3472016
Detecting doubly compressed JPEG images by using Mode Based First Digit Features
In this paper, we utilize the probabilities of the first digits of quantized DCT (discrete cosine transform) coefficients from individual AC (alternate current) modes to detect doubly compressed JPEG images. Our proposed features, named by mode based first digit features (MBFDF), have been shown to outperform all previous methods on discriminating doubly compressed JPEG images from singly compressed JPEG images. Furthermore, combining the MBFDF with a multi-class classification strategy can be exploited to identify the quality factor in the primary JPEG compression, thus successfully revealing the double JPEG compression history of a given JPEG image.
3471440
Universal JPEG steganalysis based on microscopic and macroscopic calibration
In this paper, we present a new universal steganalysis scheme to effectively attack some recently proposed JPEG steganography. Different from the other steganalyzers, not only the magnitude but also the sign dependencies existed in intra-block and inter-block quantized DCT (discrete cosine transform) coefficients are exploited by the Markov empirical transition matrices. Moreover, a new microscopic and macroscopic calibration method is proposed to calibrate the local and global distribution of the quantized DCT coefficients of the test image, thus improve the detecting performance. Experimental results demonstrate that our proposed scheme outperforms some existing steganalyzers in attacking the advanced JPEG steganography such as F5, MB1 and Outguess.
3451766
Attack LSB Matching Steganography by Counting Alteration Rate of the Number of Neighbourhood Gray Levels
In this paper, we propose a new method for attacking the LSB (least significant bit) matching based steganography. Different from the LSB substitution, the least two or more significant bit-planes of the cover image would be changed during the embedding in LSB matching steganography and thus the pairs of values do not exist in stego image. In our proposed method, we get an image by combining the least two significant bit-planes and divide it into 3x3 overlapped subimages. The subimages are grouped into four types, i.e. T 1,T 2, T 3 and T 4 according to the count of gray levels. Via embedding a random sequence by LSB matching and then computing the alteration rate of the number of elements in T 1, we find that normally the alteration rate is higher in cover image than in the corresponding stego image. This new finding is used as the discrimination rule in our method. Experimental results demonstrate that the proposed algorithm is efficient to detect the LSB matching stegonagraphy on uncompressed gray scale images.
3441918
Effect of Different Coding Patterns on Compressed Frequency Domain Based Universal JPEG Steganalysis
Current steganalytic schemes for JPEG steganography are in favor of extracting features in DCT (Discrete Cosine Transform) domain and/or spatial domain. A recently proposed compressed frequency domain based universal steganalytic algorithm [21] showed concern over the statistics of Huffman compressed stream. The authors claimed that it was very effective in detecting stego images embedded by JPEG steganographic tools, including JPHide, F5 and OutGuess. Even though only several bytes were embedded, the scheme was still able to work, thus demonstrating astonishing steganalysis capability. By carefully controlled studies on the factors which may have impact on the new steganalytic method, we find out the truly cause of the powerfulness of this "payload-independent" steganalyzer. Experimental results reveal that different coding patterns used in cover and stego images, rather than the Avalanche Criterion [24] explained by its authors, have led to great detection efficiency. When the same coding pattern is employed in both cover and stego images, the performance of the newly devised steganalyzer has greatly dropped. Implication from this paper is that we should ensure the difference between the cover and stego images is only caused by data embedding itself in steganography and steganalysis.
3475098
Steganalysis of LSB Greedy Embedding Algorithm for JPEG Images using Coefficient Symmetry
A recently developed LSB greedy embedding algorithm for JPEG images is capable of resisting the chi-square attack. By carefully studying the quantized DCT (discrete cosine transform) coefficients of the cover and stego images, we find that the embedding algorithm does not preserve the histogram of the DCT coefficients well. In this paper, we define a new chi-square statistic which is used to measure whether the image under scrutiny is like the cover or the stego. Our proposed steganalytic method is based on the symmetry property of the DCT coefficients in JPEG images. It can also be used in the scenario where the cover images are double JPEG compressed. The reliability of this specific steganalytic scheme depends on the embedding rate and it is influenced by the JPEG quality factor. Experimental results show that when the embedding rate exceeds half of the maximal embedding capacity, the steganographic algorithm is detectable with a very low false negative rate, whatever the quality factor is.
38238585
Exploiting multi-scale support vector regression for image compression
Unlike traditional neural networks that require predefined topology of the network, support vector regression (SVR) approach can model the data within the given level of accuracy with only a small subset of the training data, which are called support vectors (SVs). This property of sparsity has been exploited as the basis for image compression. In this paper, for still image compression, we propose a multi-scale support vector regression (MS-SVR) approach, which can model the images with steep variations and smooth variations very well resulting in good performance. We test our proposed MS-SVR based algorithm on some standard images. The experimental results verify that the proposed MS-SVR achieves better performance than standard SVR. And in a wide range of compression ratio, MS-SVR is very close to JPEG in terms of peak signal-to-noise ratio (PSNR) but exhibits better subjective quality. Furthermore, MS-SVR even outperforms JPEG on both PSNR and subjective quality when the compression ratio is higher enough, for example 25:1 for Lena image. Even when compared with JPEG-2000, the results show greatly similar trend as those in JPEG experiments, except that the compression ratio is a bit higher where our proposed MS-SVR will outperform JPEG-2000.
15163844
Towards a Coordination Infrastructure for Pervasive Computing Environment Based on Tuplespace and Semantic Web
Pervasive computing is an emerging computing paradigm, which is expected to be part of our everyday life in the foreseeable future. The coordination among heterogeneous devices, services, and software agents will be vital for ensuring the success of their interactions. Tuplespace (TS) offers a coordination infrastructure for communication. With pervasive computing environment which is characterized as an open and dynamic distributed system become more ubiquitous, autonomous, and complex, this can pose some limitations to TS. In this paper we introduce Semantic Tuplespaces (STS) based on a combination of Semantic Web technologies and tuplespace computing. It acts as a middleware to enable communication and coordination based on the principle of publish and retrieve of semantic information. We describe overview of the conceptual model and discuss the necessary extensions to the original tuplespace. An initial version of the STS prototype system has been implemented based on Jena and Pellet, a DL reasoner. Finally, through an elaborate use case, we show the usability and benefits of our approach.
35160170
RBF Neural Network Based Shape Control of Hyper-redundant Manipulator with Constrained End-Effector
Hyper-redundant manipulator has more degrees of freedom than the least necessary to perform a given task, thus it has the features of overcoming conventional industrial robot’s limitation to carry out a designated difficult task. When the manipulator carries out the missions such as brushing or writing on a surface, drilling or inspection in a hole, the end-effector of the manipulator usually has both position and orientation requirement. Effective control of the hyper-redundant manipulator with such constrained end-effector is difficult for its redundancy. In this paper, a novel approach based on RBF neural network has been proposed to kinematically control the hyper-redundant manipulator. This technique, using variable regular polygon and RBF neural networks models, is completely capable of solving the control problem of a planar hyper-redundant manipulator with any number of links following any desired direction and path. With the shape transformation of variable regular polygon, the manipulator’s configuration changes accordingly and moves actively to perform the tasks. Compared with other methods to our knowledge, this technique has such superiorities as fewer control parameters and higher precision. Simulations have demonstrated that this control technique is available and effective.
13896042
Posture control of a dual-crawler-driven robot
This paper deals with a tracked robot that consists of the proposed crawler module, in which a planetary gear reducer is used as the power transmission device to give two different outputs with just one actuator. This under-actuated system could perform posture control through the interaction between the front and rear modules. On occasion, the posture that the front module is lifted up can make the robot overcome obstacles actively and easily. To find out the controllable postures, the static analysis of the robot has been conducted. In this paper, we provide the control strategy for performing the posture control, and propose the control methods including direct, indirect, and cooperative control to conduct the posture control. Experimental tests show the effectiveness of the control methods.
9741896
Authoritative Server's Impact on Domain Name System's Performance and Security