A refining localization watermarking for image tamper detection and recovery

More than ever, the practical and accurate watermarking technologies are called for the growing amount of exchanged digital image over the Internet. To protect the integrity and authenticity of digital image and to enhance the effect of tamper detection and restoration, we design and implement a semi-fragile watermark based on cat transformation, mostly used to locate tamper and recover for the transformed image and plain-image. The watermark which consists of two parts: the authentication watermark and recovery watermark, is embedded into the 2 least significant bit (LSB) of the pixel of the original image. The authentication watermark is calculated by the pixel value comparison and the parity check code, while the recovery watermark contains the average pixel value of the Torus image block. In the detection side, we use the hierarchy concept to locate the tamper in three layers and recover the attacked image in two layers. By using the hierarchy concept, this algorithm has another superiority that tamper can be detected on confused image. The experimental results show that our algorithm can accurately locate tamper and realize the content recovery and effectively prevent the vector quantization attack. Compared with other algorithms, this algorithm has better effect of tamper location and recovery.

A secure high capacity full-gray-scale-level multi-image information hiding and secret image authentication scheme via Tchebichef moments

Obtaining accurate location information is important in practical applications of wireless sensor networks (WSNs).The distance vector hop (DV-Hop) is a frequently-used range-free localization algorithm in WSNs, but it has low localization accuracy.Moreover, despite various improvements to DV-Hop-based localization algorithms, maintaining a balance between high localization accuracy and good stability and convergence is still a challenge.To overcome these shortcomings, we proposed an improved DV-Hop localization algorithm based on the bat algorithm (IBDV-Hop) for WSNs.The IBDV-Hop algorithm incorporates optimization methods that enhance the accuracy of the average hop distance and fitness function.We also introduce a nonlinear dynamic inertial weight strategy to extend the global search scope and increase the local search accuracy.Moreover, we develop an updated solutions strategy that avoids premature convergence by the IBDV-Hop algorithm.Both theoretical analysis and simulation results show that the IBDV-Hop algorithm achieves higher localization accuracy than the original DV-Hop algorithm and other improved algorithms.The IBDV-Hop algorithm also exhibits good stability, search capability and convergence, and it requires little additional time complexity and energy consumption.

Pinpoint authentication watermarking based on a chaotic system

On accuracy of region based localization algorithms for wireless sensor networks

We propose a new watermarking algorithm for stereoscopic image tamper detection and self-recovery in three-dimensional multimedia services. Initially, left and right views of stereoscopic image are divided into nonoverlapping 2×2 blocks in order to improve the accuracy of tamper localization in an image. As the left and right views of a stereoscopic image are not independent from each other but have an inter-view relationship, every block of a stereoscopic image is classified into matching block or nonmatching block and then block disparities are obtained. Both matching blocks in the left and right views have similar pixel values, so that fewer bits are allocated for recovery watermark generation, which can increase the quality of watermarked stereoscopic images. A hierarchical tamper-detection strategy with a four-level checkup is presented to improve the accuracy of tamper localization. Additionally, two copies of block (matching block and nonmatching block) information are embedded into the stereoscopic image, and it assures the quality of tampered recovery. For the nonmatching block recovery, two copies of the partner block are embedded into their chaotic mapping blocks, which supply the second chance for tamper recovery. For the matching block recovery, the inter-view relationship between tampers of left and right views supplies the third chance for tamper recovery. Experimental results show that the proposed algorithm can not only detect and locate tampers in stereoscopic image more accurately but also recover the tampered regions better, compared with other algorithms.

Localization is an essential problem in Wireless Sensor Networks (WSNs). Many localization algorithms have been proposed, but few efforts have been paid on theoretical analysis on the accuracy of these algorithms. Because it is naturally to formalize range-based localization problems as deterministic parameter estimation problems, for range-based localization algorithms Cramér-Rao Lower Bound (CRLB) has been used to lower bound the variance on the estimation of sensor's positions. However, few similar works have been done for range-free localization algorithms. In this paper, based on geometry properties, we theoretically analyze bounds on accuracy for Region-Based Localization (RBL) algorithms which can be classified as one type of range-free localization algorithms. We prove that if in a RBL algorithm, the deployment region R with the area size s is partitioned into k regions (they can be with any shape and any area size), the localization accuracy is bounded below by no matter how the algorithm partitions R. Although the lower bound is not theoretically tight, our simulation results show that the gap between this bound and achievable accuracy is very small. We conjecture a tighter lower bound when k is large enough. We also observe that in order to achieve high localization accuracy, partitioned regions should have nearly the same size. We give three examples with simulation results to show how the results can be used to set the values of the parameters, like k and the corresponding anchor/event number, in a RBL algorithm in order to achieve desired localization accuracy.

It is a challenging work to design tamper recovery schemes for digital speech signal. Briefly, there are two problems need to be solved. One is that the signals used to tamper recovery are difficult to generate and embed, and the second is that it's hard to tamper location precisely for attacked speech signal. In this paper, compression and reconstruction method based on discrete wavelet transform (DWT) and discrete cosine transform (DCT) is given, to obtain the compressed signals used to tamper recovery. And then frame number and compressed signals are embedded based on block-based method. Attacked signal can be located by frame number, and compressed signals are extracted and used to reconstruct the attacked signal. Theory analysis and experimental results indicate that the scheme proposed not only improves the accuracy of tamper localization, but also can reconstruct the attacked signals.

Communication and networking plays a crucial role in data transmission in UASN. The sensor nodes in UASN are intermittently deployed randomly in the three‐dimension scenario. As a consequence, the three‐dimension based localization algorithm is the need for an hour. To fulfill the objective, we have proposed a localization algorithm I‐LASP (Improvement of localization algorithm for compensating stratification effect based on extended improved particle swarm optimization technique) in three‐dimensional UASN, based on compensation of stratification effect for the improvement of the performance parameters such as localization accuracy, ranging accuracy, convergence rate and execution time. To compute the accurate position of target nodes, EIPSO (Extended improved PSO) technique is applied, and the degree of coplanarity is checked before the calculation of distance among nodes in order to get the accurate location of target nodes. The Centroid method is used to initialize the position of sensor nodes, and the ray theory method is used to compensate the stratification effect on the layered ocean water. The proposed algorithm is compared to the existing LASP, Std PSO, and GNA‐ESSP (Gauss‐newton algorithm‐extended sound speed profile) localization algorithm. The proposed algorithm provides 34.50%, 38.87%, and 42.66% of high accuracy in terms of localization with low density of target sensor nodes and 37.96%, 29.58%, and 50.77% high accuracy in terms of localization with a high density of target sensor nodes respectively. The proposed algorithm is compared with LASP, GNA‐ESSP, and TDOA to obtain 66.84%, 71.14%, and 86.13% of high accuracy in terms of ranging with low density of target sensor nodes and 42.34%, 89.00%, and 95.08% high accuracy in terms of ranging with a high density of target sensor nodes respectively. Experimental results represents that the proposed algorithm obtains better performance in terms of localization accuracy, ranging accuracy, root mean square error, normalized localization error, execution time and convergence rate.

Several fragile watermarking schemes presented in the literature are either vulnerable to vector quantization (VQ) counterfeiting attacks or sacrifice localization accuracy to improve security. Using a hierarchical structure, we propose a method that thwarts the VQ attack while sustaining the superior localization properties of blockwise independent watermarking methods. In particular, we propose dividing the image into blocks in a multilevel hierarchy and calculating block signatures in this hierarchy. While signatures of small blocks on the lowest level of the hierarchy ensure superior accuracy of tamper localization, higher level block signatures provide increasing resistance to VQ attacks. At the top level, a signature calculated using the whole image completely thwarts the counterfeiting attack. Moreover, "sliding window" searches through the hierarchy enable the verification of untampered regions after an image has been cropped. We provide experimental results to demonstrate the effectiveness of our method.

Due to the rise in many industrial environment applications involving distributed networked collaborative intelligent measurement systems, intelligent monitoring and multi-sensor information exchange of private information, digital image information security and hidden image authentication, tampering detection, correction, and automatic intelligent self-recovery have become critical concerns. Towards that end, there is a need for more secure, efficient, and robust-to-unauthorized-tampering digital image watermarking, information hiding and authentication schemes. In our prior work, we introduced non-blind watermarking schemes where the carrier and watermark images are available at the receiver's end. We also proposed a double-blind scheme where both the carrier and the watermark images are not available at the receiver's end, but at the expense of possible lower pixel tampering, authentication and automatic intelligent self-correction ability. This paper proposes a blind wavelet-based, high capacity, secure digital watermarking and information hiding scheme with higher tampering localization and authentication that nullifies the need to have the carrier image available at the receiving end. The proposed scheme also increases robustness to image authentication and automatic self-recovery and correction compared to our prior double-blind scheme. The scheme is high capacity and sustains hiding secret hidden and watermarking images of the same full size as an arbitrary-sized carrier image. One of the benefits of the blind watermarking scheme is that it allows usage of varying and arbitrary carrier images that are unknown and unavailable anywhere, including the receiver's end. This is to prevent hackers' recognition of a familiar carrier image and their potential unauthorized tampering. Here, in this paper, two grayscale images are inserted in a colored carrier image. Here the watermark image is used for authentication and tamper localization. The second image is used as ownership or encoded secret hidden message image. The Arnolds Transform is used to introduce added security to a hidden image. The proposed scheme uses an embedded correction matrices mechanism for the extracted hidden information self-recovery from various tampering and digital attacks by unauthorized hackers.

Fragile watermarking methods have been used as active image authentication methods. These methods must have capabilities like high capacity, high visual quality, high image authentication ability and image recovery capability. Many of the fragile watermarking methods suggested in the literature do not provide all of these capabilities. In this article, a new probabilistic image authentication method with high capacity, high visual quality, high image authenticity ability and image recovery capability is proposed. Chaotic pseudo random number generators, a new watermark generation network which similar to neural network, modulo based watermark embedding functions, modulo based watermark extraction functions, tamper detection algorithm and perceptual hash based image recovery algorithm are utilized for creating a new probabilistic image authentication method in this article. The proposed method is a block based authentication method and 3 × 3 size of overlapping neighborhood blocks are used in this method. The proposed watermark generation network uses symmetric pixels as inputs and weights to generate predicted pixel. In this step, modulo operator and random numbers are used for calculating embeddable value. Owing to chaotic random number generator, the proposed method gains probabilistic and nonlinear structure. To generate random number, logistic map is used as random number generator in the proposed image watermarking method. Then, a modulo based watermark embedding function is used for embedding embeddable value (generated watermark). In the watermark extraction step, modulo operator is used. If the predicted value differs from the extracted value, tamper detection is performed. Otherwise, image authentication is success. A new image recovery algorithm is proposed in this method. This algorithm provides image recovery for tampered areas with high visual quality. The proposed image watermarking method can authenticate grayscale and color images. The experimental results demonstrated that, the proposed method has high payload capacity, high visual quality and high image authentication ability.

This paper proposes a fragile watermarking scheme of anti-deleting features for 2D vector map. The features in vector map are first divided into disjoint groups to ensure the accuracy of tamper localization. In order to locate the batch features deletion attack, we design a feature group correlation technique based on vertex insertion. And a watermark is generated by folding the hash results of the differences of the log-radiuses, which is robust to resist rotation, uniform scaling and translation (RST) operations. And we embed the watermark with a RST invariant watermarking method. Two datasets are constructed for experimentation and the results compared with previous methods indicate that the proposed scheme has good invisibility and high tampering localization accuracy on the feature addition and deletion attack.

The hop‐based localisation algorithm uses hop‐by‐hop propagation to establish node‐to‐anchor distance estimation, which does not require costly and complicated ranging hardware. This helps boost system performance, while minimising the cost of localising the nodes within the network. However, the application of hop‐based localisation algorithms is restricted due to their dramatic accuracy degradation in irregular network, which is mainly caused by the large error of distance estimation. The authors find that the error variance of the estimated distance increases as the hop count increases, i.e. there is a heteroscedasticity problem in the distance estimation process, which will affect the location estimation. In this study, by exploring the error during the location estimation, they aim to find and employ the optimal weighted function to improve localisation accuracy. A geometric constraint algorithm is also devised to correct the incorrectly estimated location by mitigating the adverse effects from flip ambiguity. By combining the optimal weighted function and the geometric constraint algorithm, a novel hop‐based localisation algorithm is proposed in this study. Both the theoretical analysis and experimental results show that the proposed method has not only maintained the economic characteristics of hop‐based localisation, but also has the high localisation accuracy where it can be adapted to various networks with different node distributions.

Images captured by camera may contain scattered particles that reduce the quality of the image indirectly. This point motivate researchers contribute the image enhancement and recovery algorithms but the outcome may distort with halo, artefact textures and low light scene. Hence, the potential information contain in the images may eliminate accidently. This study maintains the structure of the scene like texture to keep the potential information by using illumination estimation and remain the colour range accordingly. Experimental result did to the sample images obtain the good clear image, edges ratio (e), the gradient ratio (g), the percentage of number of saturated pixels (E), and structure similarity index metric (SSIM).