Tamper Localization Research Articles

Improved copy move forgery detection method via L*a*b* color space and enhanced localization technique

The wide availability of easy-to-use image editors has made the authenticity of images questionable. Copy-move is one of the most applied forgery types. A new copy-move forgery detection and localization technique independent from the characteristics of the forged regions is proposed in this paper. SIFT keypoints are obtained from CLAHE applied sub-images extracted from the input image by using RGB and L*a*b* color-spaces. Keypoint matching is realized on the sub-images and duplicated regions are determined roughly to create roughly marked image R. RANSAC is also applied in this stage and generated homography matrix is used to construct transformed roughly marked image R′. The method extracts DCT based features from R and R′ to localize exact borders of the tampered regions on the roughly determined areas by using a dynamic threshold. The proposed method has a new suggestion to determine the threshold dynamically. Tamper localization procedure also utilizes from morphological operations (chosen depending on the characteristic of the image) and Connected Component Labeling to determine exact forge boundaries. Results indicate that the proposed method has a better performance compared with state-of-the-art copy-move forgery detection methods on the GRIP dataset. Scaling attack performance of the method is especially better than similar works as shown in the results.

A novel color image encryption algorithm based on image hashing, 6D hyperchaotic and DNA coding

In order to improve the key space of color image encryption algorithm, the sensitivity to the contents of plain images, the robustness against various types of known attacks, and to achieve the tamper location analysis, a novel color image encryption algorithm based on image hashing, six-dimensional (6D) hyperchaotic and dynamic DNA coding is proposed. Firstly, the color image is pre-processed and the hash sequence is extracted by image hashing algorithm which is used as the initial value and control parameter of chaotic system. Secondly, three color channels of the color image RGB are synthesized into a two-dimensional matrix and the pixels replacement are performed by using the improved two-dimensional chaotic map. Finally, a 6D hyperchaotic system is used to generate random sequences for DNA dynamic coding and arithmetic operations of color images, the encrypted image is obtained. The experimental results show that, compared with the existing methods, the proposed algorithm has a large enough key space, better plain-image sensitivity, better statistical and differential characteristics, as well as can resistant various forms of attacks such as noise and cropping, and the tampering image can be tamper-located analyzed, which has good security and strong robustness.

Replacing DWT with DTCWT in blind image rotation angle estimation

During the image tampering, rotation is often involved to make the forgery more convincing. Hence, estimating the rotation angle accurately and locally is of forensic importance. Recently, a novel rotation angle estimation scheme was proposed based on linear pattern (LP), achieving state of the art performance especially in the case when the rotation angle is small. However, due to the limitations of the involved discrete wavelet transform (DWT), the existing LP based method cannot always accurately detect rotated linear pattern from a rotated image. To fill this gap, we propose to extract the rotated LP using dual tree complex wavelet transform (DTCWT). Thanks to the good directional selectivity of DTCWT, the proposed method can extract the LP more accurately. Experiments show that our proposed method performs better than the state of the art in rotation angle estimation, and is also a promising forensic tool for tampering localization.

A hybrid-Sudoku based fragile watermarking scheme for image tampering detection

Protection of intellectual property rights has become one of the focuses of social concerning. To reduce those disputations, the watermark is implanted into the media by the content owner to declare original copyright. Among which, the high payload can achieve the accurate tampering localization, but maybe bring low visual quality watermarked image. Both accurate tampering localization and high watermarked image quality seem contradictory. For this, this paper proposes a hybrid-Sudoku based fragile watermarking scheme for digital image tampering detection. The hybrid-Sudoku based scheme provides a double perspective mechanism to embed the watermark. In the first perspective of the Sudoku, the watermark is virtually embedded into each pixel pair, resulting in the temporary coordinate information. Then, the temporary coordinate information is concealed into cover image based on the second perspective of the Sudoku. Finally, several common attacks are utilized to evaluate the tampering detection performance of the proposed method. Experimental results show that the proposed scheme can achieve a considerable accuracy in tampering localization and provide the satisfactory visual quality of watermarked image, with PSNR of 47.80 dB. Additionally, the design enhances the security and imperceptive of the hidden watermark.

Color image watermarking for content authentication and self-restoration applications based on a dual-domain approach

Digital image watermarking has been witnessed as a powerful tool that can be used in image ownership identification, copyright protection and content authentication applications. In this paper, a dual-domain watermarking scheme for digital image authentication with self-recovery capabilities is proposed. The proposed scheme has a high ability to recover tampered image regions while pertaining high watermarking imperceptibility and high robustness under various types of attacks. The proposed scheme employs two watermarks: 1) content-dependent, and, 2) content-independent, where the content-dependent watermark contains two-bit sequences for authentication and recovery operations. The authentication bits are generated based on the singular value decomposition (SVD) of each block, while the recovery bits are generated from the average value within selected sub-blocks. The independent watermark is embedded using the Discrete Cosine Transform (DCT), whereas, the dependent watermark is embedded directly into the first and second least significant bits (LSB) of the image pixels. The developed dual-domain watermarking scheme has exhibited high robustness performance against various attacks with high imperceptibility and watermarking capacity as well. For authentication purposes, the proposed scheme incorporated three developed measures to detect the authenticity of the probe image, and, to accurately localize tampered regions. The experimental results have shown that the proposed scheme has a high imperceptibility, compared to other existing schemes, and can effectively distinguish malicious from incidental attacks with accurate tampering localization. Moreover, the proposed scheme exhibits high performance against moderate-to-strong incidental attacks such as noise and low-quality JPEG attacks.

Image Tampering Localization Using Demosaicing Patterns and Singular Value Based Prediction Residue

Almost all image sensors measure only one color per pixel through the color filter array. Missing pixels are estimated using a demosaicing process. For this reason, a demosaiced image leaves a particular trace. When an image is manipulated or tampered, the demosaicing trace can be changed. This change can serve as a basic clue for detecting or localizing image tampering. Demosaicing pattern-based tampering localization algorithms require a re-interpolation process, and the prediction residue between the given image and the re-interpolated image is commonly used to localize tampered regions. However, the prediction residue is not always valid because the demosaicing interpolation kernel cannot be known, which deteriorates the localization performance. This paper presents an effective re-interpolation process using singular value decomposition for an unknown demosaicing method. First, the green channel of the given image is decomposed into four sub-images according to the Bayer pattern. For a small block of each sub-image, the singular value decomposition is performed. The prediction residue is obtained by reconstructing the image block after removing the largest singular value. The feature to localize the forged regions is extracted by the logarithm ratio of the prediction residue variance. The proposed method does not require any statistical model for the extracted feature, because the prediction residue is more accurate than that of conventional methods. We perform intensive experiments for three test datasets and compare the proposed method with state-of-the-art tampering localization methods, the results of which indicate that the proposed scheme outperforms existing approaches.

Image Tampering Localization Using a Dense Fully Convolutional Network

The emergence of powerful image editing software has substantially facilitated digital image tampering, leading to many security issues. Hence, it is urgent to identify tampered images and localize tampered regions. Although much attention has been devoted to image tampering localization in recent years, it is still challenging to perform tampering localization in practical forensic applications. The reasons include the difficulty of learning discriminative representations of tampering traces and the lack of realistic tampered images for training. Since Photoshop is widely used for image tampering in practice, this paper attempts to address the issue of tampering localization by focusing on the detection of commonly used editing tools and operations in Photoshop. In order to well capture tampering traces, a fully convolutional encoder-decoder architecture is designed, where dense connections and dilated convolutions are adopted for achieving better localization performance. In order to effectively train a model in the case of insufficient tampered images, we design a training data generation strategy by resorting to Photoshop scripting, which can imitate human manipulations and generate large-scale training samples. Extensive experimental results show that the proposed approach outperforms state-of-the-art competitors when the model is trained with only generated images or fine-tuned with a small amount of realistic tampered images. The proposed method also has good robustness against some common post-processing operations.

An Innovative Approach to Solve Healthcare Issues Using Big Data Image Analytics

The increasing adoption of transmission of medical images through internet in healthcare has led to several security threats to patient medical information. Permitting quiet data to be in peril may prompt hopeless harm, ethically and truly to the patient. Accordingly, it is important to take measures to forestall illicit access and altering of clinical pictures. This requests reception of security components to guarantee three fundamental security administrations – classification, content-based legitimacy, and trustworthiness of clinical pictures traded in telemedicine applications. Right now, inside created symmetric key cryptographic capacities are utilized. Pictorial model-based perceptual image hash is used to provide content-based authentication for malicious tampering detection and localization. The presentation of the projected algorithm has been evaluated using performance metrics such as PSNR, normalized correlation, entropy, and histogram analysis, and the simulation results show that the security services have been achieved effectively.

Blind multipurpose watermarking with insertion of a single watermark: a generic construction based on verifiable threshold secret sharing

Currently, the existing literature on multipurpose watermarking employs multiple watermarks for simultaneous achieving of multiple security objectives. This approach can be problematic since a watermark targeting tampers might fail to detect tampering of another watermark inserted for copyright violation. Moreover, most of the current schemes follow a non-blind approach where the original watermark is needed for authentication. A question that naturally arises is whether multipurpose watermarking can be realised with the insertion of a single watermark in a blind way or not. The goal of the authors study is to provide an affirmative answer to this important question. They show how a cryptographic primitive called verifiable threshold secret sharing can be used to come up with a generic construction for blind multipurpose watermarking which inserts a single watermark into the host image for simultaneous achieving of copyright protection, authentication, and tamper localisation. The generic property of the proposed scheme provides flexibility for choosing the embedding/extraction of the watermark based on the desired level of fidelity, robustness and capacity. Experimental results are provided to confirm the superiority of their proposed technique as compared to existing approaches.

Multi-format speech BioHashing based on energy to zero ratio and improved LP-MMSE parameter fusion

In order to solve the problems of poor security and small application scope of speech content authentication, and to improve the robustness, discrimination and real-time performance of speech authentication, a multi-format speech BioHashing algorithm based on energy to zero ratio and improved linear prediction minimum mean square error (LP-MMSE) parameter fusion is proposed. Firstly, the algorithm extracts the short-term logarithmic energy, zero-crossing rate and the covariance method’s LP-MMSE of speech signal to be processed. Then, the time-frequency parameters are fused, and the fused feature vector and the orthogonal normalized random matrix of the key control are generated into BioHashing sequences through the inner product form. Finally, the BioHashing is encrypted by equal-length scrambling using henon chaotic map. The experimental results show that the proposed algorithm not only has the characteristics of good discrimination, strong robustness, good security, high real-time performance and wide application range, but also realizes the detection and localization of small-scale tampering of speech through minimum code distance (MCD) algorithm. At the same time, the algorithm also validates the unidirectionality of BioHashing with trapdoor by comparative difference method.

DWFCAT: Dual Watermarking Framework for Industrial Image Authentication and Tamper Localization

The image data received through various sensors are of significant importance in Industry 4.0. Unfortunately, these data are highly vulnerable to various malicious attacks during its transit to the destination. Although the use of pervasive edge computing (PEC) with the Internet of Things (IoT) has solved various issues, such as latency, proximity, and real-time processing, but the security and authentication of data between the nodes is still a significant concern in PEC-based industrial-IoT scenarios. In this article, we present “DWFCAT,” a dual watermarking framework for content authentication and tamper localization for industrial images. The robust and fragile watermarks along with overhead bits related to the cover image for tamper localization are embedded in different planes of the cover image. We have used discrete cosine transform coefficients and exploited their energy compaction property for robust watermark embedding. We make use of a four-point neighborhood to predict the value of a predefined pixel and use it for embedding the fragile watermark bits in the spatial domain. Chaotic and deoxyribonucleic acid encryption is used to encrypt the robust watermark before embedding to enhance its security. The results indicate that DWFCAT can withstand a range of hybrid signal processing and geometric attacks, such as Gaussian noise, salt and pepper, joint photographic experts group (JPEG) compression, rotation, low-pass filtering, resizing, cropping, sharpening, and histogram equalization. The experimental results prove that the DWFCAT is highly efficient compared with the various state-of-the-art approaches for authentication and tamper localization of industrial images.

Image Security using Self embedding Fragile Watermarking Method

Rapid development in technology to provide security to data in the form of images is a major issue. So to provide security to the original image, watermark image embedded in it. In this paper we use self embedded watermark using fragile watermark technique. Authenticity of an image can be tested using block based technique of self embedding fragile watermarking; to represent the entire image the feature image watermark is used. In each 2x2non overlapping block four authentication bits and eight recovery bits are generated. In each block three least significant bits are embedded with authentication bits and recovery bits are embedded in the three least significant bits of the mapped block This paper mainly summarizes the Selection of image, method of watermark insertion, detection and tamper localization and recovery procedure. The experimental results of this proposed method shows visual quality of image recovery better than some of the schemes.

Multipurpose Watermarking Algorithm for Medical Images

Considering the existing medical image watermarking algorithms, a single function often has limitations, and a multipurpose watermarking algorithm for medical images is proposed. First, medical images are divided into regions of interest (ROIs) and regions of noninterest (RONIs). Then, the authentication watermark produced for each subblock of the ROI is embedded into the corresponding mapping subblock. The visible watermark is embedded into the RONI, and, finally, the watermark information and constructed authentication information in each subblock of the ROI are embedded into the corresponding RONI subblock. Simulation results show that the embedded visible watermark can protect and facilitate medical image management. In addition, the proposed algorithm has strong robustness and very good visual quality. It can simultaneously realize copyright protection and content authentication and also has high tamper localization capability.

Semi Fragile Watermarking with Tamper Localization and Recovery using AMBTC Method

The watermarking scheme in digital media communication has become an essential tool in helping content creators prove ownership if any dispute arises in copyright infringement. In this paper, Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) is performed in the watermarking process which improves the authentication of the image and the detection of the tampered region. The semi-fragile watermarking scheme provides robustness to the watermark during extraction process even after the unintentional compression attacks like JPEG compression. The watermark payload is significantly lowered in order to increase the quality of the image. The recovery is done using the absolute moment block truncation coding (AMBTC) of the image in the untampered region. Thus, both the mean and first absolute moment are used in recovering the tampered regions in the watermarked image.

An effective image self-recovery based fragile watermarking using self-adaptive weight-based compressed AMBTC

The quality of the watermarked image is degraded by introducing a large amount of the watermark, which also draws more attention of malicious attackers. Therefore, it is important to improve the quality of a watermarked image and improve the restoration capability of a tampered image. For this, a novel self-recovery based fragile watermarking scheme is proposed in this paper. To improve the watermarked image quality, a bit-reduction based AMBTC technology is employed to generate a watermark with fewer bits. The watermark is then embedded into the original image using turtle shell based data hiding technique. In the tampering detection phase, the high accuracy for tampering localization is achieved employing a two-level tampering detection strategy. Additionally, an effective self-adaptive weight-based recovery algorithm and an image inpainting algorithm are sequentially employed to provide improved recovered image quality. The experimental results show that the watermarked images appear to demonstrate higher quality (up to 49.76 dB), and the average PSNR of recovered images can be up to 34.65 dB, which is higher than that of the state-of-the-art methods.

Video tampering dataset development in temporal domain for video forgery authentication

Videos are tampered by the forgers to modify or remove their content for malicious purpose. Many video authentication algorithms are developed to detect this tampering. At present, very few standard and diversified tampered video dataset is publicly available for reliable verification and authentication of forensic algorithms. In this paper, we propose the development of total 210 videos for Temporal Domain Tampered Video Dataset (TDTVD) using Frame Deletion, Frame Duplication and Frame Insertion. Out of total 210 videos, 120 videos are developed based on Event/Object/Person (EOP) removal or modification and remaining 90 videos are created based on Smart Tampering (ST) or Multiple Tampering. 16 original videos from SULFA and 24 original videos from YouTube (VTD Dataset) are used to develop different tampered videos. EOP based videos include 40 videos for each tampering type of frame deletion, frame insertion and frame duplication. ST based tampered video contains multiple tampering in a single video. Multiple tampering is developed in three categories (1) 10-frames tampered (frame deletion, frame duplication or frame insertion) at 3-different locations (2) 20-frames tampered at 3- different locations and (3) 30-frames tampered at 3-different locations in the video. Proposed TDTVD dataset includes all temporal domain tampering and also includes multiple tampering videos. The resultant tampered videos have video length ranging from 6 s to 18 s with resolution 320X240 or 640X360 pixels. The database is comprised of static and dynamic videos with various activities, like traffic, sports, news, a ball rolling, airport, garden, highways, zoom in zoom out etc. This entire dataset is publicly accessible for researchers, and this will be especially valuable to test their algorithms on this vast dataset. The detailed ground truth information like tampering type, frames tampered, location of tampering is also given for each developed tampered video to support verifying tampering detection algorithms. The dataset is compared with state of the art and validated with two video tampering detection methods.

Embedding in medical images: an efficient scheme for authentication and tamper localization

In e-healthcare applications integrity of the received information is of prime importance for ensuring the accurate diagnosis. The integrity of electronic medical record (EMR) is possible only when the medical images and other relevant data received are tamper free. Reversibility of medical images after certain degree of processing is always a desired property in medical images as it aids proper diagnosis. This paper proposes a novel reversible image authentication (RIA) scheme for tamper detection and authentication of medical images. In the proposed RIA scheme, the medical image is divided into 4 × 4 blocks followed by embedding fragile watermark bit (for authentication) in each of these blocks. Along with authentication, the localization of tamper is achieved accurately by using LSB embedding along with mean modification approach. The security of the watermark has been enhanced with Arnold cat map, Gray coding and AES-128 encryption. The experimental results show that the scheme offers better fragility against all intentional/unintentional signal processing attacks. The comparison results between proposed RIA scheme and similar state-of-the-art schemes show superiority of our scheme in terms of imperceptivity, fragility and tamper localization. For a payload of 16 kb, the average PSNR achieved for 50 Gray scale images of size 512 × 512 is more than 47 dB. In addition, the scheme offers very less complexity; the embedding and extraction times are around 0.6 s and 0.5 s respectively. Given the features of proposed scheme it could serve as a potential candidate for transfer of EMR in an e-healthcare system.

Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion

The protection of database systems content using digital watermarking is nowadays an emerging research direction in information security. In the literature, many solutions have been proposed either for copyright protection and ownership proofing or integrity checking and tamper localization. Nevertheless, most of them are distortion embedding based as they introduce permanent errors into the cover data during the encoding process, which inevitably affect data quality and usability. Since such distortions are not tolerated in many applications, including banking, medical, and military data, reversible watermarking, primarily designed for multimedia content, has been extended to relational databases. In this article, we propose a novel prediction-error expansion based on reversible watermarking strategy, which not only detects and localizes malicious modifications but also recovers back the original data at watermark detection. The effectiveness of the proposed method is proved through rigorous theoretical analysis and detailed experiments.

High-Resolution Remote Sensing Image Integrity Authentication Method Considering Both Global and Local Features

Content integrity of high-resolution remote sensing (HRRS) images is the premise of its usability. Existing HRRS image integrity authentication methods are mostly binary decision-making processes, which cannot provide a further interpretable information (e.g., tamper localization, tamper type determination). Due to this reason, a robust HRRS images integrity authentication algorithm using perceptual hashing technology considering both global and local features is proposed in this paper. It extracts global features by the efficient recognition ability of Zernike moments to texture information. Meanwhile, Features from Accelerated Segment Test (FAST) key points are applied to local features construction and tamper localization. By applying the concept of multi-feature combination to the integrity authentication of HRRS images, the authentication process is more convincing in comparison to existing algorithms. Furthermore, an interpretable authentication result can be given. The experimental results show that the algorithm proposed in this paper is highly robust to the content retention operation, has a strong sensitivity to the content changing operations, and the result of tampering localization is more precise comparing with existing algorithms.

A secure image authentication scheme based on dual fragile watermark

Both security and tamper localization are essential for fragile watermarking techniques. Embedded fragile watermark should be sensitive enough to cover images. But high sensitivity maybe bring inaccurate tamper localization, and both high sensitivity and accurate tamper localization seem contradictory. This paper proposes a watermark scheme based on dual fragile watermark: diffusion watermark and authentication watermark. The diffusion watermark is determined by a cover image, a secret key and two random numbers via nonlinear transformations, and the authentication watermark is generated from the cover image, the diffusion watermark and another secret key. The diffusion watermark and the authentication watermark have high sensitivity to cover images and at meantime the authentication watermark can verify the integrity of images and localize tampered area. The scrambled authentication watermark and the diffusion watermark are arbitrarily embedded into the two lowest significant bit layers of the cover image through a random sequence controlled by a secret key. The design aims to enhance the security of fragile watermarking, and the statistical results and security analysis show that this scheme can resist chosen cover-image attacks.