3D网格隐写与隐写分析回顾与展望

在计算机图形学中,3D形状可有多种表示形式,包括网格、体素、多视角图像、点云、参数曲面和隐式曲面等。3D网格是常见的表示形式之一,其构成3D物体的顶点、边缘和面的集合,通常用于表示数字3D物体的曲面和容积特性。在过去的20年中,基于3D网格载体的虚拟现实、实时仿真和交叉3维设计已经在工业,医疗和娱乐等场景得到广泛应用,以3D网格为载体的水印技术、隐写和隐写分析技术也受到研究者的关注。相比于图像与音视频等载体的隐写,3D网格具备嵌入方式灵活与载体形式多变等其自身的优势。本文回顾了3D网格隐写和隐写分析的发展,并对现有研究工作进行了系统的总结和分类。根据嵌入方式和嵌入位置将隐写算法分成4类：两态调制隐写、最低位隐写、置换隐写和变换域隐写;根据特征提取角度将隐写分析算法分为2类：通用型隐写分析和专用型隐写分析。随后,介绍了每个类别的技术,综合安全性、鲁棒性、容量以及运算效率分析了各类算法的优劣性,总结当前的发展水平,并提供了不同嵌入率下两种数据集上隐写分析算法之间的性能比较。最后讨论了3D隐写和隐写分析现有技术的局限性,并探讨了潜在的研究方向,旨在为后续学者进一步推动3D隐写和隐写分析技术提供指导。     

一种基于权重融合的JPEG隐写分析方法

针对JPEG图像通用隐写检测中检测效率低、训练时间长的问题,提出一种基于集成分类器的新检测方法。算法以CC-PEV为特征对图像进行描述并作为隐写分析特征;然后,随机构造若干个特征子空间,用bootstrap方法构造图像训练子集,分别进行训练得到数个基分类器;根据基分类器的分类结果赋予基分类器不同的权重,将基分类器的结果按照其权重进行融合得到最终的结果。本文对该算法进行了测试,对它的集成性、检测准确率和训练时间进行分析。实验结果表明,相对于传统的集成方法,本文方法用自举方法构造训练集、随机方法构造子特征空间、赋予基分类器不同权重进行融合能够显著地提高算法准确率。本文方法相对于SVM和传统的集成分类方法,具有更高的检测率,对于特征维数更大的图像检测,具有更好的拓展性和一般适用性。     

Audio steganalysis based on reversed psychoacoustic model of human hearing

During the last decade, audio information hiding has attracted lots of attention due to its ability to provide a covert communication channel. On the other hand, various audio steganalysis schemes have been developed to detect the presence of any secret messages. Basically, audio steganography methods attempt to hide their messages in areas of time or frequency domains where human auditory system (HAS) does not perceive. Considering this fact, we propose a reliable audio steganalysis system based on the reversed Mel-frequency cepstral coefficients (R-MFCC) which aims to provide a model with maximum deviation from HAS model. Genetic algorithm is deployed to optimize dimension of the R-MFCC-based features. This will both speed up feature extraction and reduce the complexity of classification. The final decision is made by a trained support vector machine (SVM) to detect suspicious audio files. The proposed method achieves detection rates of 97.8% and 94.4% in the targeted (Steghide@1.563%) and universal scenarios. These results are respectively 17.3% and 20.8% higher than previous D2-MFCC based method.     

An active steganalysis approach for echo hiding based on Sliding Windowed Cepstrum

This paper presents an active steganalysis technique for echo hiding (EH). This approach can differentiate stego audios (with hidden message) from nature ones (without hidden message), and then extract sequential EH messages in stego audios without prior knowledge about the EH technique. The procedure of this algorithm can be simplified as follows: (i) Sliding Windowed Cepstrum (SWC) is obtained by employing a Sliding Window (SW) to move over the audio signal sample by sample. (ii) The echo detector is designed based on statistical analysis of the Cepstrum Peak Location Aggregation Degree (CPLAD). (iii) For stego signals, both echo delay and the range of segment length are estimated by exploring the changing rule of the SWC. (iv) The accurate estimation of segment length and synchronism position is acquired by the grid search algorithm. (v) Finally, the binary secret message can be extracted using the estimated parameters in the previous steps. The proposed method has been implemented and tested to extract the message which is embedded into audio clips by using EH techniques with different kernels. The experimental results show that the accuracy of extraction is no less than 90% when attenuation is greater than 0.45.     

PN序列估计与扩频隐藏信息分析

在非协作信息侦测情况下,提出了一种直接序列扩频(DS-SS)信号PN序列的估计方法,在此基础上实现了扩频隐藏信息的盲提取.该方法以估计序列和扩频信号的累积相关值为目标函数,建立估计序列长度及其构成的两变量优化模型,通过遗传算法求解,可较好地估计出PN序列.通过获取的PN序列与藏密信号的相关性分析,可实现扩频隐藏信息的盲...     

针对隐写分析冗余评估指标的属性约简算法

针对隐写分析评估指标体系中存在的知识冗余,提出了一种隐写分析评估指标的属性约简方法.在分析存在知识冗余的指标体系的基础上,采用BCC算法求出各评估指标初始区间及其约简,并用之将仿真实验数据离散化;之后将离散化矩阵作为HORAFA算法的输入,输出即得到最终的属性约简.仿真实验验证了该属性约简方法对冗余评估指标约简的有效性...     

Steganalysis Using Fractal Block Codes and AP Clustering in Grayscale Images

This paper presents a universal scheme (also called blind scheme) based on fractal compression and affinity propagation (AP) clustering to distinguish stego-images from cover grayscale images, which is a very challenging problem in steganalysis. Since fractal codes represent the self-similarity features of natural images, we adopt the statistical moment of fractal codes as the image features. We first build an image set to store the statistical features of natural images with and without hidden messages, and then apply the AP clustering technique to group this set. The experimental result shows that the proposed scheme performs better than Fridrich's traditional method.     

基于时间和空间冗余的视频隐写分析方法

为了实现对视频隐写的有效检测,提出一种使用支持向量机(SVMs)的视频隐写盲检测方法.该方法利用时间和空间冗余,用帧间共谋的方式获取帧估计数据,提取视频帧的融合马尔科夫和DCT特征,构造SVMs分类器对待测视频进行检测,从而达到视频隐写检测的目的.实验结果表明,该方法能够准确地区分载密视频和原始视频.     

基于博弈论的无意攻击和隐写分析攻击下嵌入水印漏警概率分析(英文)

Steganalysis attack is to statistically estimate the embedded watermark in the watermarked multimedia,and the estimated watermark may be destroyed by the attacker.The existing methods of false negative probability,however,do not consider the influence of steganalysis attack.This paper proposed the game theory based false negative probability to estimate the impacts of steganalysis attack,as well as unintentional attack.Specifically,game theory was used to model the collision between the embedment and steganalysis attack,and derive the optimal building embedding/attacking strategy.Such optimal playing strategies devote to calculating the attacker destructed watermark,used for calculation of the game theory based false negative probability.The experimental results show that watermark detection reliability measured using our proposed method,in comparison,can better reflect the real scenario in which the embedded watermark undergoes unintentional attack and the attacker using steganalysis attack.This paper provides a foundation for investigating countermeasures of digital watermarking community against steganalysis attack.     

JPEG-Compatibility Steganalysis that Distinguishes Embedding Changes from Recompression Artifacts

JPEG-Compatibility steganalysis detects the presence of secret message embedded in the JPEG decompressed images and estimates the embedding rate. We propose a JPEG-Compatibility steganalysis algorithm that estimates the embedding rate based on the difference between the stego image and its recompression based predicted co-vet image. In particular, compression artifacts and embedding changes are distinguished based on the amplitude of pixel value changes. This is done independent of the embedding positions, thus is effective for both content non-adaptive and content adaptive steganography. In addition, we also improve the recompression prediction scheme to more accurately estimate the JPEG quantization table. Experimental results show that the proposed algorithm is significantly more effective in detecting spatial ±1 steganography across a wide range of quality factors and embedding rates, when compared to the previous works.