Information Hiding Techniques for Steganography and Digital Watermarking
Abstract
Until recently, information hiding techniques received very much less attention from the research community and from industry than cryptography. This situation is, however, changing rapidly and the first academic conference on this topic was organized in 1996. The main driving force is concern over protecting copyright; as audio, video and other works become available in digital form, the ease with which perfect copies can be made may lead to large-scale unauthorized copying, and this is of great concern to the music, film, book and software publishing industries. At the same time, moves by various governments to restrict the availability of encryption services have motivated people to study methods by which private messages can be embedded in seemingly innocuous cover messages.
This book surveys recent research results in the fields of watermarking and steganography, two disciplines generally referred to as information hiding.
... The content used to embed information is called as cover object. The cover along with the hidden information is called as stego-object [1]. In this paper image is the cover and secret information is also an image. ...
... The major objective of steganography is to prevent some unintended observer from stealing or destroying the confidential information. There are some factors to be considered when designing a steganography system: [1] • Invisibility: Invisibility is the ability to be unnoticed by the human. ...
... The design of a steganographic system can be categorized into spatial domain methods and transform domain methods [1]. ...
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
... The content used to embed information is called as cover object. The cover along with the hidden information is called as stego-object [1]. In this paper color image is taken as cover and two grey scale images are considered as secret information. ...
... The major objective of steganography is to prevent some unintended observer from stealing or destroying the confidential information. There are some factors to be considered when designing a steganography system: [1] • Invisibility: Invisibility is the ability to be unnoticed by the human. ...
... The design of a steganographic system can be categorized into spatial domain methods and transform domain methods [1]. In spatial domain methods, the processing is applied on the image pixel values directly. ...
Steganography is the science of invisible communication. The purpose of Steganography is to maintain secret communication between two parties. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide multiple secret images and keys in color cover image using Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted secret images are also similar to the original secret images. Very good PSNR (Peak Signal to Noise Ratio) values are obtained for both stego and extracted secret images. The results are compared with the results of other techniques, where single image is hidden and it is found that the proposed technique is simple and gives better PSNR values than others.
... These systems are more robust if they operate in the transform domain (Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Contourlet Transform (CT), etc.). Specifically, in the DCT domain, the algorithms are more robust against common processing operations (JPEG and MPEG compression) compared with spatial domain techniques, and also, the DCT offers the possibility of directly realizing the embedding operator in the compressed domain (i.e., inside a JPEG or MPEG encoder) to minimize the computation time [53]. ...
... To assess the performance of our watermarking algorithm, we employed the following metrics [53]: Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Structural Similarity Index (MSSIM), Normalized Cross-Correlation (NCC), Bit Error (B error ), and Bit Error Rate (BER). In the cases of the MSE, PSNR, SSIM, MSSIM, and NCC, the images were X × Y px, where x and y represent the spatial coordinates: ...
... The Bit error (B error ) denotes the number of wrong bits extracted from the binary string (W)(x), regarding the total bits (N) embedded in the binary string W(x) [53]. • ...
Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image’s quality is of utmost importance, for example in medical images, where improper embedding of the watermark could change the patient’s diagnosis. On the other hand, in digital images distributed over the Internet, the owner of the images must also be protected. In this work, an imperceptible, robust, secure, and hybrid watermarking algorithm is presented for copyright protection. It is based on the Hermite Transform (HT) and the Discrete Cosine Transform (DCT) as a spatial–frequency representation of a grayscale image. Besides, it uses a block-based strategy and a perfectibility analysis of the best embedding regions inspired by the Human Vision System (HVS), giving the imperceptibility of the watermark, and a Singular-Value Decomposition (SVD) approach improved robustness against attacks. In addition, the proposed method can embed two watermarks, a digital binary image (LOGO) and information about the owner and the technical data of the original image in text format (MetaData). To secure both watermarks, the proposed method uses the Jigsaw Transform (JST) and the Elementary Cellular Automaton (ECA) to encrypt the image LOGO and a random sequence generator and the XOR operation to encrypt the image MetaData. On the other hand, the proposed method was tested using a public dataset of 49 grayscale images to assess the effectiveness of the watermark embedding and extraction procedures. Furthermore, the proposed watermarking algorithm was evaluated under several processing and geometric algorithms to demonstrate its robustness to the majority, intentional or unintentional, attacks, and a comparison was made with several state-of-the-art techniques. The proposed method obtained average values of PSNR = 40.2051 dB, NCC = 0.9987, SSIM = 0.9999, and MSSIM = 0.9994 for the watermarked image. In the case of the extraction of the LOGO, the proposal gave MSE = 0, PSNR ≫ 60 dB, NCC = 1, SSIM = 1, and MSSIM = 1, whereas, for the image MetaData extracted, it gave BER = 0% and Berror=0. Finally, the proposed encryption method presented a large key space (K=1.2689×1089) for the LOGO image.
... Стеганографія, у широкому сенсі, це такий спосіб передачі закодованого інформаційного повідомлення, при якому приховується сам факт його існування [1,2]. На відміну від криптографії, методи стеганографії дають можливість замінити несуттєві частки даних на конфіденційну інформацію так, щоб неможливо було запідозрити існування вбудованого таємного послання [1]. ...
... Стеганографія, у широкому сенсі, це такий спосіб передачі закодованого інформаційного повідомлення, при якому приховується сам факт його існування [1,2]. На відміну від криптографії, методи стеганографії дають можливість замінити несуттєві частки даних на конфіденційну інформацію так, щоб неможливо було запідозрити існування вбудованого таємного послання [1]. ...
... На сьогодні у зв'язку з розвитком обчислювальної техніки і нових каналів передачі інформації з'являються нові стеганографічні методи, в основі яких лежить приховування інформації в комп'ютерних файлах -контейнерах, які володіють високим рівнем природньої надмірності (фото-та відеозображення, аудіо-файли, текстові документи, тощо). Сутність приховування полягає в скритній заміні надмірних даних інформаційними повідомленнями, вилучити або навіть встановити факт наявності яких може тільки вповноважена особа, що має секретний стеганографічний ключ [1,2]. ...
A new direction of technical steganography related to the concealment of information in the process of layer-by-layer creation (cultivation) of a solid-state object using various 3D-printing technologies is investigated. Information data are converted into a digital 3D-model of elementary physical objects that are placed inside this 3D-model of the container product. After printing, a solid object physically contains the hidden information that cannot be deleted or distorted without damaging the container product. In addition, the applied methods do not reduce the operational, aesthetic and any other properties of the finished product. The proposed complex is invariant to the method of layer-by-layer growing, that is, it can be equipped with any peripheral devices of 3D-printing of various manufacturers with any materials and principles of layer-by-layer creation.
... In this way, message bits can be embedded in the cover image generating the stegoimage from which the message bit can be extracted. Figure-2, describes this overall process of LSB strategy [15][16][17][18][19][20]. The LSB method has the following features: LSB reserves 8 bytes from the covering image to hide one character from the secret message. ...
... The possibility of obtaining a digital color image at no cost due to the diversity of sources and the availability of various equipment that generates the digital image [15][16][17][18][19][20]. ...
Protecting secret messages is a vital issue, in this paper's research, a simplified, highly secure method of message steganography will be introduced. The proposed method will use a complicated PK, which contains information to select a secret block from the color image to be used as a covering block; also it will contain the values of the chaotic logistic map model to run this model to generate the indices key needed to substitute the message binary matrix. The PK will provide a huge keyspace capable to resist hacking attacks, the extracted message will be very sensitive to any minor changes in the PK, and any changes in this key during the extraction phase will be considered a hacking attempt by producing a damaged extracted message. It will be shown that the proposed method will be always efficient when changing the message length and changing the covering images. The proposed method will be implemented using various messages and various covering images, the obtained results will be analyzed using various types of data analysis methods to prove the improvements provided by the proposed method (quality, security, and efficiency).
... LabVIEW countermeasures involve adaptive embedding and cryptographic augmentation for improved security [11]. ...
Steganography, the science of concealing information within digital media, has gained prominence in security applications. While conventional approaches rely on Python, MATLAB, and Java, the LabVIEW (Laboratory Virtual Instrument Engineering Workbench) environment has emerged as a powerful alternative for implementing real-time, hardware-assisted steganographic techniques. This paper explores various LabVIEW-based steganography methods, including image, audio, and video steganography, and their integration with FPGAs, DSPs, and other embedded systems. The paper also examines the security robustness of LabVIEW-based implementations against steganalysis attacks, provides real-world applications, compares LabVIEW with emerging alternatives, and highlights future research directions in AI-driven and quantum-resistant steganography.
... Further application are Transmission Control Protocol/Internet Protocol TCP/IP (TCP/IP) packets (a unique ID can be embedded into an image to analyze the network traffic of particular users), secure transmission of military, diplomatic, video-audio synchronization, safe circulation of secret data by businesses, television broadcasting, and checksum embedding [14]. In Medical Imaging Systems, a separation between the captions and the image data or Deoxyribonucleic Acid (DNA) sequences of patients are considered necessary for confidentiality [15]. Steganography would be the only security method that could guarantee complete authentication. ...
In recent years, computers and the internet are two most important means of communication. The fear of having one's data spied on while it is being sent from one party to another has increased, as a result of advances in data communication. As a result, data communication becomes inseparable from information security. Steganography and steganalysis are crucial components of information hiding. Steganography is not a new field; however, its significance has increased in the modern world, where data is frequently and easily transmitted via email, the Internet, and other computer methods. The fields of image steganography and steganalysis is being driven by the requirement for better strategies and procedures that can be utilized to both embed hidden data in images and recognize messages concealed in images. Accordingly, the review essences on various approaches applied for image steganography and Steganalysis together. This survey used 25 papers on a variety of techniques, and it provides a review of techniques-based research. The inclusive analysis is carried out depending on the software utilized for the technique, utilized dataset, various techniques used in image steganography and the performance achievement. The review lists the future scope by analyzing the research challenges that are prevalent in the literary works of image steganography and Steganalysis for researchers to improve the current works.
... In the specialized domain of image (Cox, et al., 2007;Kadhim, et al., 2019) and video steganography (Sadek, et al., 2014), two primary approaches have emerged: spatial domain steganography and transform domain (or frequency domain) steganography (Katzenbeisser, et al., 2000). Spatial domain techniques operate by directly manipulating pixel values -such as color, brightness, or contrast -within an image or video frame (Chan, et al., 2004). ...
This study focuses on spatial domain video steganography, motivated by the increasing need for secure data embedding methods that leverage natural video properties to remain undetectable. Existing literature has largely overlooked the detailed statistical characterization of naturally occurring pixel color differences across consecutive video frames. This gap hinders the development of encoding techniques that effectively exploit these variations to enhance the imperceptibility of hidden data. To address this void, the study analyzes the statistical properties of pixel color differences in video frames, examining histograms and frequency patterns to identify predictable natural variations. Using a diverse sample of video files, the analysis revealed distinct patterns in color changes, which are crucial for understanding how to embed data seamlessly within the inherent noise of video content. The findings contribute both theoretically and practically: theoretically, by offering a deeper understanding of the statistical behavior of pixel color differences, and practically, by providing a framework to inform and guide the development of advanced spatial domain steganographic methods. These methods aim to exploit natural noise to reduce detectability while maintaining video quality. This work lays the foundation for further research into resilient and imperceptible steganographic techniques, addressing a critical need in secure data communication.
... The definition of the Incremental Information Function (IIF) is inspired by the concept of the Bit Error Rate (BER), which measures the ratio of incorrectly encoded bits to the total number of encoded bits in a message [19]. A lower BER indicates less information loss in the encoded message and higher robustness. ...
This study presents a detailed characterization of iterative steganography, a unique class of information-hiding techniques, and proposes a formal mathematical model for their description. A novel quantitative measure, the Incremental Information Function (IIF), is introduced to evaluate the process of information gain in iterative steganographic methods. The IIF offers a comprehensive framework for analyzing the step-by-step process of embedding information into a cover medium, focusing on the cumulative effects of each iteration in the encoding and decoding cycles. The practical application and efficacy of the proposed method are demonstrated using detailed case studies in video steganography. These examples highlight the utility of the IIF in delineating the properties and characteristics of iterative steganographic techniques. The findings reveal that the IIF effectively captures the incremental nature of information embedding and serves as a valuable tool for assessing the robustness and capacity of steganographic systems. This research provides significant insights into the field of information hiding, particularly in the development and evaluation of advanced steganographic methods. The IIF emerges as an innovative and practical analytical tool for researchers, offering a quantitative approach to understanding and optimizing iterative steganographic techniques.
... In the late of 1990s several companies were established to market watermarking product (S. Katzenbeisser and F. A. P. Petitcolas, 2000). ...
... Based on this observation, the paper assumed that Trojans could be injected into the lower bits of weights. Embedding or extracting the binary payload is similar to the digital steganography [44], which can not only ensure high accuracy but also hide Trojans in the model. Then, during the inference process, the trigger can extract the embedded payloads from the weights and execute them by the built-in API in the run-time system. ...
Deep Neural Networks (DNNs) have found extensive applications in safety-critical artificial intelligence systems, such as autonomous driving and facial recognition systems. However, recent research has revealed their susceptibility to Neural Network Trojans (NN Trojans) maliciously injected by adversaries. This vulnerability arises due to the intricate architecture and opacity of DNNs, resulting in numerous redundant neurons embedded within the models. Adversaries exploit these vulnerabilities to conceal malicious Trojans within DNNs, thereby causing erroneous outputs and posing substantial threats to the efficacy of DNN-based applications. This article presents a comprehensive survey of Trojan attacks against DNNs and the countermeasure methods employed to mitigate them. Initially, we trace the evolution of the concept from traditional Trojans to NN Trojans, highlighting the feasibility and practicality of generating NN Trojans. Subsequently, we provide an overview of notable works encompassing various attack and defense strategies, facilitating a comparative analysis of their approaches. Through these discussions, we offer constructive insights aimed at refining these techniques. In recognition of the gravity and immediacy of this subject matter, we also assess the feasibility of deploying such attacks in real-world scenarios as opposed to controlled ideal datasets. The potential real-world implications underscore the urgency of addressing this issue effectively.
... b) Image watermarking: Traditional watermarking schemes embeds invisible marks within multimedia content to assert copyright ownership (robust watermarking) or authenticate content (fragile watermarking). Classic techniques involve manipulating spatial or frequency domains representation of the media [12], [13]. Recently, deep-learning enabled more robustness as first shown with the encoderdecoder HiDDeN architecture [5] and followed with [14], [15]. ...
This paper proposes a novel approach towards image authentication and tampering detection by using watermarking as a communication channel for semantic information. We modify the HiDDeN deep-learning watermarking architecture to embed and extract high-dimensional real vectors representing image captions. Our method improves significantly robustness on both malign and benign edits. We also introduce a local confidence metric correlated with Message Recovery Rate, enhancing the method's practical applicability. This approach bridges the gap between traditional watermarking and passive forensic methods, offering a robust solution for image integrity verification.
... The two popular approaches to information confidentiality are Cryptography and Steganography [1,2,3]. Cryptography is the study and practice of protecting information by data encoding and transformation techniques. ...
In today's world, there are a number of cryptographic and steganography techniques used in order to have secured data transfer between a sender and a receiver. In this paper a new hybrid approach that integrates the merits of cryptography and audio steganography is presented. First, the original message is encrypted using chaotic neural network and the resultant cipher text is embedded into a cover audio using Double Density Discrete Wavelet Transform (DD DWT). The resultant stego audio is transmitted to the receiver and the reverse process is done in order to get back the original plain text. The proposed method presents a Steganography scheme along with the cryptography scheme which enhances the security of the algorithm.
... Приховування даних зазвичай включає методи приховування даних у просторовій області, наприклад, вбудовування найменшого значущого біта (LSB) [1], який передбачає зміну значень пікселів зображення для вбудовування прихованого повідомлення або даних або методи частотної області, які змінюють дані таким чином, що прихована інформація стає непомітною для людського ока. Нижче розглянемо методи LSB, частотний діапазон [2] та Patchwork [3]. ...
... Cyclically permutable codes (CPCs), originally introduced by Gilbert in the early 1960s [1], make up a binary block code of code length n such that each codeword has a cyclic order n and the codewords are cyclically distinct. CPCs have many applications in communication networks, for example, as protocol sequences [2,3], and in watermarking systems [4]. Additionally, non-binary CPCs have applications in direct sequence code division multiple access systems with asynchronous base stations [5], as well as in the construction of frequency-hopping sequence sets [6][7][8][9]. ...
In this paper, we propose a way to partition any constacyclic code over a finite field in its equivalence classes according to the algebraic structure of the code. Such a method gives the generalization of cyclically permutable codes (CPCs), which are called constacyclically permutable codes (CCPCs), and it is useful to derive a CCPC from a given constacyclic code. Moreover, we present an enumerative formula for the code size of such a CCPC, with all of the terms being positive integers, and we provide an algebraic method to produce such a CCPC.
... Стеганографія -наука приховування повідомлень, але не шляхом їхнього перетворення на щось нерозпізнаване, як це відбувається у криптографії, а шляхом того, щоб вони залишалися непоміченими [2]. Загалом, стеганографія може використовувати у вигляді контейнерів будь-що від таких цифрових носіїв інформації, як зображення, аудіо та відео, до мережних протоколів еталонної моделі OSI. ...
Audio file steganography can be used as an effective and efficient method to hide messages, but it is a complex process because the human auditory system is sensitive to small changes in audio data. In this article an improved approach for hiding secret text message in audio is presented, combining steganography and cryptography. The Least Significant Bits (LSB) technique, one of the most common and basic methods of steganography, is used as an algorithm for steganographic transformation. The described point of this method is to replace the least significant bits of the audio container with message bits that contain not very useful information, so filling them with additional information has little effect on the quality of perception. Such a significant disadvantage as the low level of reliability is improved by the introduction of a cryptographic layer, the feasibility of which is justified in the article. Cryptographic protection has been added in the form of one of the modern symmetric encryption algorithms – the AES algorithm in the CBC mode. Pseudo-random numbers are used to create a stable cryptokey. The cryptoalgorithm is used to protect the message, which after cryptographic conversion is hidden in the audio file using the steganographic LSB method. The main characteristics of the stegosystem are analyzed. In this paper, the application system of steganographic protection of information in audio files using a cryptographic algorithm is implemented using the environment of Microsoft Visual Studio 2019 and cryptographic libraries, the programming language is C ++. A WAV audio file was used as the digital container. NIST tests were used to assess resistance to stegoanalysis, which according to the results is better using an improved method compared to the classical LSB approach. In addition, the steganographic algorithm is evaluated by visual analysis by comparing the original audio file and the stegofile with the hidden message. The results of the analysis indicate the absence of traces of steganography. Based on the obtained results, it can be argued about the reliability and efficiency of the proposed approach, so the use of LSB-AES technique can be proposed to ensure secure data transmission.
... In (Lemma et al. 2003;Cox et al. 2002), the approach described in (Wolfgang et al. 1999;Potdar et al. 2005) for selecting the attribute vector is improved. Nevertheless, an attack has been identified in (Stefan and Fabien 2000). Following the incorporation of a watermark, the discrepancy of weight values increases, revealing details regarding a concealed communication in a particular CNN layer. ...
The rise of artificial intelligence (AI) and machine learning (ML) has prompted concerns regarding the intellectual property (IP) protection of neural networks (NNs). A proposed solution is watermarking, which incorporates a unique identifier into a NN. However, the effectiveness of watermarking methods in enhancing privacy and ownership secrecy remains questionable. This study intended to evaluate the efficacy of watermarking techniques for enhancing the security and ownership protection (SOP) of NNs. An exhaustive search of scholarly databases for peer-reviewed journal articles and conference proceedings was conducted in accordance with PRISMA standards. Eligible papers evaluated the efficacy of watermarking techniques used to protect NNs. Twenty research articles using various watermarking techniques, including digital watermarking (DW), reversible watermarking (REW), and robust watermarking (ROW), were analyzed. Various performance indicators, such as detection rate (DR), robustness, and distortion, were employed to evaluate the applicability of each method. The results demonstrated that watermarking techniques effectively protected the intellectual property of NNs with minimal impact on performance. However, the need for specialized apparatus and the difficulty of incorporating watermarks into deep neural networks (DNN) hampered their implementation. To improve the practicability and effectiveness of watermarking techniques, additional research is required. Researchers, professionals, and policymakers should consider watermarking to safeguard the intellectual property of NNs in a variety of domains, including finance, healthcare, and national security.
... Embedding data which is to be hidden requires two files first is innocent-looking image that will hold the hidden information, called the cover image. The second file is the message the information to be hidden [3]. Firstly the cover image and hidden message are combined to form stego image. ...
An image steganographic scheme is one kind of steganographic systems, where the secret message is hidden in a digital image with some hiding method. Someone can then use a proper embedding procedure to recover the hidden message from the image. The original image is called a cover image in steganography, and the message-embedded image is called a stego image. This Steganography technique is more popular in recent year than other steganography possibly because of the flood of electronic image information available with the advent of digital cameras and high-speed internet distribution. It can involve hiding information in the naturally occurred noise within the image. In this paper we provide a review on various image steganography techniques.
... Other examples of steganography include combinations with cryptography [47,48], watermarking [27,49] or secret sharing [50][51][52], multi-secret steganography used for concealing more than one message in a single container [53], techniques that do not require a predefined medium but generate the carrier from scratch [54,55], format-specific methods destined for particular files [36,56,57], the creation of subliminal channels in existing schemes to achieve better undetectability [58,59], systems that use biometric authentication for data hiding [60,61], combining various techniques to obtain secure data transmission in telemedicine applications [62,63], and many more. ...
In this paper, several ideas of data hiding in WebP images are presented. WebP is a long-known, but not very poplar file format that provides lossy or lossless compression of data, in the form of a still image or an animation. A great number of WebP features are optional, so the structure of the image offers great opportunities for data hiding. The article describes distinct approaches to steganography divided into two categories: format-based and data-based. Among format-based methods, we name simple injection, multi-secret steganography that uses thumbnails, hiding a message in metadata or in a specific data chunk. Data-based methods achieve secret concealment with the use of a transparent, WebP-specific algorithm that embeds bits by choosing proper prediction modes and alteration of the color indexing transform. The capacity of presented techniques varies. It may be unlimited for injection, up to a few hundred megabytes for other format-based algorithms, or be content-dependent in data-based techniques. These methods fit into the container modification branch of steganography. We also present a container selection technique which benefits from available WebP compression parameters. Images generated with the described methods were tested with three applications, including the Firefox web browser, GNU Image Manipulation Program, and ImageMagick. Some of the presented techniques can be combined in order to conceal more than one message in a single carrier.
... The payload capacity P is measured in the unit of bps (bits per second). According to the International Federation of the Phonographic Industry (IFPI) 44 , the payload capacity must be at least 20 bps for any audio watermarking system. Therefore, the payload capacity of the proposed system, shown in Table 3, is too high and very sufficient and verifies the IFPI condition, which is set at 20 bps. ...
Transform-domain audio watermarking systems are more robust than time-domain systems. However, the main weakness of these systems is their high computational cost, especially for long-duration audio signals. Therefore, they are not desirable for real-time security applications where speed is a critical factor. In this paper, we propose a fast watermarking system for audio signals operating in the hybrid transform domain formed by the fractional Charlier transform (FrCT) and the dual-tree complex wavelet transform (DTCWT). The central idea of the proposed algorithm is to parallelize the intensive and repetitive steps in the audio watermarking system and then implement them simultaneously on the available physical cores on an embedded systems cluster. In order to have a low power consumption and a low-cost cluster with a large number of physical cores, four Raspberry Pis 4B are used where the communication between them is ensured using the Message Passing Interface (MPI). The adopted Raspberry Pi cluster is also characterized by its portability and mobility, which are required in watermarking-based smart city applications. In addition to its resistance to any possible manipulation (intentional or unintentional), high payload capacity, and high imperceptibility, the proposed parallel system presents a temporal improvement of about 70%, 80%, and 90% using 4, 8, and 16 physical cores of the adopted cluster, respectively.
... When the intensity levels of the FFT coefficients become higher, the resulting SNRs go lower. In this case, the 48 FFT coefficients in the frequency range (II), starting from the 7th Barker scale, are selected as embedding carriers, and the average SNR just exceeds the minimum acceptable threshold (i.e., 20 dB) recommended by the International Federation of the Phonographic Industry (IFPI) [33]. As for the ODGs, the results in Table 1 also exhibit a similar trend, i.e., the higher the FFT coefficient indexes are, the better the ODG scores. ...
Watermarking is a viable approach for safeguarding the proprietary rights of digital media. This study introduces an innovative fast Fourier transform (FFT)-based phase modulation (PM) scheme that facilitates efficient and effective blind audio watermarking at a remarkable rate of 508.85 numeric values per second while still retaining the original quality. Such a payload capacity makes it possible to embed a full-color image of 64 × 64 pixels within an audio signal of just 24.15 s. To bolster the security of watermark images, we have also implemented the Arnold transform in conjunction with chaotic encryption. Our comprehensive analysis and evaluation confirm that the proposed FFT–PM scheme exhibits exceptional imperceptibility, rendering the hidden watermark virtually undetectable. Additionally, the FFT–PM scheme shows impressive robustness against common signal-processing attacks. To further enhance the visual rendition of the recovered color watermarks, we propose using residual neural networks to perform image denoising and super-resolution reconstruction after retrieving the watermarks. The utilization of the residual networks contributes to noticeable improvements in perceptual quality, resulting in higher levels of zero-normalized cross-correlation in cases where the watermarks are severely damaged.
... Camouflage is a widely used information security technology [21]. As a quite prevalent embodiment of camouflage, reversible data hiding(RDH) have achieved well, but they also show a complex trade-off between quality and embedding capacity [22]- [30] and they are all pixel-level. ...
The single type of multimedia data, such as text, image, video, and audio, has been extensively studied in the past decades. With the advances in multimedia applications and services, the exponential growth of multimedia data has emerged. Therefore, it is crucial to effectively represent multimedia data and capture the relationships among them in the study of multimedia applications. In the paper, we propose a novel reversible multimedia representation method based on a complex base. In the proposed multimedia representation method, we first process different modalities of data, such as text, image, and audio separately and convert them into different Gaussian integers, then place them on the same representation plane and resulting in a joint multimedia representation model. Therefore, the relationships of multimedia data are established by using the geometric operations on the same representation plane. Experimental results show that the proposed multimedia representation method is lossless and reversible. In addition, we explore the potential applications of the proposed representation method in multimedia camouflage and multimedia secret sharing, and verify that the proposed representation method has good practical applicability in multimedia security.
... This is done by adding unique user-specific information, or a fingerprint, to several copies of the same content. A multimedia fingerprinting algorithm is a protocol that involves three operations between the owner of the content and the user: fingerprint generation, embedding, and the ability to track down pirates using copies that have been obtained illegally or through collusion (Stefan and Fabien 2000). ...
Due to the ubiquity of social media and digital information, the use of digital images in today’s digitized marketplace is continuously rising throughout enterprises. Organizations that want to offer their content through the internet confront plenty of security concerns, including copyright violation. Advanced solutions for the security and privacy of digital data are continually being developed, yet there is a lack of current research in this area.
Examining Multimedia Forensics and Content Integrity features a collection of innovative research on the approaches and applications of current techniques for the privacy and security of multimedia and their secure transportation. It provides relevant theoretical frameworks and the latest empirical research findings in the area of multimedia forensics and content integrity. Covering topics such as 3D data security, copyright protection, and watermarking, this major reference work is a comprehensive resource for security analysts, programmers, technology developers, IT professionals, students and educators of higher education, librarians, researchers, and academicians.
... Steganography can also be used for digital watermarking, which can be used to protect copyrighted material from being stolen or illegally used. By embedding a unique identifier within an image or audio file, the owner of the material can track its use and identify any unauthorized usage [10][11][12][13][14][15][16][17][18]. ...
This article provides an overview of steganography and its use for hiding images in other images. Steganography is a technique that allows users to hide information in plain sight, making it difficult for unauthorized parties to detect or access the information. Spatial domain steganography is a popular technique for hiding images within other images, where the least significant bits of the cover image are modified to embed the secret image. The article discusses the advantages of steganography and its use in various applications such as digital watermarking and secure communication. The article also provides an overview of the various techniques used for spatial domain steganography, and how these techniques can be implemented using programming languages such as Python. Finally, the article concludes by emphasizing the importance of using steganography responsibly and ethically.
... Which comes from [37,38]: ...
Secrecy is one of ownership rights for persons or foundations, there are many trials for finding new methods for hiding information inside innocuous media (image, audio, text… etc.). Steganography is the technique to hide information, it can be defined as the art and science of communication that hide the transmitted information without suspicious. Using cryptography techniques can increase the level of secrecy.
In cryptosystem, a hardware device (Fingerprint reader) is used to generate a primary unique key for any user. Then this key was developed to make it a one-time-pad.
The steganography part of the system based on the transformation domain of YCbCr image format. Discrete Cosine Transform (DCT) technique is used to hide the information in stego-image in transmission side. Inverse Discrete Cosine (IDCT) is used to extract the text message from the stego-image at the receiver side. This technique made the system more immune to active attacks, such as lossy compression (JPEG) and the information more uniformly distributed when compared to LSB technique.
The proposed system has two sub-systems. One for the manager of the network, which has all users fingerprints as database. The second sub-system is public to all clients distention.
The keys generated and the corresponding data produced by different techniques are tested using frequencies, serial and auto-correlation standard tests. These tests have shown an acceptable level of randomness when test was considered.
Using PSNR tests the stego-images, gets more than 30 dB was obtained without any data error.
... There have been many data hiding technology which is based on spatial-domain and frequency-domain techniques. These techniques use multimedia data such as text, image, audio and video as the cover medium to hide the secret data [25]. ...
Hiding a data inside video plays a vital role in data communication. The aim of data hiding is to protect the data with minimum distortion rate. In this paper, key frame selection data hiding in videos using Search Tree Labeling Scheme (STLS) is proposed. The cover video in the frames is trained for noise removal and compression using Denoising Convolution Neural Network (DnCNN) and the quality factor is checked for every frame using parameters. The compression is applied and key frames in the cover video are selected using Neural Image Assessment (NIMA) and Convolution Neural Network (CNN) model. This model is trained to predict the score of each frame based on quality metrics. The high score frame are selected as the key frame and it is separated into 2 × 3 blocks. Each block of pixels are represented in the tree structure using STLS to identify the differences and pixel is named in the tree according to its distortion range. Data is embedded using odd or even bit embedding on the pixel using Most Significant Bit (MSB) and Least Significant Bit (LSB). The experimental result reveals that the proposed schemes can attain better data extraction with more Embedding Capacity (EC), and security. The proposed method provides Peak Signal Noise Ratio (PSNR) value for ImageNet VID is 46.63 and CD-net 2014 is 45.47 and EC has achieved for ImageNet VID: 693,242 and CD-net 2014: 712,422 bits). Moreover the proposed scheme is significantly outperforms the state-of-the-art techniques in terms of quality assessment in the selection of frames and data embedding.
... This resulting modified image is called stego-image. The transform technique is found to be more robust than the spatial domain[20]. ...
Security systems have a great importance in protection confidential (private) data from being accessed by unauthorized persons or intruders. One of theses security systems is image steganography that uses the image as a container (cover) for the data need to be protected without the need for changing the hidden data or visible changes to the host image.
In this work, two proposed methods are suggested for the steganography system. The two proposed stego-methods use the slantlet transform domain in the steganography process in order to increase the robustness by embedding the frequency component of the secret image in the high frequency component of the cover image. The first proposed method is based on the replacement method, the secret image is encrypted by combinational permutation before embedding. The second proposed method is based on the weight method, either image or text file which can be embedded when using this method. The proposed methods provide efficient security, because the original secret image or text is encrypted before embedding in order to make the system more complex to be defeated by attackers. Some of the well known fidelity measures like (PSNR and AR) have been used to assess the quality of the modified image and extracted image. The results show that the stego-image is closed related to the cover image, when the Peak Signal to Noise Ratio (PSNR) is up to 55dB. The recovered secret image is extracted (100%) if stego-image has no attack. These methods can provide good hiding capacity and image quality. Several types of attacks have been applied to the proposed methods in order to measure the robustness like (compression, add noise and cropping).
... Generally, a secure method of a watermarking in medical applications is processed according to two principal stages, the first being the watermark embedding, the second the watermark extraction. This process is illustrated in Fig. 1 [23]. In the first stage, by the Content courtesy of Springer Nature, terms of use apply. ...
Nowadays, the distribution of huge amounts of medical images through open networks in telemedicine applications has become increasingly faster and easier. Therefore, a number of considerations are introduced related to the risks of the illegal use of these images, as total diagnosis depends on them. Indeed, the patient’s data management, storage, and transmission require a technique for boosting security, integrity and privacy measures in telehealthcare services. In fact, in our previous works, we used polynomial decompositions such as Chebychev orthogonal polynomial transform in medical image watermarking. We then customise our tools for finding the best candidate area for embedding the watermark, always seeking to provide the best solution to this issue. In this research, a variation to medical image watermarking approach based on Hermite transform (HT) is suggested for reliable management of medical data. In this approach, the HT is employed as a preprocessing step so as to extract the texture component of the host medical image. Afterward, a sliding window technique is done to select the most suitable regions for watermark embedding. Lastly, the Arnold transform is utilized for encrypting the watermark to strengthen the security of our scheme. Experiments were conducted on various modalities of medical images. Results indicate that the proposed scheme is robust when subjected to various attacks while preserving a high level of security and invisibility factors. Also, our method preserves the quality of medical images with a good embedding capacity. The obtained results support the use of Hermite Polynomials for the implementation of watermarking in the medical imaging context.
... In the second half of the 20th century, the World Wide Web or WWW phenomenon, demonstrated the economic value of offering digital media free of charge. The use of digital networks to include digital media for commercial purposes is expected of multinationals (MNCs) [1]. But also, their ownership must be protected. ...
The most advanced technology, watermarking enables intruders to access the database. Various techniques have been developed for information security. Watermarks and histories are linked to many biometric techniques such as fingerprints, palm positions, gait, iris and speech are recommended. Digital watermarking is the utmost successful approaches among the methods available. In this paper the multiband wavelet transforms and singular value decomposition are discussed to establish a watermarking strategy rather than biometric information. The use of biometrics instead of conservative watermarks can enhance information protection. The biometric technology being used is iris. The iris template can be viewed as a watermark, while an iris mode of communication may be used to help information security with the addition of a watermark to the image of the iris. The research involves verifying authentication against different attacks such as no attacks, Jpeg Compression, Gaussian, Median Filtering and Blurring. The Algorithm increases durability and resilience when exposed to geometric and frequency attacks. Finally, the proposed framework can be applied not only to the assessment of iris biometrics, but also to other areas where privacy is critical.
... Digital watermarking embeds a marker (watermark) in noise-tolerant digital works such as images, videos, etc. [2,7,9,21] The watermark helps verify the authenticity or integrity of the works and identify the owners of the works. It may also help to trace copyright infringements and for banknote authentication [4,6]. ...
An important component of cartography, the map legends can be a type of hybrid data with small data quantity and high precision. Therefore, its watermark method should be versatile to all map legend data types. In addition, its watermark should be robust, imperceivable, and small. In this regard, our study proposes a novel watermarking method of map legends for copyright protection. The data types of map legends are evaluated. According to the data types and just noticeable distortion tolerance, the watermark bit embedding positions of each data type are defined. A text watermark is adopted to reduce the number of watermark bits. By the watermark bit count, map legends are divided into groups to contain multiple watermarks. Meanwhile, a watermark bit recovery method is designed to fix the damaged watermark bits based on the extracted ones, which ensures greater robustness. The experimental results demonstrate the proposed method achieves the expected goal in terms of various types of attacks and image operations.
... However, cryptography techniques are considered week or consume high resources. Steganography is mainly based on covering digital data in a safe digital carrier [2]. Steganography is utilized for hiding secret messages in ancient times [3]. ...
Steganography is a vital technique in cybersecurity, allowing users to conceal information within digital media to enhance security and privacy. This guide provides an in-depth tutorial on the fundamentals of steganography, its applications in cybersecurity, tools for implementation, and best practices to mitigate risks.
Steganography, the practice of embedding secret information within a seemingly innocuous medium, has seen significant advancements over the years. With the growth of digital communications, steganography has become a useful tool for secure communication. In this paper, we explore the application of image-based steganography to conceal a text file within an image using two methods: a basic encryption technique and the PHP-based least significant bit (LSB) manipulation method. The effects of each method are analyzed in terms of file size, visual alteration, and hex data comparisons. We discuss how LSB steganography provides a more secure but resource-intensive method. Our analysis highlights the advantages and limitations of each approach and suggests potential future directions for more efficient steganographic methods
This study investigates spatial domain video steganography, driven by the increasing demand for secure data embedding techniques that leverage inherent video properties to remain undetectable. Traditional approaches in the literature often neglect the detailed statistical characterization of naturally occurring pixel color differences across video frames, creating a significant gap in understanding how these variations can be systematically analyzed and effectively applied to steganographic methods. To address this deficiency, the study develops a comprehensive mathematical model for video files, introducing a function to compute inter-frame color differences and constructing a formalized color difference histogram. This innovative metric enables precise characterization of video files by analyzing the frequency and distribution of pixel color variations, offering a novel perspective on video content analysis. The findings confirm that the proposed model reliably captures the statistical patterns of color differences, providing a robust and scalable framework for improving steganographic techniques. By leveraging these patterns, the model enhances the resilience and imperceptibility of spatial domain steganography against detection and tampering. Future research will extend this framework to diverse video datasets, exploring its adaptability and uncovering additional insights into natural color variation dynamics and their potential applications in secure information encoding. This work lays the foundation for further advancements in the integration of statistical analysis and steganographic innovation.
In today's digital age, ensuring the security and confidentiality of image data is paramount, particularly with the proliferation of online communication and storage platforms. This project proposes a hybrid approach for enhancing image security by synergistically integrating encryption and steganography techniques. The combination of these two methods aims to fortify the protection of digital images against unauthorized access and tampering. Encryption ensures the confidentiality of image content by converting it into an unintelligible form using robust cryptographic algorithms. Concurrently, steganography conceals the encrypted data within the image itself, embedding it imperceptibly into the pixels or metadata. The synergy of encryption and steganography not only safeguards the integrity of image data but also adds an additional layer of concealment, making it arduous for adversaries to detect and decipher sensitive information. Through this project, the efficacy of the hybrid approach will be evaluated through experimentation and analysis, with the ultimate goal of providing a comprehensive solution for image security in various applications and contexts.
The project titled "Image Steganography using Mid-Point Transformation Technique" aims to explore and implement a novel approach to concealing information within digital images while preserving their visual integrity. Steganography is an age-old technique for covert communication, and this project leverages the mid-point transformation method to embed data seamlessly into images. The mid-point transformation technique involves the subtle alteration of pixel values based on the midpoint of neighboring pixels. This process ensures that the changes made to the image are imperceptible to the human eye, allowing for effective data hiding without compromising the overall visual quality. The project will focus on the development of an algorithm to encode and decode hidden information within images using the mid-point transformation technique. Implementation will be carried out using a programming language suitable for image processing, and the project aims to provide a user-friendly interface for ease of use. Key objectives include understanding the theoretical foundations of steganography, implementing the mid-point transformation algorithm, evaluating the effectiveness of the technique in terms of data capacity and visual impact, and comparing the results with existing steganographic methods. Key Words: Image Steganography, Mid Point Transformation, Steganography Techniques, Digital Image Security, Data Hiding, Information Security.
Cyclically permutable codes (CPCs) have found important applications in many communication systems, such as the multiple access collision channel without feedback, frequency-hopping spread spectrum communication channels and the digital watermarking systems. In this paper, by introducing a new method we completely settle the problem of constructing a CPC with the largest possible code size derived from a given simple-root cyclic code. The contribution of this paper is twofold. First, we present a new enumerative formula for the code size of such CPC with all the terms being positive integers, contrasting to the previously known ones given in [1], [20], [22], [24] which involve the Möbius function. Second, we provide an algebraic and systematic method to produce such a CPC. Several examples are also included to illustrate our main results.
The human being sought to find a human variety of techniques to assure data access with complete confidentiality. The transition from the use of. regular text and audio data to digital media has improved data access and transport. It has become relatively simple to intercept data sent across networks or get access to a variety of machines. Steganography is the study of concealing the existence of communication by embedding hidden data in multimedia payloads such as text, image, audio, and video. This project investigates how to improve steganography by merging text and image production to provide invisible encryption, security, and robustness in digital images. Text hide into another text using quality in the proposed system include Mean Square Error (MSE), Normalized Correlation (NC), and Normalized Cross–correlation Mean Squared Error, Histogram Analysis, Standard Deviation, and Statistical Test and Analysis. The algorithm of our suggested system seems to meet the greatest standards of security, perceptions, and capability. Using the standard of ASCII Control characters for a cover word, the procedure for using the processed system is supplied from the cover sentence. The same method is used for other words from different cover sentences, given the line numbers of each cover sentence and Stego sentence. Keywords: Algorithm, Secret Text, Steganography
It’s It's been so crucial lately to emphasize data security applying as the world depends on data exchange extensively almost in all domains. Steganography is one of the main techniques used to ensure information security in storage and during communication. We accomplish this novel technique by using two main layers. In the first layer, the secret message is compressed using Gzip or encrypted using Advanced Encryption Standard (AES). In the next layer, the binary representation of the secret message is embedded into vertices of x, y, and z-coordinates of the 3D object using the Gray code sequence, Recamán's sequence, and Lucas sequence. This binary representation of secret message is embedded using the Least Significant Bit (LSB) technique according to the value of the used sequence. Different performance measurements are computed and evaluated to ensure that the 3D object quality remains preserved such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), embedding rate (ER), Normalized Hausdorff Distance (NHD) and maximum embedding capacity. The proposed scheme is compared with its counterparts in the literature. Outstanding numerical results are achieved, showing the superiority of the proposed schemes in the terms of performance, capacity, and security.
Privacy is a criterion of growing importance in today's world. People nowadays transfer products more often due to the rapid growth of technology. But during the transfer of products, the information regarding the sender and the receiver is visible to the staff in logistics as well as the people delivering the product. So, if the data is visible, it is prone to leakage of the information, which leads to crime that cannot be solved by digital forensics especially since there is no evidence for the leakage of the personnel information. Thus, a new approach is being used in this paper known as Intermodal Address Access Control Management based on the innovative use of QR code, Shamir's Secret Sharing Scheme and Attribute-Based Encryption. In this proposed solution, using Shamir's secret sharing technique, a secret access key is being split and encrypted using the ciphertext policy attribute-based encryption, and then encoded in a QR code. Subsequently, the staff in the respective transits scan the QR code and recover the individual secret key using their attributes satisfying an access policy associated with the ciphertext. Here, flexible access control is ensured only when a sufficient number of participants is present. So, the details of the person receiving the product are hidden to the staff in each transit since they only possess the key to decrypt the postcode. Thus, the intermediate transits will only be able to know the next transit. This, hence, provides a more secure way of transmission of the products from source to destination.
There are two types of content on the blockchain: centralized and decentralized. On centralized video platforms, the platform owner controls most of the content uploaded, rather than the creator. However, some content creators post low-quality content in exchange for free cryptocurrencies, creating a cryptocurrency algorithm that demotivates other content creators. In contrast, decentralized blockchain-based video platforms aim to lessen ad pressure and eliminate intermediaries. On video platforms, copyright violations and the unauthorized dissemination of protected information are also significant issues. Copyright protection, illegitimate access restriction, and legitimate dissemination of video files are necessary to guarantee that authors' original output is appropriately compensated.
The recent explosion of technology in healthcare has rapidly changed the healthcare sector. Technologies such as artificial intelligence and machine learning along with the integration of the Internet of Medical Things have evolved to tackle the need for remote healthcare systems, augmenting them in a self-sustainable way. This new volume explores the many important smart technologies that can make healthcare delivery and monitoring faster, more efficient, and less invasive. It looks at computational tactics as applied to the development of biomedical applications using artificial intelligence, machine learning, signal analysis, computer-aided design, robotics and automation, biomedical imaging, telemedicine, and other technologies. The book provides a solid framework to give the modern class of medical gearheads information on the innovative applications of computational mechanisms for improving and expediting patient-friendly automation in healthcare.
Steganography is one of the important research subjects in the field of information security. It enables secret communication by embedding messages in the texts, images, audio, video files or other digital carriers. Among all the image information hiding methods, LSB embedding is widely used for its high hiding capacity and it is with great significance to detect the images with hidden messages produced by LSB embedding effectively, accurately and reliably. Therefore, many experts made efforts on the LSB steganography and steganalysis research over the years. This research presents a steganographic technique based on using LSB of one of the pixel color components in the image and changes them according to the message’s bits to hide. The rest of bits in the pixel color component selected are also changed in order get the nearest color to the original one in the scale of colors. This new method has been tested with others that work in the spatial domain through applying some common metrics which give us good result as a compared with the other steganographic tools.
The article presents an applied steganographic system of hiding textual information in audio files on the basic of an advanced approach that combines the methods of steganography and cryptography. The method of the least significant bit (LSB) was used as a steganographic transformation algorithm. The low level of reliability of the method can be improved by introducing a cryptographic layer, the feasibility of which is justified in the article. The improvement is to add one of the modern symmetric encryption algorithms – the AES algorithm in CBC mode. The applied steganographic system for hiding textual information in audio files, taking into account the improvement of the LSB method, is implemented in the Microsoft Visual Studio 2019 environment using the cryptographic libraries that are present in it. The application is developed in the C++ programming language. NIST tests were used to assess the stability of the implemented system to steganalysis. The proposed approach is considered in order to anticipate its role in emerging networks.KeywordsSteganographySteganographic systemLeast significant bitAES-CBCAn audio fileNIST-tests
Steganography is the skill of hiding the existence of data in other transmission medium to attain secret communication. It does not restore cryptography but quite boost the security using its abstruse features. In this paper we have surveyed on a Steganography and cryptography techniques which provide highly secure skin tone data hiding. Biometric characteristic used to apply steganography is skin tone region of images. Here important data is implanted within skin region of image which will give an outstanding secure location for data hiding. For this skin tone detection is need to be performed. Different steps of data hiding can be applied by cropping an image interactively. Cropping of an image improved security than hiding data without cropping the whole image, so cropped region works as a key at decoding region. Cryptography algorithm is used to convert the secret messages to an unreadable form before embedding; which provides a strong backbone for data security. This survey paper focuses on illuminating the technique to secure data or message with authenticity and non repudiation. So with this object oriented steganogaphy we track skin tone objects in image with the higher security and satisfactory PSNR .Modern steganography's goal is to keep its mere presence undetectable.
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