Data hiding using pseudo magic squares for embedding high payload in digital images

Multimedia Tools and Applications - In this paper, a novel information hiding scheme based on pseudo magic squares is proposed. The pseudo magic square pattern is generated using the Knight’s...     

预条件的平方Smith法求解大型Sylvester矩阵方程

提出了一种预条件的平方Smith算法求解大型连续Sylvester矩阵方程,该算法利用交替方向隐式迭代(ADI)来构造预条件算子,将原方程转换为非对称Stein方程,并在Krylov子空间中应用平方Smith法迭代产生低秩逼近解。数值实验表明,与已知的Jacobi迭代法等算法相比,该算法有更好的迭代效率和收敛精度。     

Efficient large payloads ternary matrix embedding

Matrix embedding (ME) can be exploited to improve the embedding efficiency for steganography by making fewer changes to the cover data. In ME, the sender and recipient agree on a parity check matrix (PCM) in advance. The PCM will be used by the sender to embed secret message into the cover data and later by the decoder to extract the embedded message. The embedding performance of ME is greatly influenced by the PCM thus the choice of PCM is crucial for ME. On the other hand, since larger sized PCM usually leads to higher embedding efficiency, how to keep the balance between the computational complexity and the embedding efficiency is also an important problem of ME. Based on these considerations, an efficient ternary ME method for large payloads data embedding is proposed in this paper. We utilize a specific matrix construction for PCM to improve embedding efficiency and a sub-optimal search strategy to reduce the computational complexity. The experimental results show that the proposed method achieves good embedding efficiency at low time cost and it outperforms some state-of-the-art works. For example, for a cover image with 512 × 512 pixels at an embedding rate of 1 bit per pixel, the proposed method can be implemented within 0.5 second in a personal computer with a rather high embedding efficiency as 3.89.     

Matrix embedding for large payloads

Matrix embedding is a previously introduced coding method that is used in steganography to improve the embedding efficiency (increase the number of bits embedded per embedding change). Higher embedding efficiency translates into better steganographic security. This gain is more important for long messages than for shorter ones because longer messages are, in general, easier to detect. In this paper, we present two new approaches to matrix embedding for large payloads suitable for practical steganographic schemes-one based on a family of codes constructed from simplex codes and the second one based on random linear codes of small dimension. The embedding efficiency of the proposed methods is evaluated with respect to theoretically achievable bounds.     

Minority codes with improved embedding efficiency for large payloads

Improving embedding efficiency is important for watermarking with large payloads. In this paper, we propose a coding scheme named Minority codes by observing the relationship between the populations and positions of the binary bits in a sequence whose length is an odd number. In such a sequence, there is always a bit value, whose population is minority. We observe that the positions of the minority bit in two complement sequences are the same. By using this property, we create Minority codes whose codebook is composed of a pair of complement sequences for each entry. Minority codes can be combined with watermarking algorithms to improve embedding efficiency, because we can always identify the codeword that causes fewer embedding changes according to the host image and the watermarking method. The performance of Minority codes is analyzed theoretically and supported experimentally. The complexity of Minority codes is quite low and suitable for large payloads.     

On-line frequency domain information for control of a flexible-linkrobot with varying payload

Experimental results are given for the endpoint position control of a single-link, very flexible robot arm carrying an unknown, varying payload. The control objective is to maintain endpoint position accuracy in the presence of flexure effects after rapid movement due to a rigid body slew-angle commanded position. Fast, simple, and efficient frequency domain schemes are used for online controller gain adjustment within an effective scheduling framework. Only endpoint acceleration and motor shaft angle measurements are utilized in relatively simple control laws where the appropriate gains have been scheduled as correlated to modal frequency information corresponding to a varying, unknown payload     

融合属性信息的异质网络嵌入方法

现有的异质网络嵌入方法不仅忽略了网络中的异质边及其对节点嵌入的不同影响,还未考虑到网络结构与节点属性的融合。为此提出了一种融合属性信息的异质网络嵌入方法（SHANE）。将序列到序列（seq2seq）模型应用到依据边类型划分的子图中,无缝融合节点的结构信息和属性信息,同时捕捉节点的高阶语义信息。实验表明,SHANE在两个不同类型的数据集中进行链接预测任务,可以取得相对显著的效果。     

A high stego-image quality steganographic scheme with reversibility and high payload using multiple embedding strategy

Tian’s method is a breakthrough reversible data embedding scheme with high embedding capacity measured by bits per pixel (bpp) and good visual quality measured by peak signal-to-noise ratio (PSNR). However, the embedding capacity and visual quality of this method can be significantly improved. Thus, we propose a simple reversible steganographic scheme in spatial domain for digital images by using the multiple embedding strategy. The proposed method horizontally and vertically embeds one secret bit into one cover pixel pair. The experimental results show that the proposed reversible steganographic method achieves good visual quality and high embedding capacity. Specifically, with the one-layer embedding, the proposed method can obtain the embedding capacity of more than 0.5 bpp and the PSNR value greater than 54 dB for all test images. Especially, with the five-layer embedding, the proposed method has the embedding capacity of more than 2 bpp and the PSNR value higher than 52 dB for all test images. Therefore, the proposed method surpasses many existing reversible data embedding methods in terms of visual quality and embedding capacity.     

Nonlinear cascade control of an electro-hydraulic actuator with large payload variation

Electro-hydraulic actuators have been widely used in industrial production, but the unknown variable payload seriously affects its position control accuracy. Therefore, a radial basis function neural network disturbance observer is designed to estimate the lumped disturbance force through strong online learning ability in the absence of force sensor. Besides, a nonlinear cascade controller with double loop structure is proposed in this paper. A global fast terminal sliding mode control method is firstly applied in the outer loop position system, which can eliminate chattering and improve convergence speed comparing to traditional sliding mode control. The inner loop force system adopts a backstepping control method to calculate the actual input of the whole system. Theoretical analysis indicates that the proposed controller is stable even if existing time-variant disturbance. Moreover, three comparative controllers are designed and tested in both simulations and experiments. Comparative results show that the developed method has absolute average errors of 1.14 and 0.49 mm in different position tracking, which means more satisfactory tracking performance compared to the contrast controllers.     

结合EMD-cl嵌入的多载体密图分存方法

目的 传统误差扩散或恢复函数的多载体密图分存会对嵌密载体视觉质量造成较大影响,同时恢复函数需单独设计,只适用于二值或灰度图像,且通过简单Arnold置乱或异或加密仅能提供有限的安全性。针对此问题,提出结合EMD-c^l嵌入的多载体密图分存方法。方法 采用双哈希MD5和SHA-1值产生多组与密图属性和用户密钥有关的置乱参数,驱动2维双尺度矩形映射来改变载体像素对应关系,然后将置乱后载体同位置像素构成向量,按扩展约瑟夫遍历映射分配基向量,通过EMD-c^l嵌入秘密像素,从而将密图分存到多张载体中。结果 采用EMD-c^l提高了嵌密载体视觉质量且不需额外设计恢复函数,可针对不同分辨率和灰度阶密图分存。所提方法载体像素位置和EMD-c^l基向量都与密图MD5和SHA-1值以及用户密钥紧密绑定,仅有正确用户密钥和密图MD5和SHA-1值才能对密图恢复,并可通过第三方公信方托管的参与者分存信息MD5和SHA-1值使得所述策略具备认证能力。所提方法密钥空间为1.193 6×10¹¹⁸,可抵抗暴力破解。实验结果表明,结合EMD-c^l,所提方法具有较好的嵌密载体视觉质量,NC趋近于1,对于EMD-3^l,嵌密载体PSNR均接近50 dB;对于EMD-5^l和EMD-7^l,PSNR分别达到45 dB和42 dB,而传统方法,PSNR最好仅为42 dB。所提方法可分存不同分辨率和灰度阶密图,可对参与者密钥分存信息的真实性进行检验且对密图哈希和用户密钥极度敏感。结论 所提方法具有较低复杂度,较高安全性和普适性及认证能力,在整体性能上优于传统误差扩散或恢复函数的多载体密图分存方法,适用于对嵌密载体视觉质量要求高和针对不同分辨率和灰度阶密图分存的安全场景中。     

Improving embedding efficiency for digital steganography by exploiting similarities between secret and cover images

Multimedia Tools and Applications - Digital steganography is becoming a common tool for protecting sensitive communications in various applications such as crime/terrorism prevention whereby law...     

融合链接预测相似度矩阵的属性网络嵌入算法

在属性网络中,与节点相关联的属性信息有助于提升网络嵌入各种任务的性能,但网络是一种图状结构,节点不仅包含属性信息还隐含着丰富的结构信息。为了充分融合结构信息,首先通过定义节点的影响力特性、空间关系特征;然后根据链接预测领域基于相似度的定义构建相似度矩阵,将节点二元组中的关联向量映射到相似度矩阵这一关系空间中,从而保留与节点相关的结构向量信息;再基于图的拉普拉斯矩阵融合属性信息和标签特征,将上述三类信息集成到一个最优化框架中;最后,通过二阶导数求局部最大值计算投影矩阵获取节点的特征表示进行网络嵌入。实验结果表明,提出的算法能够充分利用节点二元组的邻接结构信息,相比于其他基准网络嵌入算法,本模型在节点分类任务上取得了更好的结果。     

Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates

Steganalysis with low embedding rates is still a challenge in the field of information hiding. Speech signals are typically processed by wavelet packet decomposition, which is capable of depicting the details of signals with high accuracy. A steganography detection algorithm based on the Markov bidirectional transition matrix (MBTM) of the wavelet packet coefficient (WPC) of the second-order derivative-based speech signal is proposed. On basis of the MBTM feature, which can better express the correlation of WPC, a Support Vector Machine (SVM) classifier is trained by a large number of Least Significant Bit (LSB) hidden data with embedding rates of 1%, 3%, 5%, 8%,10%, 30%, 50%, and 80%. LSB matching steganalysis of speech signals with low embedding rates is achieved. The experimental results show that the proposed method has obvious superiorities in steganalysis with low embedding rates compared with the classic method using histogram moment features in the frequency domain (HMIFD) of the second-order derivative-based WPC and the second-order derivative-based Mel-frequency cepstral coefficients (MFCC). Especially when the embedding rate is only 3%, the accuracy rate improves by 17.8%, reaching 68.5%, in comparison with the method using HMIFD features of the second derivative WPC. The detection accuracy improves as the embedding rate increases.     

融合层次类型信息的双向图注意力机制的知识图谱嵌入模型

知识图谱嵌入旨在将实体与关系映射到低维且稠密的向量空间中。目前已有的嵌入模型仍存在以下两个方面的缺陷：现有的模型大多只关注知识图谱的语义信息,而忽略了大量三元组的隐藏信息;现有的模型仅关注了实体的单向信息,而忽略了双向的潜在信息。针对以上问题,提出了一种融合层次类型信息的双向图注意力机制的知识图谱嵌入模型Bi-HTGAT,该模型设计了层次类型注意力机制,考虑不同关系下每种类型的不同实体对中心实体的贡献。同时引入了关系的方向注意力机制,通过融合不同方向的邻居信息来更新实体和关系嵌入,最终聚合两部分信息以得到实体的最终嵌入。在基准数据集上的实验证明,Bi-HTGAT在链接预测任务上性能明显优于其他基线模型,充分证明了Bi-HTGAT能够进一步提高嵌入结果的精准度。     

Rich QR code with three-layer information using visual secret sharing scheme

Multimedia Tools and Applications - Owing to efficient machine recognition, QR codes have been widely used in many aspects such as information management, electronic identity and mobile payment....     

具有鲁棒性与数据嵌入能力的JPEG压缩图像加密算法

针对JPEG图像加密算法引起的比特流大小增加与鲁棒性较差的问题,提出了一种具有鲁棒性与数据嵌入能力的JPEG图像格式兼容的加密算法。首先,利用AC系数抓取纹理信息并生成部分区域,基于该区域将DC系数编码;然后,使用8个不同的顺序扫描AC系数,选择其中比特流大小最小的顺序;之后,提取每块的AC系数,并且操作AC系数来增加置换的范围。算法的主要过程均具有可逆性,可成功提取嵌入信息并且完美地重建原图像。基于真实JPEG照片的实验结果表明,本算法对素描攻击具有鲁棒性,可抑制比特流大小增加且具有数据嵌入的能力。     

A deep person re-identification model with multi visual-semantic information embedding

Multimedia Tools and Applications - The local features of different body parts have been widely used to learn more discriminative representation for person re-identification, which act as either...     

融合多层次结构信息的深度属性二分网络表示学习

网络表示学习旨在将网络中的节点转换到低维向量空间,并保持网络固有属性.现有方法大多针对普通网络,忽略了属性二分网络的特殊性及网络的高度非线性特性等.针对上述问题,首先引入一个扩展权重矩阵融合二分网络显式和携带属性信息的隐式结构;接着提出一种基于深度自编码器的属性二分网络表示学习模型,以捕捉网络的高度非线性特性;通过深度自编码器重构二阶邻近度以保持全局网络结构,同时该编码器利用节点一阶邻近度作为监督信息来保持局部网络结构;最后进行联合优化.将该模型在Yelp、Douban Book、Dou-ban Movie和MovieLens四个数据集上进行推荐任务,结果显示该模型的F1@10、MAP@10、MRR@10和NDGG@10指标在四个数据集上的平均值相较最新基准方法(ABNE)分别提高4.29％、5.63％、6.26％、4.21％.     

Entropy-based multi-view matrix completion for clustering with side information

Pattern Analysis and Applications - Multi-view clustering aims to group multi-view samples into different clusters based on the similarity. Since side information can describe the relation between...