Image Content Authentication Research Articles

Perceptual authentication hashing for digital images based on multi-domain feature fusion

In recent decades, numerous perceptual authentication hashing schemes have been proposed for image content authentication. However, most of these schemes are based on a single spatial or transform domain, and they fail to provide satisfactory robustness and discrimination capability when facing complex image manipulations in real scenarios. In this work, we present a perceptual authentication hashing scheme based on Convolutional Neural Network (CNN) that leverages both spatial and frequency domains. Specifically, we construct two separate streams for spatial and transform domains. Then, we introduce a feature fusion module to merge the features of these two domains to generate a hash sequence. Besides, we design a frequency domain channel filter and a frequency attention module for the frequency domain, and introduce a frequency domain loss function to optimize model training. Based on large-scale testing datasets, our scheme demonstrates superior performance compared to state-of-the-art schemes, as evidenced by Receiver Operating Characteristic (ROC) curves.

Security analysis and improvement of DWFCAT

With the rapid development of Internet technology, the copyright protection and authentication of multimedia data have attracted more and more attention. Recently, a dual watermarking framework for industrial image content authentication and tampering localization (DWFCAT) has been proposed, in which the main innovation is the double encrypted robust watermark is embedded into the transform domain by exploiting the DCT energy compression characteristics and block coefficient correlation mechanism, the fragile watermark is embedded in the spatial domain to ensure data authentication and tamper location. However, through security analysis, we found that DWFCAT has security holes, the dual encryption algorithm of the robust watermarks cannot resist KPA attacks and prevent robust watermarks from being damaged, stolen, and replaced, even when the fragile watermark is unaware. Theoretical analysis and simulation results verify the effectiveness of the method. To improve the security of the original watermarking scheme and the ability to tampering with location, and restore the robust watermark that has been tampered with, an improved scheme is also given in this paper.

A reversible watermarking for image content authentication based on wavelet transform

A reversible watermarking for image content authentication based on wavelet transform

Security Analysis and Improvement of Dual Watermarking Framework for Multimedia Privacy Protection and Content Authentication

The demand for using multimedia network infrastructure for transmission grows with each passing day. Research scholars continue to develop new algorithms to strengthen the existing network security framework in order to ensure the privacy protection and content authentication of multimedia content and avoid causing huge economic losses. A new technology for multimedia image copyright protection and content authentication has been proposed. The innovations lie in the use of an inter-block coefficient difference algorithm to embed robust watermarking in the transform domain, and the same fragile watermark is embedded twice in the spatial domain so that any tiny tampering can be identified and located. A new encryption algorithm combined with Arnold transform is used to encrypt data before embedding. However, some security vulnerabilities were found, and successful cryptanalysis and attack were conducted. Subsequently, an improved scheme was proposed to improve the security and tamper detection ability of the original watermarking scheme and recover the tampered robust watermark. The results show that the improved scheme is safer and more reliable and shows good performance in tampering detection and the recovery robustness of the watermark.

Image Perceptual Hashing for Content Authentication Based on Geometric Invariant Vector Distance

Image perceptual hashing is broadly applied in image content authentication, recognition, retrieval, and social media hotspot event detection. An image authentication algorithm is put forward based on the Itti visual saliency model and geometric invariant vector distance. To begin with, the image is preprocessed and weighted by the Itti model and contourlet transform. After that, the weighted image is randomly divided into blocks, and the image feature vector is constructed by calculating the geometric invariant vector distance on both Hu invariant moment vector and maximum singular value vector of the random blocks. In the end, the feature vector is quantized and encrypted to generate the ultimate hash. Experimental results illustrate that when the threshold T = 70, the true positive rate P T P R for duplicate images stands at 0.96574, while the false rate P F P R of different images is merely 0.0224, with the total error rate reaching the minimum value (0.0566). Furthermore, the AUC value of the proposed algorithm is 0.9951, which is higher than that of the comparison algorithms, indicating that the algorithm has better performance than other state-of-the-art algorithms in terms of various visual content-preserving attacks.

Fragile Watermark in Medical Image Based on Prime Number Distribution Theory.

The research of medical image in the field of anti-counterfeiting and authentication plays a crucial role in the development of hospital digitization. In this paper, a new fragile medical watermarking scheme is proposed using the prime number distribution theorem, chaotic mapping, and Hash. Firstly, an approximate pixel set is constructed according to the distribution of prime numbers, and then the parity of the pixel value is re-granted with chaotic mapping, and Hash. The embedding and extraction of the watermark are done by using logical operations to adjust the pixel value according to the parity of the pixel value and the number of prime numbers contained in the pixel value. The experimental results demonstrate that the proposed scheme is imperceptible, efficient, and safe. Compared with the existing methods, the proposed scheme achieves the binding of medical image and patient information, as well as exhibits excellent detection and positioning capability, and will have good application prospects in medical image content authentication and tampering detection.

A survey on fragile watermarking based image authentication schemes

Ensuring the image content authentication is a necessity need when images are used as supporting evidence in critical applications such as law enforcement, medical diagnosis, news reporting, and forensic investigation. Fragile watermarking is an effective solution for ensuring image content authentication. This paper presents a survey on fragile watermarking schemes for tamper localization and self-recovery. The characteristics and general framework are included to get an overview of these schemes. A brief review and comparison of various fragile watermarking schemes along with their merits and limitations are also given. The observations drawn from the comparative study are included to aid further research in this area. In addition to this, experimental evaluation of state-of-the-art tamper localization and self-recovery schemes in terms of watermarked image quality, tamper localization accuracy, and recovery capability is carried out.

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.

Fusion of Handcrafted and Deep Features for Forgery Detection in Digital Images

Content authentication of digital images has captured the attention of forensic experts and security researchers due to a multi-fold increase in the dissemination of multimedia data through the open and vulnerable Internet. Shrewd attackers successfully devise novel ways to challenge state-of-art forensic tools used for forgery detection in digital images. Feature engineering approaches have yielded up to 97% accuracy on benchmarked datasets. Deep learning approaches have shown promising results in various image classification problems but cannot find hidden patterns in digital images, which can reliably detect image forgeries. State-of-art accuracy of deep learning approaches for forgery detection is up to 98% on benchmarked datasets. The objective of the proposed approach is to further escalate the detection accuracy, pushing it near 100%. In this paper, a synergy of handcrafted features based on color characteristics and deep features using the image’s luminance channel is employed to mine patterns responsible for accurate forgery detection. In the first Stream, 648-D Markov-based features are computed from the quaternion discrete cosine transform of the image. In the second Stream, the luminance channel of YCbCr colorspace is used to extract the Local Binary Pattern of the image. Further, local binary feature maps are fed to the pre-trained ResNet-18 model to obtain a 512-D feature vector called ’ResFeats’ from the last layer of the model’s convolutional base portion. The handcrafted features from Stream I and ResFeats from Stream II are combined to form an 1160-D feature vector. Further, classification is performed using a shallow neural network, and the method is tested on CASIA v1 and CASIA v2 datasets. The accuracy of the proposed fusion-based approach is 99.3% on benchmark datasets.

Efficient and secure image authentication with robustness and versatility

Image authentication is the technology of verifying image origin, integrity and authenticity. A rich stream of research on image authentication has shown various trade-off among four favorable features, namely robustness, security, versatility and efficiency. Image data authentication has the highest level of security but provides no robustness/versatility. Image content authentication from robust hashing keeps robust to limited types of operations, and as a result its versatility is not satisfactory. Existing designs of image content authentication from advanced cryptographic primitives achieve robustness, security and versatility, at the cost of low efficiency. In this paper, we present a new design of image authentication with an improved trade-off among the aforementioned features. Our versatile design is robust to a number of predefined image processing operations. Its security can be reduced to q-strong Diffie-Hellman (q-SDH), a complexity problem used by existing cryptographic algorithms. From the aspect of efficiency, the new design has a constant-size authentication overhead (⩽ 2 kB) and a constant verification time (around 0.05 s). While the time of generating authentication overhead increases linearly with the number of permissible editing operations, it only takes around 0.33 s for 1000 types of permissible operations. We believe the new design will facilitate image applications where trustworthy image editing is required.

A novel deep learning framework for copy-moveforgery detection in images

In this era of technology, digital images turn out to be ubiquitous in a contemporary society and they can be generated and manipulated by a wide variety of hardware and software technologies. Copy-move forgery is considered as an image tampering technique that aims to generate manipulated tampered images by concealing unwanted objects or reproducing desirable objects within the same image. Therefore, image content authentication has become an essential demand. In this paper, an innovative design for automatic detection of copy-move forgery based on deep learning approaches is proposed. A Convolutional Neural Network (CNN) is specifically designed for Copy-Move Forgery Detection (CMFD). The CNN is exploited to learn hierarchical feature representations from input images, which are used for detecting the tampered and original images. The extensive experiments demonstrate that the proposed deep CMFD algorithm outperforms the traditional CMFD systems by a considerable margin on the three publicly accessible datasets: MICC-F220, MICC-F2000, and MICC-F600. Furthermore, the three datasets are incorporated and joined to the SATs-130 dataset to form new combinations of datasets. An accuracy of 100% has been achieved for the four datasets. This proves the robustness of the proposed algorithm against a diversity of known attacks. For better evaluation, comparative results are included.

Detecting similarity in color images based on perceptual image hash algorithm

Due to the ever-increasing digitization, the authentication of digital media content is becoming more and more important. Authentication, in general, means deciding whether a digital media is authentic or not, that is, if it matches a given original image. The authentication depends heavily on the type of the digital media, in other words, it is important that every single bit exactly matches the original digital media. Cryptographic hash functions are adequate for such tasks; in this case, a robust hashing is a technology as a change tolerant alternative to cryptographic hashes. Since normal cryptographic hashing methods are error prone to image processing techniques, perceptual hashing is a promising solution to image content authentication. However, conventional image hash algorithms only offer a limited authentication level for overall protection of the content. When intensity components of the color image are used, it is meant that the image is converted to only hashing functions image to produce strong adaptive hashes and that is lead to inadequate recognition abilities.In this paper, a hash function for color images has been introduced and it is considered robust against global changes inside the image contents. A good discrimination achievement has been obtained since it takes all constituents of the color images into account. Firstly, the input image is resized or re-scaled into a fixed size that is predefined earlier. Secondly, converting the RGB image to HSI and YCbCr color spaces, respectively. The purpose of this process is to extract local color features of the RGB image. Thereafter, the YCbCr image is divided into blocks for computing mean and variance of each block component. Finally, the hash values for both source and attack images are calculated using Euclidian distances formula to measure the difference between them.Experiments are lead to validate the efficiency of the suggested perceptual robustness hash function. Different image operations; brightness, darkness and rotating; were used to test the robustness of the image hash functions. Besides, different evaluated metrics, such as Mean Square Error (MSE) and Peak to Signal to Noise Ratio (PSNR), were used to measure the performance of the hash function. The obtained results from the perceptual image hash algorithm matched up to 98% between the source image and their corresponding attack image.

Blind Image Watermark Decoder in UDTCWT Domain Using Weibull Mixtures-Based Vector HMT

As one promising solution, digital watermarking has been proposed to resolve image copyright protection and content authentication, and has been applied successfully in many fields. Owing to their excellent description capability and invariance property, statistical models have become a popular tool for the image watermarking resulting in favorable trade-offs among imperceptibility, robustness and data payload. By modeling the robust undecimated dual tree complex Wavelet transform (UDTCWT) coefficient magnitudes with the Weibull mixtures based vector hidden Markov trees (HMT) and employing maximum likelihood (ML) test criterion, we propose a new image watermarking approach in UDTCWT domain in this paper. Our image watermarking approach consists of two parts, namely, embedding and extracting. In the embedding process, we compute the robust UDTCWT coefficient magnitudes with UDTCWT domain real/imaginary parts, and insert the digital watermark into the significant UDTCWT coefficient magnitude subband. In the extracting phase, robust UDTCWT coefficient magnitudes are firstly modeled by employing the Weibull mixture-based vector HMT, where the statistical properties of UDTCWT magnitudes are captured accurately. Then the expectation/conditional maximization (ECM) approach is introduced to estimate the statistical model parameters. Finally, an image watermark decoder for multiplicative watermarking is developed using the Weibull mixtures based vector HMT and ML test. The experiments show that the proposed method not only improves the imperceptibility, but also increases the robustness performance and outperforms state-of-the-art methods on a set of standard test images.

Image alignment based perceptual image hash for content authentication

Perceptual image hash is an emerging technology that is closely related to many applications such as image content authentication, image forging detection, image similarity detection, and image retrieval. In this work, we propose an image alignment based perceptual image hash method, and a hash-based image forging detection and tampering localization method. In the proposed method, we introduce an image alignment process to provide a framework for image hash method to tolerate a wide range of geometric distortions. The image hash is generated by utilizing hybrid perceptual features that are extracted from global and local Zernike moments combining with DCT-based statistical features of the image. The proposed method can detect various image forging and compromised image regions. Furthermore, it has broad-spectrum robustness, including tolerating content-preserving manipulations and geometric distortion-resilient. Compared with state-of-the-art schemes, the proposed method provides satisfactory comprehensive performances in content-based image forging detection and tampering localization.

A watermarking scheme based on rotating vector for image content authentication

Semi-fragile watermarking technique for digital image, as a technology for content authentication, aims at telling malicious tampering from content-preserving operators. However, with the resolution of imaging sensors increasing and the explosive growth of digital images on the internet, before authorization, watermarked images tend to undergo such double-compression environments as: first compression (JPEG/JPEG2000) for release, decoding, application processing (conventional signal processing such as nosing, filtering, cropping, and scaling/security attack/malicious tampering), and second compression (JPEG2000/JPEG) for release again. In this paper, based on rotating vector, we propose a novel watermarking expression method that can describe carrier semantics to a certain extent and its modulation algorithm for digital image, and analyze the stability of the watermarked data theoretically. Then, a semi-fragile watermarking scheme is proposed for image content authentication to effectively distinguish malicious content manipulation from content-preserving operations in the double-compression application environment, which expands the application scope of content authentication based on watermarking technology.

A watermarking algorithm for image content authentication in double-compression environment

Malicious tampering of digital image content may lead to serious consequences. As image resolution increases and its circulations on the network grows rapidly, images undergo double compression in the following environment: compression (JPEG/JPEG2000) for first release, decoding, application processing (conventional signal processing/security attacks/malicious content tampering), and compression (JPEG2000/JPEG) for rerelease before detection. Effectively determining whether the image content has been tampered and to locate the tampering position in a double-compression environment is an urgent problem. In this paper, a novel watermark expression method based on rotating vector and its modulation algorithm is proposed. Based on this method, a semi-fragile watermarking scheme is established for the image content authentication. The stability of watermarked data is analyzed theoretically, providing the watermark scheme with a theoretical basis. The authentication schemes with feature extraction and reconstruction, watermark embedding and extraction, and tamper detection and localization are mainly elaborated. The robustness of watermark, its security, and related detection performance are analyzed. Theoretical analysis and experiments show that the scheme features a good watermark transparency, good robustness, and stable distribution for different attacks and can effectively distinguish malicious tampering from content-preserving operators and locate tampering area under double-compression environment. In addition, the proposed scheme can resist watermark attacks, collage attacks, and forge attacks. Compared with related schemes, the proposed scheme has superior comprehensive performance and is suitable for content authentication in double-compression environment, which expands the application scope of watermark-based content authentication.

Dual watermarking framework for privacy protection and content authentication of multimedia

In the current multimedia networked infrastructure, privacy breaches due to cyber-attacks result in huge economic losses. Despite these threats there is ever increasing demand to share data over various insecure networks for accomplishment of numerous tasks. In such a scenario there is a greater need to develop new algorithms for strengthening the existing cybersecurity frameworks, ensure security, privacy, copyright protection and authentication of data. In this paper a new technique for copyright protection, data security and content authentication of multimedia images is presented. The copyright protection of the media is taken care of by embedding a robust watermark using an efficient inter-block coefficient differencing algorithm and is proposed as Scheme I. Scheme II has been utilized to ensure both copyright protection, and content authentication. The authentication of the content has been ensured by embedding a fragile watermark in spatial domain while as copyright protection has been taken care of utilizing a robust watermark. In order to thwart an adversary and ensure that it has no access to actual embedded data, we make use of a novel encryption algorithm in conjunction with Arnold transform to encrypt data prior to its embedding. The experimental results reveal that the proposed framework offers high degree of robustness against single/dual/triple attacks; with Normalized Correlation (NCC), more than or equal to 0.95. Besides, the fragile watermark embedding makes the system capable of tamper detection and localization with average BER more than 45% for all signal processing/geometric attacks. The average PSNR achieved for both schemes is greater than 41 dB. A comparison of the proposed framework with various state-of-the-art techniques demonstrate its effectiveness and superiority.

Fingerprint Image Hashing Based on Minutiae Points and Shape Context

Fingerprint minutiae is the unique representation of fingerprint image feature points as terminations and bifurcations. Therefore, generating a hash signature from these feature points will unarguably meet the desired properties of a robust hash signature and which will accurately fit in for fingerprint image content authentication purposes. This article proposes a novel minutiae and shape context-based fingerprint image hashing scheme. Fingerprint image minutiae points were extracted by incorporating their orientation and descriptors, then embedded into the shape context-based descriptors in order to generate a unique, compact, and robust hash signature. The robustness of the proposed scheme is determined by performing content preserving attacks, including noise addition, blurring and geometric distribution. Efficient results were achieved from the given attacks. Also, a series of evaluations on the performance comparison between the proposed and other state-of-art schemes has proven the approach to be robust and secure, by yielding a better result.

Authenticity and copyright verification of printed images

Perceptual image hashing and digital watermarking are two of the extensively investigated techniques for content authentication and copyright verification of digital images, respectively. One of the significant challenges of perceptual image hashing is a better tradeoff between robustness and discrimination. On the other hand, a major objective of digital watermarking techniques is to provide enhanced robustness and imperceptibility. In this paper, we present extensive experimental analysis, detailed laboratory forensic investigations, and application of the wave atom transform (WAT) based perceptual image hashing and digital watermarking techniques for printed images. Authenticity and copyright of printed images are verified via image hashing and digital watermarking techniques which are resilient against print-scan process distortions. To fulfill the requirement of a good balance between print-scan robustness and discrimination capabilities, we propose a compact, hybrid image hash using lower and middle frequency scale bands in the wave atom coefficients tiling. The hybrid image hash generation strategy is also advantageous due to its computational simplicity and reduced size of the hash value. Furthermore, we propose an enhanced multipurpose scheme which can support multiple applications, such as image authentication and copyright protection, simultaneously, for both digital-only and print-scanned images. Experimental analysis demonstrates the ability of wave atom based image hashing and watermarking schemes to provide authenticity and copyright verification for printed color images.

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

With the popularity of network and the continuous development of multimedia technology, saving of network bandwidth and copyright protection of multimedia content have gradually attracted people’s attention. The fragile watermark for integrity authentication of image data and protection of copyright has become a hotspot. In the storage and transmission process, image data must be compressed to save network bandwidth. As a result, semi-fragile watermarking techniques, which can be used to distinguish common image processing operations from malicious tampering, are emerging. In this paper, semi-fragile watermarking algorithms for image authentication are surveyed. The basic principles and characteristics about semi-fragile watermarking algorithms are introduced, and several kinds of attack behaviors are also included. Aiming at several typical image-authentication algorithms, advantages and disadvantages are analyzed, and evaluation indexes of various algorithms are compared. Finally, we analyze the key points and difficulties in the study on semi-fragile watermarking algorithms, and the direction about future development is prospected.