be very space and communication inefficient if the secret is a large confidential file, a long message to be transmitted over unreliable links, or a secret data base shared by several servers. Applications like these are becoming more and more necessary. Visual Secret Sharing schemes:The secret represents image. The first time for such scheme was introduced1994.
2. The Quality of Recovered Image
The accuracy and the quality of the recovered secret image classify v secret sharing schemes into two categories:
Lossless visual secret sharing schemes:The recovered image from qualified set of shares must be identical to the original secret image.
Lossy visual secret sharing schemes:The schemes attempt to eliminate imperceptibly information of image and minimize the size in bandwidth and storage space
3. The computational Power for Decoding Shares
According to this criteria, generally visual secret scheme fall into three main categories:
(1) Visual cryptography (VC-based) visual secret sharing schemes: Secret image sharing called visual cryptography where the recovery process of the secret image requires no computations.
(2) Variant Visual Secret Sharing (VVSS-based):Quality of the recovered secret image improves dramatically by extending visual cryptography to adopt low computation operations (e.g., logical AND, OR and XOR) in decoding.
(1) Interpolation method (IM-based) schemes:Secret sharing schemes in this category encode and decode image using the most computational power (compared with the above two categories).
Information hiding is mostly used in different application areas like, the business world, Steganography can be used to hide a secret chemical formula or plans for a new invention. Steganography can also be used in the non-commercial sector to keep private digital information protected for a number of purposes such as secret data hiding and copyright protection. It can be used for Data authentication, ensuring authenticated data availability for academic usage, monitoring of data piracy, labeling electronic data/contents, ownership identification, providing confidentiality and integrity enhancement control of electronic data piracy etc.
Unobtrusive communications are required by military and intelligence agencies:even if the content is encrypted, the detection of a signal on a modern battlefield may lead rapidly to an attack on the signaler. For this reason, military communications use techniques such as spread spectrum modulation or meteor scatter transmission to make signals hard for the enemy to detect or jam.
Criminals also place great value on unobtrusive communications and their preferred technologies include prepaid mobile phones and hacked corporate Switch boards through which calls can be rerouted. As a side effect, law enforcement and counter intelligence agencies are interested in understanding these technologies and their weaknesses, so as to detect and trace hidden messages.
Information hiding techniques also underlie many attacks on "multilevel secure" systems used by military organizations. A virus or other malicious code propagates itself from "low security" to "high security" levels and then signals data downwards using a covert channel in the operating system or by hiding information directly in data that may be declassified.
hiding techniques can also be used in situations where plausible deniability is required. The obvious motivation for plausible deniability is when the two communicating parties are engaged in an activity which is somehow illicit, and they wish to avoid being caught but more legitimate motives include fair voting, personal privacy, or limitation of liability.
Anonymous communications, including anonymous remailers and Web proxies, are required by legitimate users to vote privately in online elections, make political claims, consume sexual material, preserve online free speech, or to use digital cash. But the same techniques can be abused for defamation, blackmail, or unsolicited commercial mailing. The ethical positions of the players in the information hiding game are not very clear; therefore, the design of techniques providing such facilities requires careful thought about the possible abuses, which might be non-obvious.
The healthcare industry, and especially medical imaging systems, may benefit from information hiding techniques. They use standards such as DICOM (digital imaging and communications in medicine) which separates image data from the caption, such as the name of the patient, the date, and the name of the physician. Sometimes the link between image and patient is lost, thus, embedding the name of the patient in the image could be a useful safety measure. Another emerging technique related to the healthcare industry is hiding messages in DNA sequences. This could be used to protect intellectual property in medicine, molecular biology or genetics.
A number of other applications of information hiding have been proposed in the context of multimedia applications. In many cases they can use techniques already developed for copyright marking directly; in others, they can use adapted schemes or shed interesting light on technical issues. The application of information hiding includes automatic monitoring of copyrighted material on the Web, automatic audit of radio transmissions, Data augmentation, Tamper proofing.
The purpose of this research is to investigate the image information hiding issues associated with estimating the capacity of the embedding process in addition to develop a visual secret sharing scheme. The contributions of this dissertation are described as follows:
Firstly, In order to enhance the security of the information, we proposed a novel and effective visual secret sharing scheme (VSS) based on the use of pseudo random number generator (PRNG). The PRNG has very long periods to ensure unrepeated pattern, meets the known conditions for randomness. The random generator devised here will have new features, such as, using variable permutation, and a system of linear feedback shift registers in addition to nonlinear functions. The proposed scheme is developed to be perfect (the scheme is called perfect if any non-qualified (forbidden) subset has absolutely no information about the shared secret); in our system, any share will not reveal any unintended information about the secret image. The proposed scheme is intended to achieve optimal pixel expansion, which leads to huge reduction in the space needed to store shares and improves the speed of transmission channel of digital information. The shares of the visual cryptography schemes are to be used mainly in digital networking and they are transmitted on air. As the shares become smaller they get transmitted faster and save storage media space.
Second, the basic idea is to build image a steganography technique to hide information in the frequency domain by altering the magnitude of all DCT coefficients to increase the embedding capacity. To achieve that we used Discreet Cosine transformation (DCT) to transform original image (cover image) blocks from spatial domain to frequency domain. Huffman encoding is performed on the secret image before it is embedded in the frequency domain and the four tier storage procedure is applied to increase the security of the secret image. LSB embedding mechanism is perfect in deceiving the HVS; however, it has weak resistance to attacks. We applied a Consistent Bit Length embedding mechanism in frequency domain to increase the embedding capacity w
信息隐藏的想法可以追溯到几千年前。在实践中通过简单加密使内容模糊的方法并不足够。在竞争情况下,隐藏沟通的存在是用于避免对手的嫌疑,字面意思是“隐秘”,它源于希腊和今天仍然在使用的“覆盖的写作”。隐蔽通信的许多故事已经过几代人的实践,但他们主要用于军方和情报机构。隐写术是科学,涉及通信秘密数据在适当的多媒体载体,例如,图像,音频和视频文件。假设下,如果该功能是可见的,攻击点是显而易见的,因此,这里的目标是嵌入式的数据总是以隐藏的方式存在。
不是玩用语,本文使用三个方面的加密技术,信息隐藏和数字水印。嵌入的数据,通常被称为水印(次),用途广泛,其中每一个与之不同的鲁棒性,安全性和嵌入容量要求。与其他解决方案相比,隐藏数据的主要优点是它能够以无缝的方式与主媒体辅助数据关联。稍后我们将看到在这篇论文中,无缝连接在许多应用中是可取的。例如,嵌入的水印可以与主机媒体运行,并承担其保护功能,即使在解密后,唯一的例外是二级数据预期是潜移默化的。
三种技术是相通的,隐秘,水印和加密技术,信息隐藏一词的标准和概念“所见即所得(WYSIWYG)",我们有时会遇到打印图像或其他材料的同时,不再是精确的,不会是速记式加密,因为它并不是总成立的。图像可以是更多速记式加密比我们所看到的与我们人类视觉系统(HVS),因此,他们仅仅可以传达超过1000字。直观地看,这项工作使得使用由隐秘和水印社区的常用的一些术语。在整个本文的术语“封面图像”将被用于描述指定的图像进行嵌入的位。嵌入的数据,这里称为有效载荷中的图像被称为“隐写图像”。此外“隐写”或“攻击”是指不同的图像处理和统计分析方法,旨在破坏或攻击隐写算法。
从这个简短的概述,已经可以注意到隐秘和水印的另一个根本区别。隐藏的水印系统的信息总是与被保护对象或数字,它的主人,是隐藏的隐秘系统内的任何信息。“鲁棒性”的标准也不同,因为隐秘关注的主要是检测隐藏的消息,同时关注潜在的去除水印。最后,隐蔽通信通常是点至点(在发送者和接收者之间),而数字水印技术通常是一到多。
隐藏技术,对数据进行分类的方法有很多。一个简单的分类是根据小学多媒体源的类型来划分,为我们的数据隐藏系统提供感性和非感性来源。本论文关注的是感性的来源,包括二进制图像和彩色或灰度图像。在数字信号源,非感性和感性的非数据之间的主要区别是,非感性的数据,如文本和可执行代码,通常需要无损处理,传输和存储。翻转单位,可能会导致不同的含义。感知的数据,但是,有一个感性的公差范围内,允许微小的变化,之前被人类注意到。这种感性的属性使感性降解可控量。
感知性方面,数据隐藏技术可分为两组；感知并觉察不到隐藏。可察觉的水印主要用于图像和视频。甲视觉上有意义的图案,如徽标,覆盖在图像或视频,这本质上是一个图像编辑或合成的问题。可见水印明确表现出版权,所有权信息或访问控制政策,以阻止滥用的水印图像
半透明的标志通常通过广播网络电视节目和预览图像通过万维网访问受版权持有人。当前的数据大部分研究关注隐藏与潜移默化的水印。正如我们前面提到的,感知模型需要加以探讨,以确保由一个嵌入系统强加的改变是潜移默化地保留感知质量和价值的多媒体来源。
应用程序域是另一种标准数据隐藏技术的分类。经典应用包括所有权保护,身份验证,指纹识别,复制/门禁和注释。我们将简要地解释每个应用程序的设计要求：
1.所有权保护：表示所有权水印嵌入多媒体源。水印,只有版权持有人,预计生存共同处理和故意攻击,让主人可以显示水印,存在争议的情况下,以证明他／她的所有权。检测应尽可能的不能有一点含糊和误报。总的嵌入容量,小的错误概率,可以嵌入和提取的比特数,即不具有在大多数情况下要高。
2.身份验证／篡改检测：次要数据的一组预先嵌入在多媒体源,是用来确定主机媒体是否被篡改或去除水印的鲁棒性对或使其无法察觉的是不是一个问题,从攻击者的角度来看,有没有这样的刺激。然而,必须防止在未经授权或篡改的媒体源锻造一个有效的认证水印。在实际应用中,这也是可取的定位篡改,以及其他一些变化(如内容篡改)区分的一些变化(如非内容的变化所产生的适度的有损压缩)。嵌入容量一般要高,以适应这些需求。应进行检测,没有原始水印的复制,因为这原来是不可用或尚未建立其完整性。这种检测通常被称为非相干检测或盲检测。
3.指纹或标签：在这个应用程序中的水印是用来跟踪的起源或多媒体源的特定副本收件人。例如,不同的水印嵌入多媒体来源不同的副本,然后再分发到多个接收者。稳健反对抹杀和能力传达一个不平凡的比特数是必需的。
4.复制控制和访问控制嵌入的水印在这种情况下,代表一定的的拷贝控制或访问控制策略。水印检测器通常集成在一个记录／重放系统中,像拟议的DVD拷贝控制和持续SDMI活动的。经检测,在政策执行指挥某些硬件或软件的行动中,如启用或禁用记录模块。反对拆除,盲检测的能力,有能力传达一个不平凡的比特数的鲁棒性是必需的。
5.注释：在这个应用程序中嵌入的水印预计传达尽可能不使用原始无人盯防的副本检测多达位。虽然免受蓄意攻击的鲁棒性不是必需的,对常见的处理,有一定程度的鲁棒性,可以有损压缩。
视觉密码是一种方法,在一组的参与者中,其中某些组的参与者定义为合格,并结合自己的股份,以获得原始秘密图像的秘密图像共享一个秘密图像,但其他某些群体被定义为禁地,即使他们结合知识及其零部件的秘密图像,他们无法获得任何信息的原始秘密图像。黑白像素组成的图像。像素是最广泛使用的数字图像表示元素的术语。进行编码的秘密的图像中,每个像素被分成m个子像素,其中一些是黑色的,其中有一些是白色的。这些子像素是如此之小,他们的眼睛的平均一些的灰色阴影,被称为空间频率分辨率。每个参与者的股份(透明度)的图像看起来黑色和白色像素的随机分布。参与者只需叠加透明胶片。参数m称为的像素膨胀,使得此参数小装置节省存储空间,并减少传输时间。
有趣的是,视觉密码解密,因为不需要计算,而是通过人的视觉系统。图像重建相结合,一个合格的组参与者的股份,与秘密图像是不相同的。秘密图像的像素,白色比黑色的图像的像素是一个打火机的灰色阴影,在黑暗的黑色和白色像素的差异是一个参数,称为对比度。在理想的情况下,最高的对比度在分化黑色和白色区域的术语能给出较好的结果。
共享方案的安全性依赖于信息,可以从每个单一股份或任何禁组参与者的股份中获得秘密图像。这涉及到多远的子像素随机分布在每个份额,产生的图像合并。
对温和派的处理如压缩,不可见性,鲁棒性和能力(能够隐藏多少位)是许多数据隐藏应用程序的基本而是相互冲突的要求。此外,在实践中遇到的其他一些重要问题,如图像和嵌入容量不均的二进制图像的感知模型,很少受到关注文学。视觉需求模型,被称为神奇的三角形。第一个要求,容量也嵌入的有效负载,确定嵌入在每个盖像素的比特的数量。较高的容量允许的更机密的数据被插入到封面图像。第二个要求,名为“不可感知性,通常是计算峰值信号信噪比(PSNR)。当封面图像和隐写图像之间的差异小时,PSNR值是高的。因此,隐写图像质量被认为是好的时,不可见性高。至目前为止,要求被称为鲁棒性,从而防止从图像中被攻击或被盗的秘密数据。然而,只有持有添加复杂的图像的一部分的信息。原因有很多隐藏的数据,但他们都归结为防止未经授权的人员存在知悉消息的欲望。
数字信息的许多优点,产生了新的挑战和新的机遇创新。互联网提供无处不在的提供和交换信息的渠道。多媒体数据,以及快速传送多媒体内容的各种最终用户／设备数量和安全保证使用的安全性和公平是重要而又具有挑战性的课题。这些问题的解决方案将不仅有助于我们了解这个快速移动的复杂的技术,而且还提供了探索的新的经济机会。随着互联网和数字媒体的广泛使用,已经成为信息隐藏通信秘密或未经授权的复制保护他人的数字作品感兴趣的人尤其重要。信息隐藏包括隐秘,不愿透露姓名的覆盖渠道和版权标记等不同的主题。这些主题大多有着悠久的历史,发现他们的方式融入日常的生活和流行文化。已经提出了许多技术的各种应用。数据隐藏也可作为一般的多媒体通信中的发送方信息的工具来实现额外的功能或提高性能。
有几个原因限制调查仅适用于图像信息隐藏。图像在互联网上广泛存在,并有提高的可能,可作为载体对象。他们有很多格式, JPEG和GIF是使用的最广泛。(反之,音频文件通常是MPEG3格式,视频是MPEG1或MPEG2格式)。最后,大多数的图像文件是相当大的,有对很多没有明显损坏的图像内容进行修改的能。
类型的图像数据被划分为两个主要的类别：位图和矢量。位图图像(也称为光栅图像),可以通过图像模型I(R,C),每个像素数据具有一些文件格式存储在一个相应的亮度值。矢量图像是指代表直线,曲线和形状的方法存储的关键点(这主要是用计算机图形,而不是自然的图像)。这些关键点是足以定义的形状,并把它们转变成一个图像,其过程被称为渲染。已经被渲染的图像之后,就可以认为是作为位图的格式,其中每个像素具有与它相关联的特定值。
部分的位图图像的压缩,这样,I(R,C)的值是不能直接使用,直到该文件被解压缩。在一般情况下,这些类型的图像包含的标题信息和原始像素数据。标头必须包含有关的行数(高度),(高度)的行数,列的数目(宽度),频段的数量,每个像素的位数,该文件类型的数目。此外,与一些更复杂的文件格式中,标头可包含有关下列内容的信息的使用的压缩类型和其他必要的参数来创建图像,I(R,C)。简单的文件格式是BIN和PPM文件格式。BIN格式是简单的原始图像数据(R,C)。该文件不包含报头信息,用户必须知道必要的参数大小,band数和每像素比特使用作为图像文件。
PPM格式的广泛使用,是免费提供的一组转换实用程序(bmpplus)。他们基本上都含有原始图像数据,尽可能用最简单的头。的PPM格式包括家禽副产品粉(二进制),PGM(灰度级),PPM(颜色),和PNM处理任何上述类型的。这些图像文件格式的标头包含一个神奇的数字,用于标识文件类型,图像的高度和宽度的带的数量,和最大亮度值(它决定了所需的每个频带的每个像素的比特数)。
JPEG文件交换格式(JFIF)正迅速成为一种标准,可被用在许多不同的计算机平台,用JPEG算法压缩的图像。
JFIF文件有图片(SOI)和应用程序标记,作为一个文件头开始。在万维网上被广泛使用的JPEG图像压缩,有望成为许多应用程序的标准。两种格式最初是电脑特有的,但整个行业已经成为常用的,是太阳光栅和SGI(硅图形公司)文件格式。
Sun光栅文件格式比SGI更是无处不在,但在国家的最先进的图形电脑,SGI已经成为领导者。SGI格式处理多达1600万色,支持RLE压缩。
SGI的图像标头是512字节(与大多数不使用时,大概是为将来的扩展字节),然后由图象数据。太阳光栅格式的定义,以允许任何数量的位每像素并且还支持RLE压缩和色彩的LUT。它具有一个32字节的标头,然后由图象数据
虽然隐写术是一门古老的学科,它往往被赋予了现代科学,其中两名囚犯希望通信秘密孵化逃生计划提出的囚犯的问题。所有的沟通通过舍监扔在禁闭,她应该怀疑任何秘密通信。监狱长有权检查所有犯人之间的通信交换,可以是被动或主动。被动状态时,监狱长只是考察,并确定它是否可能包含机密信息的通信。如果她怀疑包含隐藏的信息通信,消极的看守注意到的检测隐蔽通信的报道,这一些外部人士,并没有阻止它让消息。另一方面,积极的看守,将尝试改变沟通与涉嫌故意隐藏信息,以删除信息
几乎所有的数字文件格式可用于隐写术,但更适合的格式,是那些具有高的冗余度。冗余度可以被定义为提供精度远远大于所需的对象的使用和显示的一个对象,该对象的位。冗余比特的一个目的是可以很容易被检测到的变化,改变那些比特。图像和音频文件,尤其符合这一要求,同时研究还发现了其他的文件格式,可以用于信息隐藏。
隐藏文本信息是隐秘历史上最重要的方法。一个明显的方法是在每一条短信的每一个字的第n个字母隐藏着什么秘密消息。这只是因为互联网的开始和所有的不同的数字文件格式,已减少其重要性。使用数字文件的文本隐写不经常使用,因为文本文件,有一个非常小的冗余数据量。由于数字图像的扩散,特别是在互联网上,给定的图像中的数字表示存在大量的冗余比特,图象隐写术的最热门的遮蔽物。
要隐藏音频文件中的信息,类似的技术被用来为图像文件。不同的技术,独特的音频隐秘掩码,它利用了人耳的特性,无形中隐藏信息。一个微弱的,但发声,声音变得听不见另一个更响亮的声音的存在。此属性创建一个隐藏信息渠道。虽然几乎相等的图像隐写的潜力,使用图像不及尺寸较大的有意义的音频文件受欢迎。
基本上,加密技术和隐秘的目的是提供保密通信。然而,隐秘作为密码学是不一样的。加密隐藏了一个秘密消息的内容免受恶意攻击,而隐秘,甚至掩盖了存在的消息。隐写术不能与加密技术相混淆,我们改造的消息,以便使其含义晦涩拦截恶意攻击者。因此,破坏系统的定义是不同的。在密码学中,系统被打破时,攻击者可以阅读秘密信息。打破了隐写系统需要攻击者检测到已经使用的隐写,他有这个能力,能够读取嵌入的消息。
在密码学中,一个消息的结构,加扰,使其毫无意义的,难以理解的,除非所述解密密钥是可用的。它没有试图掩饰或隐藏编码的消息。基本上,加密提供的能力的方式,防止第三者从读取的人之间的信息发送。还可以提供加密验证某人或某事的身份认证。与此相反,隐写术不改变秘密消息的结构,但它不能看到一个隐藏图片中的内容。密文中的消息,例如,可能引起怀疑的收件人而隐写方法不会创建一个“看不见”的消息。换句话说,隐秘防止意外的数据存在怀疑收件人。另外,经典的隐写系统的安全性依赖于数据编码系统的保密性。一旦在编码系统是已知的,隐写系统就被击败。
这是将可能的结合的技术进行加密,使用加密消息,然后隐藏在加密的邮件中使用隐写术。由此产生的隐写图像可以传输,没有透露秘密信息。此外,即使攻击者打败隐写技术,检测从目标消息,他仍然需要加密解码破译加密的消息。
敏感信息的保护是有效和安全的通信系统或网络存储系统的首要任务。然而,它也是重要的,任何信息的过程,以保证数据不被篡改。加密方法是一种流行的方法,以确保受保护的信息的完整性和保密性。然而,一个加密技术的关键脆弱性的保护的信息暴露。为了解决这些可靠性问题,尤其是信息量大的项目,如秘密图像(卫星照片或医疗图像),图像秘密共享方案(SSS)是一个很好的替代解决这些漏洞的类型。
假设银行的金库必须每天开放。尽管银行雇用三名高级出纳员,管理层并不想委托任何个人相结合。因此,银行管理层希望三名高级出纳员需要任意两个的储藏库访问系统。这个问题是可以解决的,使用秘密共享方案称为两外的三道坎计划。
秘密共享方案是一个智力的候选人,以确保秘密如加密密钥通过互联网传输。有许多应用领域需要共享秘密。这些应用领域中的某些部分如下：
1.公钥密码的密钥托管。
2.撤销匿名电子货币。
3.关键业务的授权
有很多标准进行分类秘密共享方案。在这些标准是基于不同的秘密,回收过程中,回收的秘密的精度和质量。这种分类可以根据：
1.揭秘型号
在此分类中,有两种类型的秘密共享方案：旧的传统的秘密共享：在这里,这个秘密只能代表数量。复苏的秘密涉及计算。自1979年发明以来,秘密共享方案已经得到了广泛的应用。特别是,大量的工作是秘密的大小相对于股份上完成所需要的长度。,众所周知一个秘密共享的基本事实是秘密本身的大小,大部分工作调查可以达到或不同种方案必须超过下限。有股秘密的大小是不是一个严重的问题,因为只要这些秘密很短,如短的密钥,作为最传统的应用需要。但是,这种影响参与者之间的分布式环境的信息复制是非常节省空间,沟通效率高,如果这个秘密是一个大型的机密文件,长的要发送的消息不可靠的链接,或秘密数据的基础上,由几台服务器共享。像这样的应用程序变得越来越有必要。
秘密共享方案：秘密代表图像。该计划的第一次是1994年引进。
2.恢复图像质量恢复的秘密图像的精度和质量视觉秘密共享方案进行分类,可分为两类：
无损可视秘密共享方案：必须从合格的一套股份恢复图像的原始秘密图像相同。
有损视觉秘密共享方案：有关计划试图消除图像潜移默化信息,并尽量减少带宽和存储空间的大小
3.解码股份的计算能力
根据这一标准,一般视觉秘密计划下降主要分为三类：
(1)视觉密码(基于VC++)视觉秘密共享方案：秘密图像共享,称为视觉密码的秘密图像恢复过程不需要计算。
(2)延伸视觉密码解码采用较低的计算操作(例如,逻辑AND, OR,XOR)的Variant视觉式秘密分享(基于VVSS):恢复的秘密图像质量得到显着改善。
(3)插值方法(基于IM)计划：秘密共享计划,在这个类别的编码和解码图像使用的计算能力(与上述两类相比)信息隐藏主要是用在以下应用领域：
在商业世界中,隐写术可以用来隐藏一个秘密化学公式或一个新发明的计划。隐写术也可用于非商业部门,以保持数字信息保护秘密数据隐藏和版权保护的目的,如一些私人。它可用于数据验证,确保验证的数据可用性学术使用,监测数据的盗版,电子数据／内容,所有权识别标签,提供机密性和完整性增强控制的电子数据盗版等不显眼的通信需要由军方和情报机构.
即使内容是加密的,现代战场上的信号检测可能迅速导致求救人的攻击。出于这个原因,军事通信的使用技术,如扩频调制或流星散射传输信号不易于敌人侦测到。
于犯罪分子也很有价值,他们的首选技术为隐蔽通信,包括预付费移动电话和公司开关板,通过它可以拨打和接听电话。但有一个副作用,执法和反情报机构有机会了解这些技术和他们的弱点,从而检测和跟踪隐藏消息。
信息隐藏技术,也强调许多“多级安全”的军事组织所使用的系统的攻击。病毒或其他恶意代码传播自身,从“安全性低”到“安全性高”的水平,然后在操作系统中使用一个隐蔽通道的信号数据向下或直接的数据可能被解密隐藏信息。
信息隐藏技术也可以用在必需的情况下,似是而非的。似是而非的动机明显是从事某种非法的活动,而当通信双方,他们希望避免被抓,但更合理的动机包括公平的投票权,个人隐私,或限制责任。
匿名通信,包括匿名邮件转发器和Web代理,都必须由合法用户,私下在网上选举投票,使政治主张,消耗性材料,保护网上言论自由,或使用数字现金。但是,相同的技术可能会被滥用,诽谤,勒索,或不请自来的商业邮件。在信息隐藏游戏的玩家的伦理立场也不是很清楚,因此,提供这类设施的设计技术可能被滥用,这是明显需要仔细思考的。
医疗保健行业,尤其是医疗成像系统,可能会受益于信息隐藏技术。他们使用的标准,如DICOM(在医学数字成像和通信),分离从字幕的图像数据,如病人姓名,日期,和医生姓名。有时图像和患者之间的链路丢失,因此,嵌入在图像中的患者的名字可能是一个有用的安全措施。另一个新兴技术相关的医疗保健行业的DNA序列中隐藏消息。这可以用来保护知识产权的医学,分子生物学或遗传学。在多媒体应用程序的上下文中,已经提出了一些其他应用程序的信息隐藏。在许多情况下,他们可以使用已开发的技术版权直接打标,在其他国家,他们可以使用调整计划或有趣的光棚上的技术问题。信息隐藏的应用包括受版权保护的材料上自动监控网络,自动无线电传输,数据增强,防篡改的审计
互联网中有大量图像可以用于隐藏信息。好的信息隐藏算法具有较高的不易察觉性和信息隐藏量,较好的对于图像修改(图像压缩等)的鲁棒性。在图像中隐藏信息可能会有损图像质量。然而,用合适的技术能够增加信息隐藏量而不会对图像内容造成明显的损害。本文主要研究了图像信息隐藏、估计隐藏量和可视密码共享方法。本文的主要贡献如下：
第一,为了提高信息安全,我们提出一种新的有效的可视密码共享方法(VSS)。这种方法基于伪随机数发生器(PRNG)。PRNG需要很长时间来确定不重复的模式,能够满足随机性的已知条件。我们设计的随机数发生器具有的新特性包括应用了可变交叉、除非线性函数之外的线性反馈移位寄存器。本方法的目标是高准确度(即任何被禁用的子集都不包含共享秘密信息)。在我们的系统中,所有的共享信息都不会泄露任何关于密码图像的信息。本文方法能够达到最优像素扩展度,这将大大缩减存储共享信息的空间,提高数字信息传输的速度。可视密码共享方法主要应用于无线数字网络。由于共享数据很小所以能够节省存储空间提高传输速度。
第二,提出了一种图像加密算法。这种算法通过改变DCT系数在频率域隐藏信息并增加信息隐藏量。用DCT变换把源图像块从空间域变换到频率域用Huffman编码对秘密图像进行编码,然后把它嵌入到频率域,用四层存储过程增加秘密图像的安全度。LSB嵌入机制能够能够较好地避开HVS检测；然而,它的鲁棒性不高。我们在频率域用(Consistent Bit Length)嵌入机制可以增加嵌入信息量而不影响安全度和源图像的质量.关于信息隐藏的基本问题：由于感知源是静态的,各个区域的可嵌入的信息量也不同。均匀的信息嵌入量对于高信息嵌入量是不利的。这种给图像嵌入等量信息的方法不仅浪费高隐藏区域的隐藏空间而且使低隐藏区产生明显的修改痕迹。本文的方法通过在源图像的DCT系数嵌入不固定的荷载比特位来最大化信息隐藏量。
最后,我们估计了估计了图像空间域最大水印荷载量估计了荷载量与嵌入强度、图像大小、图像精细度、视觉敏感度等因素的关系。这将有利于选择合适的源图像和秘密图像的嵌入方式研究了不同强度情况下的最大荷载量并用实验进行验证。这项工作的目标是为信息隐藏工作提供荷载量参考。我们研究了与最大荷载量相关的因素,除了嵌入强度之外还有图像大小、图像精细度、视觉敏感度等。
本文改进了现有信息隐藏技术,这将提高很多实际系统的性能。
Internet and wireless networks offer ubiquitous channels to deliver and to exchange information. Since the rise of the Internet, one of the most important factors of information technology and communication has been the security of information. The applications of information hiding are used by military and intelligence agencies, illicit and criminal activities, and healthcare and by other parties where data security is important. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. Imperceptibility, robustness against moderate processing such as image compression, and capacity (the amount of data that can be hidden inside the image) are the basic but rather conflicting requirements for many data hiding applications. Hiding information inside the image may damage the image quality; however, using appropriate techniques may increase the embedding capacity without noticeable damage to the image content.
The ideas of information hiding can be traced back to a few thousand years ago. Simply obscuring the content of messages by encryption is not always adequate in practice. In many rivalry environments, concealing the existence of communication is desirable to avoid suspicion from adversaries. The word "steganography", which originated from Greek and is still in use today, literally means "covered writing". Many stories of covert communications have been passed for generations, but they were mainly used by military and intelligence agencies. Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is to always conceal the very existence of the embedded data.
Rather than playing with the terminologies, this thesis uses the three terms Cryptography, Steganography and Watermarking. The embedded data, usually called watermark(s), can be used for various purposes, each of which is associated with different robustness, security, and embedding capacity requirements. The principal advantage of data hiding versus other solutions is its ability to associate secondary data with the primary media in a seamless way. As we shall see later in this thesis, the seamless association is desirable in many applications. For example, compared with cryptographic encryptions, the embedded watermarks can travel with the host media and assume their protection functions even after decryption. With the only exception of visible watermarks, the secondary data are expected to be imperceptible.
Three techniques are interlinked; steganography, watermarking and cryptography, under the term of information hiding. The standard and concept of "What You See Is What You Get(WYSIWYG)", which we encounter sometimes while printing images or other materials, is no longer precise and would not fool a steganographer as it does not always hold true. Images can be more than what we see with our Human Visual System (HVS); hence, they can convey more than merely1000words. Intuitively, this work makes use of some terms commonly used by steganography and watermarking communities. The term "cover image" will be used throughout this dissertation to describe the image designated to carry the embedded bits. The image with embedded data, called herein payload, is known as a "stegoimage". Further "steganalysis" or "attacks" refer to different image processing and statistical analysis approaches that aim to break or attack steganography algorithms.
From this brief overview the reader may have already noticed another fundamental difference between steganography and watermarking. The information hidden by a Watermarking system is always associated to the digital object to be protected or to its owner while steganographic systems just hide any information. The "robustness" criteria are also different, since steganography is mainly concerned with detection of the hidden message while watermarking concerns potential removal by a pirate. Finally, steganographic communications are usually point-to-point (between sender and receiver) while watermarking techniques are usually one-to-many.
There are many ways to categorize data hiding techniques. A straightforward classification is according to the type of primary multimedia sources, giving us data hiding systems for perceptual and non-perceptual sources. This thesis is concerned with perceptual sources, including, binary image, and color or grayscale image. Among digital sources, the major difference between perceptual and non-perceptual data is that the non-perceptual data, like text and executable codes, usually requires lossless processing, transmission and storage. Flipping a single bit may lead to different meaning. Perceptual data, however, has a perceptual tolerance range, which allows minor change before being noticed by humans. This perceptual property enables controllable amount of perceptual degradation.
In terms of perceptibility, data hiding techniques can be classified into two groups; perceptible and imperceptible hiding. Perceptible watermarks are mainly used in image and video. A visually meaningful pattern, such as a logo, is overlaid on an image or video, which is essentially an image editing or synthesis problem. The visible watermarks explicitly exhibit the copyright, ownership information, or access control policies so as to discourage the misuse of the watermarked images
Semitransparent logos are commonly added to TV programs by broadcasting networks and to the preview images accessible via World Wide Web by copyright holders. The majority of current data hiding research concerns with imperceptible watermarking. As we mentioned earlier, perceptual models need to be explored to ensure the changes imposed by an embedding system are imperceptible to retain the perceptual quality and value of the multimedia sources.
Application domain is another criterion to categorize data hiding techniques. Classic applications include ownership protection, authentication, fingerprinting, copy/access control, and annotation. We shall briefly explain the design requirement of each application:
1. Ownership Protection:a watermark indicating ownership is embedded in the multimedia source. The watermark, known only to the copyright holder, is expected to survive common processing and intentional attack so that the owner can show the presence of this watermark in case of dispute to demonstrate his/her ownership. The detection should have as little ambiguity and false alarm as possible. The total embedding capacity, namely, the number of bits that can be embedded and extracted with small probability of error does not have to be high in most scenarios.
2. Authentication or Tampering Detection:a set of secondary data is embedded in the multimedia source beforehand, and later is used to determine whether the host media is tampered or not. The robustness against removing the watermark or making it undetectable is not a concern as there is no such incentive from the attacker's point of view. However, forging a valid authentication watermark in an unauthorized or tampered media source must be prevented. In practical applications, it is also desirable to locate the tampering, and to distinguish some changes (such as the non-content change incurred by moderate lossy compression) from some other changes (such as content tampering). The embedding capacity has to be high in general to accommodate these needs. The detection should be performed without the original unwatermarked copy because either this original is unavailable or its integrity has not been established yet. This kind of detection is usually called non-coherent detection or blind detection.
3. Fingerprinting or labeling:the watermark in this application is used to trace the originator or recipients of a particular copy of multimedia source. For example, different watermarks are embedded in different copies of multimedia sources before distributing to a number of recipients. The robustness against obliterating and the ability to convey a non-trivial number of bits are required.
4. Copy Control&Access Control:the embedded watermark in this case represents certain copy control or access control policy. A watermark detector is usually integrated in a recording/playback system, like the proposed DVD copy control and the on-going SDMI activities. Upon detection, the policy is enforced by directing certain hardware or software actions such as enabling or disabling a recording module. The robustness against removal, the ability of blind detection, and the capability of conveying a non-trivial number of bits are required.
5. Annotation:the embedded watermark in this application is expected to convey as many bits as possible without the use of original unmarked copy in detection. While the robustness against intentional attack is not required, a certain degree of robustness against common processing, like lossy compression, may be desired.
Visual cryptography is a method of sharing a secret image among a group of participants, where certain group of participants are defined as qualified and may combine their shares of the secret image to obtain the original secret image, but certain other groups are defined as forbidden, even if they combine knowledge about their parts of secret image, they cannot obtain any information on the original secret image. The image is composed of black and white pixels. Pixel is the term most widely used to denote the elements of a digital image. To encode the secret image, each pixel is divided into m sub-pixels, some of which are black and some of which are white. These sub-pixels are so small that the eye averages them to some shade of grey and that is called spatial frequency resolution. Each participant's share of the image (transparency) looks as a random distribution of black and white pixels. To combine shares, participants simply stack their transparencies. The parameter m is called the pixel expansion, making this parameter small means saving storage space and reduction in the transmission time.
Visual cryptography is interesting because decryption requires no computation, but instead is done by the human visual system. The image is reconstructed by combining shares of a qualified group of participants and is not identical to the secret image. The pixels of the secret image that were white are a lighter shade of grey than the pixels of the image that were black, and the difference in the darkness of the black and white pixels is a parameter called contrast. Ideally, highest contrast gives better results in term of ease of differentiation the black and white areas.
The security of the sharing scheme depends on the information that can be obtained about the secret image from each single share or from any forbidden set of participant's shares. This involves how far the sub pixels are randomly distributed in each share and in the resulting image of combined forbidden shares.
Imperceptibility, robustness against moderate processing such as compression, and capacity (the ability to hide many bits) are the basic but rather conflicting requirements for many data hiding applications. In addition, a few other important problems encountered in practice, such as the uneven embedding capacity for image and the perceptual models for binary images, have received little attention in literature. The visual requirements model, which is called magic triangle. The first requirement, called capacity or also embedding payload, is determined by the number of secret bits embedded in each cover pixel. A higher capacity allows much more secret data to be inserted into the cover image. The second requirement, named imperceptibility, is usually calculated by peak signal-to-noise ratio (PSNR). When the difference between the cover image and the stegoimage is small, the PSNR value is high. Thus, the stegoimage quality is considered to be good when the imperceptibility is high. The last requirement is called robustness, which prevents the secret data from being attacked or stolen from the image. However, only the complex part of the image holds added information. There are many reasons to hide data but they all boil down to the desire to prevent unauthorized persons from becoming aware of the existence of a message.
The many advantages of digital information have generated new challenges and new opportunities for innovation. Internet offers ubiquitous channels to deliver and to exchange information. The security and fair use of the multimedia data, as well as the fast delivery of multimedia content to a variety of end users/devices with guaranteed quantity and security are important yet challenging topics. The solutions to these problems will not only contribute to our understanding of this fast moving complex technology, but also offer new economic opportunities to be explored. With the advent of the Internet and the widespread use of digital media, information hiding has become especially important to people interested in either communicating secretly or protecting their digital works from unauthorized copying. Information hiding comprises such diverse topics as steganography, anonymity, cover channels and copyright marking. Most of these topics have a long history and have found their way into everyday life and the popular culture. Many techniques have been proposed for a variety of applications. Data hiding is also found useful as a general tool to send side information in multimedia communications for achieving additional functionalities or enhancing performance.
There are several reasons for limiting survey of information hiding to images only. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. They come in many formats, although JPEG and GIF are most dominant.(Conversely, audio files are usually in the MPEG3format and videos are in either MPEG1or MPEG2formats.). Finally, most image files are quite large and have a lot of capacity for modification without noticeable damage to the image content.
Types of image data are divided into two primary categories:bitmap and vector. Bitmap images (also called raster images) can be presented by image model I(r,c), each pixel data has a corresponding brightness value stored in some file format. Vector images refer to methods of representing lines, curves, and shapes by storing only the key points (This is mainly used with computer graphic rather than natural images). These key points are sufficient to define the shapes, and the process of turning these into an image is called rendering. After the image has been rendered, it can be thought of as being in bitmap format where each pixel has specific values associated with it.
Some of the bitmap images are compressed, so that the I(r, c) values are not directly available until the file is decompressed. In general, these types of images contain both header information and the raw pixel data. The header must contain information regarding to the number of rows (height), the number of rows (height), the number of columns (width), the number of bands, the number of bits per pixel, the file type. Additionally, with some of the more complex file formats, the header may contain information about the type of compression used and other necessary parameters to create the images, I(r, c).
The simplest file formats are the BIN and the PPM file formats. The BIN format is simply the raw image data I(r, c). This file contains no header information; the user must know the necessary parameters-size, number of bands, and bits per pixel-to use the file as image. The PPM formats are widely used, and a set of conversion utilities is freely available (bmpplus). They basically contain raw image data with the simplest header possible. The PPM format includes PBM (binary), PGM (gray-scale), PPM (color), and PNM (handles any of the previous types). The headers for these image file formats contain a magic number that identifies the file type, the image height and width, the number of bands, and the maximum brightness value (which determines the required number of bits per pixel for each band).
JPEG File Interchange Format (JFIF) is rapidly becoming a standard that allows images compressed with the JPEG algorithm to be used in many different computer platforms. The JFIF files have a Start of Image (SOI) and an application marker that serve as a file header. JPEG image compression is being used extensively on the WWW and is expected to become the standard for many applications.
Two formats that were initially computer specific, but have become commonly used throughout the industry, are the Sun Raster and the SGI (Silicon Graphic, Inc.) file formats. The Sun Raster file format is much more ubiquitous than the SGI, but SGI has become the leader in state-of-the-art graphics computers. The SGI format handles up to16million colors and supports RLE compression. The SGI image header is512byte (with the majority of the bytes not used, presumably for future extensions) followed by the image data. The Sun Raster format is defined to allow for any number of bits per pixel and also support RLE compression and color LUTs. It has a32-byte header, followed by the image data
Although steganography is an ancient subject, the modern formulation of it is often given in terms of the prisoner's problem proposed by Simmon, where two inmates wish to communicate in secret to hatch an escape plan. All of their communication passes through a warden who will throw them in solitary confinement should she suspect any covert communication.
The warden, who is free to examine all communication exchanged between the inmates, can either be passive or active. A passive warden simply examines the communication to try and determine if it potentially contains secret information. If she suspects a communication to contain hidden information, a passive warden takes note of the detected covert communication, reports this to some outside party and lets the message through without blocking it. An active warden, on the other hand, will try to alter the communication with the suspected hidden information deliberately, in order to remove the information.
Almost all digital file formats can be used for steganography, but the formats that are more suitable are those with a high degree of redundancy. Redundancy can be defined as the bits of an object that provide accuracy far greater than necessary for the object's use and display. The redundant bits of an object are those bits that can be altered without the alteration being detected easily. Image and audio files especially comply with this requirement, while research has also uncovered other file formats that can be used for information hiding.
Hiding information in text is historically the most important method of steganography. An obvious method was to hide a secret message in every nth letter of every word of a text message. It is only since the beginning of the Internet and all the different digital file formats that is has decreased in importance. Text steganography using digital files is not used very often since text files have a very small amount of redundant data. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography.
To hide information in audio files similar techniques are used as for image files. One different technique unique to audio steganography is masking, which exploits the properties of the human ear to hide information unnoticeably. A faint, but audible, sound becomes inaudible in the presence of another louder audible sound. This property creates a channel in which to hide information. Although nearly equal to images in steganographic potential, the larger size of meaningful audio files makes them less popular to use than images.
Basically, the purpose of cryptography and steganography is to provide secret communication. However, steganography is not the same as cryptography. Cryptography hides the contents of a secret message from malicious people, whereas steganography even conceals the existence of the message. Steganography must not be confused with cryptography, where we transform the message so as to make it meaning obscure to a malicious people who intercept it. Therefore, the definition of breaking the system is different. In cryptography, the system is broken when the attacker can read the secret message. Breaking a steganographic system needs the attacker to detect that steganography that has been used and he has the ability to be able to read the embedded message.
In cryptography, the structure of a message is scrambled to make it meaningless and unintelligible unless the decryption key is available. It makes no attempt to disguise or hide the encoded message. Basically, cryptography offers the ability of transmitting information between persons in a way that prevents a third party from reading it. Cryptography can also provide authentication for verifying the identity of someone or something. In contrast, steganography does not alter the structure of the secret message, but hides it inside a coverimage so it cannot be seen. A message in cipher text, for instance, might arouse suspicion on the part of the recipient while an "invisible" message created with steganographic methods will not. In other word, steganography prevents an unintended recipient from suspecting that the data exists. In addition, the security of classical steganography system relies on secrecy of the data encoding system. Once the encoding system is known, the steganography system is defeated.
It is possible to combine the techniques by encrypting message using cryptography and then hiding the encrypted message using steganography. The resulting stegoimage can be transmitted without revealing that secret information is being exchanged. Furthermore, even if an attacker was to defeat the steganographic technique and detect the message from the stegoobject, he would still require the cryptographic decoding key to decipher the encrypted message.
An effective and secure protection of sensitive information is the primary concern in communication systems or network storage systems. Nevertheless, it is also important for any information process to ensure data is not being tampered with. Encryption methods are one of the popular approaches to ensure the integrity and confidentiality of the protected information. However, one of the critical vulnerabilities of encryption techniques is protecting the information from being exposed. To address these reliability problems, especially for large information content items such as secret images (satellite photos or medical images), an image secret sharing schemes (SSS) is a good alternative to remedy these types of vulnerabilities
Suppose a bank vault must be opened every day. Although the bank employs three senior tellers, management does not want to entrust any individual with the combination. Hence, bank management would like a vault-access system that requires any two of the three senior tellers. This problem can be solved using a secret sharing scheme called two-out-of-three threshold scheme.
A secret sharing scheme is an intellectual candidate for ensuring secrets as cryptographic keys transmit via internet. There are many application areas where secrets need to be shared. Some of these application areas are the following:
1. Key escrow in public key cryptosystems.
2. Revocable anonymity in electronic money.
3. Authorization for critical operations, i.e. missile launches, etc.
There are many criteria to classify secret sharing schemes. These criteria are based on the type of the secret, process of recovery, and the accuracy and quality of the recovered secret. This classification can be based on:
1. Secret Type.
In this classification, there are two types of secret sharing schemes: The old traditional secret sharing:Here, the secret can only represent number. The recovery of the secret involves computations. Since the invention in1979, secret sharing schemes have been extensively investigated. In particular, much work was done on the required length of the shares relative to the secret size. It is a well known basic fact that shares of a secret have to be at least of the size of the secret itself, and most of the work on share sizes investigates when this lower bound can be achieved or must be exceeded for different kinds of schemes. Having shares of the size of the secret is not a serious problem as long as these secrets are short, e.g. short secret key, as most traditional applications require. However, this effect of information replication among the participants of a distributed environment can be very space and communication inefficient if the secret is a large confidential file, a long message to be transmitted over unreliable links, or a secret data base shared by several servers. Applications like these are becoming more and more necessary. Visual Secret Sharing schemes:The secret represents image. The first time for such scheme was introduced1994.
2. The Quality of Recovered Image
The accuracy and the quality of the recovered secret image classify v secret sharing schemes into two categories:
Lossless visual secret sharing schemes:The recovered image from qualified set of shares must be identical to the original secret image.
Lossy visual secret sharing schemes:The schemes attempt to eliminate imperceptibly information of image and minimize the size in bandwidth and storage space
3. The computational Power for Decoding Shares
According to this criteria, generally visual secret scheme fall into three main categories:
(1) Visual cryptography (VC-based) visual secret sharing schemes: Secret image sharing called visual cryptography where the recovery process of the secret image requires no computations.
(2) Variant Visual Secret Sharing (VVSS-based):Quality of the recovered secret image improves dramatically by extending visual cryptography to adopt low computation operations (e.g., logical AND, OR and XOR) in decoding.
(1) Interpolation method (IM-based) schemes:Secret sharing schemes in this category encode and decode image using the most computational power (compared with the above two categories).
Information hiding is mostly used in different application areas like, the business world, Steganography can be used to hide a secret chemical formula or plans for a new invention. Steganography can also be used in the non-commercial sector to keep private digital information protected for a number of purposes such as secret data hiding and copyright protection. It can be used for Data authentication, ensuring authenticated data availability for academic usage, monitoring of data piracy, labeling electronic data/contents, ownership identification, providing confidentiality and integrity enhancement control of electronic data piracy etc.
Unobtrusive communications are required by military and intelligence agencies:even if the content is encrypted, the detection of a signal on a modern battlefield may lead rapidly to an attack on the signaler. For this reason, military communications use techniques such as spread spectrum modulation or meteor scatter transmission to make signals hard for the enemy to detect or jam.
Criminals also place great value on unobtrusive communications and their preferred technologies include prepaid mobile phones and hacked corporate Switch boards through which calls can be rerouted. As a side effect, law enforcement and counter intelligence agencies are interested in understanding these technologies and their weaknesses, so as to detect and trace hidden messages.
Information hiding techniques also underlie many attacks on "multilevel secure" systems used by military organizations. A virus or other malicious code propagates itself from "low security" to "high security" levels and then signals data downwards using a covert channel in the operating system or by hiding information directly in data that may be declassified.
hiding techniques can also be used in situations where plausible deniability is required. The obvious motivation for plausible deniability is when the two communicating parties are engaged in an activity which is somehow illicit, and they wish to avoid being caught but more legitimate motives include fair voting, personal privacy, or limitation of liability.
Anonymous communications, including anonymous remailers and Web proxies, are required by legitimate users to vote privately in online elections, make political claims, consume sexual material, preserve online free speech, or to use digital cash. But the same techniques can be abused for defamation, blackmail, or unsolicited commercial mailing. The ethical positions of the players in the information hiding game are not very clear; therefore, the design of techniques providing such facilities requires careful thought about the possible abuses, which might be non-obvious.
The healthcare industry, and especially medical imaging systems, may benefit from information hiding techniques. They use standards such as DICOM (digital imaging and communications in medicine) which separates image data from the caption, such as the name of the patient, the date, and the name of the physician. Sometimes the link between image and patient is lost, thus, embedding the name of the patient in the image could be a useful safety measure. Another emerging technique related to the healthcare industry is hiding messages in DNA sequences. This could be used to protect intellectual property in medicine, molecular biology or genetics.
A number of other applications of information hiding have been proposed in the context of multimedia applications. In many cases they can use techniques already developed for copyright marking directly; in others, they can use adapted schemes or shed interesting light on technical issues. The application of information hiding includes automatic monitoring of copyrighted material on the Web, automatic audit of radio transmissions, Data augmentation, Tamper proofing.
The purpose of this research is to investigate the image information hiding issues associated with estimating the capacity of the embedding process in addition to develop a visual secret sharing scheme. The contributions of this dissertation are described as follows:
Firstly, In order to enhance the security of the information, we proposed a novel and effective visual secret sharing scheme (VSS) based on the use of pseudo random number generator (PRNG). The PRNG has very long periods to ensure unrepeated pattern, meets the known conditions for randomness. The random generator devised here will have new features, such as, using variable permutation, and a system of linear feedback shift registers in addition to nonlinear functions. The proposed scheme is developed to be perfect (the scheme is called perfect if any non-qualified (forbidden) subset has absolutely no information about the shared secret); in our system, any share will not reveal any unintended information about the secret image. The proposed scheme is intended to achieve optimal pixel expansion, which leads to huge reduction in the space needed to store shares and improves the speed of transmission channel of digital information. The shares of the visual cryptography schemes are to be used mainly in digital networking and they are transmitted on air. As the shares become smaller they get transmitted faster and save storage media space.
Second, the basic idea is to build image a steganography technique to hide information in the frequency domain by altering the magnitude of all DCT coefficients to increase the embedding capacity. To achieve that we used Discreet Cosine transformation (DCT) to transform original image (cover image) blocks from spatial domain to frequency domain. Huffman encoding is performed on the secret image before it is embedded in the frequency domain and the four tier storage procedure is applied to increase the security of the secret image. LSB embedding mechanism is perfect in deceiving the HVS; however, it has weak resistance to attacks. We applied a Consistent Bit Length embedding mechanism in frequency domain to increase the embedding capacity w
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