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Video steganography techniques: Taxonomy, challenges, and future directions
... On the other hand, raw video steganographic methods are classified into spatial and transform domains. This survey suggests current research directions and recommendations to improve on existing video steganographic techniques [20]. T. D Sairam et al. have proposed the large embedding capacity data hiding method which maintains the acceptable image quality with PSNR is more than 30 dB. ...
... To embed secret data as audio into video frames for m = 1, Px = 9, Let the three pixel values of selected frame of video (x 1 ,x 2 ,x 3 ) = (15,18,20), and secret data D = 3, ...
... Step 3: A = 15/9 = 1.66, x 1 = 2, B = 18/9 = 2,so x 2 = 2,C = 20/9 = 2.22,so x 3 = 2. The new stego pixel values are (x 1 ',x 2 ',x 3 ' ) = (17,20,22). The recovery of secret data can be obtained using F(x 1 ',x 2 ', x 3 ') = (x 1' *1 + x 2' *2 + x 3' *3)* mod * (3m 2 + 4 m + 2) = 17*1 + 20*2 + 22*3* mod 9 = 6 which is not secret data D. Now to get the secret data D = 3, apply four various conditions (18,22,22). ...
In 2006 X. Zhang and S, Wang suggested efficient steganographic embedding by Exploiting Modification Direction (EMD) where each important secrecy bit is converted to (2n + 1) -ary notational system which produces by n pixel values where 1 pixel is increased or decreased. To date, many researchers have implemented EMD algorithms that are less secure and produce less embedding capacity and imperceptibility. So, to reduce these limitations a combination of audio-video crypto-steganography using the Digital Forensic Detection Array EMD (DFDAEMD) algorithm is used. It uses (3m² + 4 m + 2) ary notation to embed three pixels at a time for enhancing the embedding capacity and security of secret data. The observed and verified software results confirm that the implemented security model provides better Authentication, Imperceptibility, Robustness, Embedding Capacity (EC), Embedding Rate (ER), and very good recovery of both secret and original data as compared to any existing EMD methods.
... There are different techniques, namely cryptography, watermarking, and steganography, available for the data security system, as shown in Fig. 1 [3], for enhancing digital information security. These methods involve one-to-one encryption and decryption for the information to be transformed, copyright protected and concealed into the carrier object [4]. ...
... In steganography, the original data and modified stego data are very much similar such that the observer (third person) cannot identify the existence of an original secret message. The different components of a steganographic system are described as follows [3,5]. ...
... The extracting stage is having an extraction process of secret messages from the cover carrier object. Successful extraction of the secret message is measured by similarity coefficients between the original and extracted secret message [1,3,5]. ...
In the technological era, the primary source of information is in the form of digital data, which has to be secured while storing or transmitting during communication over an unsecured network. Different approaches are used to provide security to digital data, viz. text, audio, image, and video. This paper initially explains the security system such as cryptography, watermarking, and steganography and their comparative analysis based on different characteristics, viz. satisfaction level of objective, type of carrier object and secret information to be used, dependency of security level, and quality assessment parameters. This review article focuses more on steganography methods applied over video. The various methods implemented for video steganography in compressed domain, viz. inter-frame and intra-frame prediction, motion vector estimation, entropy coding (CAVLC and CABAC), and transformed and quantized coefficients of DCT, DST, and DWT, etc. and the methods based on spatial and transform domain for uncompressed video are briefly described. It is followed by the detailed analysis of related work done by various researchers in video steganography and the obtained experimental results. Furthermore, the confidential data hiding in compressed videos are explained using Moving Picture Expert Group (MPEG—1, MPEG—2, MPEG—4), Advanced Video Coding (AVC)/H.264, and High-Efficiency Video Coding (HEVC)/H.265 that includes both spatial and transform domain. This paper summarizes and explains the detailed investigations of numerous techniques of video steganography based on the comprehensive literature survey. The methods used to assess the performance of video steganography are analyzed based on the quality assessment parameters such as imperceptibility; measured by peak signal to noise ratio (PSNR), mean square error (MSE), and structural similarity (SSIM), robustness; measured by bit error rate (BER) and similarity (Sim), and embedding capacity; measured by hiding ratio. The overall review of past literature facilitates to have in-depth knowledge for upgrading the video steganography.
... Numerous steganographic methods have been used in the spatial realm. such as histogram manipulation, spread spectrum, area of interest (ROI), LSB replacement, pixel value differencing (PVD), most significant bit (MSB), and quantization index modulation (QIM) [23], matrix encoding with bit-plane complexity segmentation (BPCS) [30]. The lowest bit in a string of binary numbers is known as the LSB, or least significant bit, and it is located to the string's extreme right. ...
... These techniques have been used by several researchers to achieve spatial video steganography on various images. Additionally, their experimental findings demonstrate the effectiveness of video steganography as determined by many qualitative parameters [30]. There are several specified related works of spatial video steganography techniques and Table V. lists the advantages and disadvantages of each of them. ...
The Internet of things (IoT) is one of those emerging technologies, which are going to rule the world in the next few decades. The IoT environment not only enables Human to Machine interaction but also fosters Machine to Machine connectivity. Numerous IoT devices have poor security and insufficient computing power, making them prime targets for hackers. The IoT environment uses lightweight cryptographic techniques to address security requirements. Another security method for IoT devices is steganography. In the contemporary Internet era, the ability to secure private information is crucial, and steganography offers this capability. Due to its great ability to conceal sensitive data, video has drawn the attention of numerous academics among all forms of digital media. The main goal of this work is to examine several methods for fusing video steganography and cryptography techniques. Additionally, a thorough investigation and evaluation of a variety of video steganography methods in both compressed and raw domains are also emphasized. The comprehensive analysis of prior material makes it easier to have in-depth knowledge while creating approaches that combine cryptography with steganography.
... Digital video has emerged as one of the most prominent media because of highly interactive Internet of Things (IoT)based multimedia applications [1]. Effectiveness of steganography depends on embedding efficiency, concealment capability, imperceptibility, and robustness [2]. Based on the embedding domain, video steganography is parted into two categories: compressed-domain and uncompressed-domain video steganography [3]. ...
... The frequently used syntax elements are motion vectors, intra-prediction modes, inter-prediction modes, quantization parameters (QPs), and quantized transform coefficients (QTCs). Prior to compression, message bits are sent using raw spatial domain pixels that have been modified using methods common to image steganography [2]. By modifying the states or values of the aforementioned video elements, embedding is carried out during compression [4] using intra-prediction modes, inter-partition modes (PMs), motion vectors (MVs), DCT coefficients, and quantization parameters (QPs). ...
The development of steganography methods has raised growing worries about steganography abuse. As the significant demand for digital video processing is on the rise from last decade, data security becomes a crucial issue. Motion vector manipulation (MVM)-based video steganography has caught attention since it can result in indirect and arbitrary alterations in video data. The moderate payload capacity and complexity are issues faced by MV-based methods. A hybrid motion estimation and transform coefficients strategy applied on video steganography using the H.265 compression method is proposed. The robust imperceptible compressed domain video steganography (RI-CDVS) model is presented to increase imperceptibility with improved security. The two phases of the RI-CDVS model are embedding and extraction. The embedding stage generates the compressed stego video from the inputs of compressed cover video and secret image. Using dynamic threshold from the cover video, the motion estimation technique is used to select the group of key frames. The key frames are chosen to hide the secret image without sacrificing quality and lower error rate. The Discrete Cosine Transform (DCT) is used to transform keyframes into the frequency domain. The Least Significant Bit (LSB) of the integer coefficients of the DCT components is used to embed the secret information. The H.265 codec is used to create the compressed stego video. At extraction phase reverse operations are performed to get secret image. The experiments are conducted using a publicly accessible video collection and compared the results of RICDVS with the techniques at the cutting edge of video steganography.
... There are two types of video steganography techniques: compressed and uncompressed (raw) [4]. Intra-frame prediction, inter-frame prediction, motion vectors, transform coefficients, and entropy coding are some of the approaches utilised in compressed domains. ...
... In the raw domain, two methods could be used, which are the spatial domain methods and the transform domain methods. In the spatial domain techniques, the cover frames pixels are directly used to embed the secret message [4]. Many steganography techniques, such as least significant bit (LSB) substitution, pixel value differencing (PVD), spread spectrum, region of interest (ROI), histogram manipulation, most significant bit (MSB), and quantization index modulation (QIM), rely on the spatial domain for hiding [5]. ...
Internet simplified digital data transferring. This data needs to be secured; so securing digital data becomes an important concern. Steganography provides security for data by inserting it into a cover and concealing it. In this paper, a steganography algorithm was introduced. This algorithm used the stationary wavelet transform (SWT) and اhybrid-matrix decomposition techniques, singular value decomposition (SVD) and QR factorization to conceal a video in another video. The algorithm performance was measured with reference to the peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) for the cover and the secret videos. The algorithm successfully hid a video in another cover video and both are of the same size; the hiding capacity was 100%. The algorithm achieved a SSIM that reached 0.97 and a high PSNR value that reached 68.8 proving that the imperceptibility of the proposed algorithm is very high. The comparative analysis shows that the suggested algorithm achieved higher imperceptibility than the other state-of-the-art algorithms regarding the average PSNR. The enhanced version of the proposed method was more robust against different types of attacks.
... The spatial domain approach conceals secret data by replacing the least significant bit (LSB) with original message bits, and other methods like bit-plane and modulation methods. Even though these methods are easy to implement, they are not robust against any type of attacks [20,22]. In the video steganography schemes to embed the secret message inside the video, frames can be utilized only the luminance (Y) component, and the security of the proposed scheme is strengthened by pre-processing the secret message with encryption before embedding and achieve high imperceptibility for still image steganography. ...
... To compute the PSNR, first calculates the mean-squared error using the following Eqs. (22) to (24) for gray image ...
As today’s world are switching to the digital media through the Internet and multimedia tools like Facebook, YouTube, Twitter and WhatsApp which consists of a number of videos, hence it always better to take urgent problems of such digitally transmitted video in terms of information security. The current video steganography approach is not so effective for imperceptibility, robustness, security of hidden secret data, embedding capacity and very good visual recovery of a secret as well as original data. Hence, to maintain the balance between these issues is another big challenge. This work employs a novel and efficient Field Programmable Gate Array (FPGA) implementation of audio, video crypto steganography using General Modified Secured Diamond Encoding (GMSDE) scheme. The new proposed scheme is based on Diamond Encoding (DE), Exploiting Modification Direction (EMD) and Adaptive Pixel Pairing Matching (APPM) algorithms called as General Modified Secured Diamond Encoding (GMSDE). The DE method is always used for k > 1 which produces distortion, less embedding capacity and security of hidden data. The GMSDE scheme changed the Diamond Characteristic Value (DCV) to conceal more than one secret bit vertically and horizontally to create a modified diamond shape of secret data which is equal to log2(2x² + 6x + 5) - ary and produces the conceal capacity of 1.16 to 4.82 bpp for the values of x = 0 to 25 where x is the embedding parameter. Experimental results confirm that the conceal capacity measured by bit per pixel (bpp), security of hidden secret data, very good visual recovery of both original and secret data, Cross-Correlation (CC) and Peak Signal to Noise Ratio (PSNR) values are better than existing approaches. Further through many attacks on stego video during transmission using forensic detection approach, the imperceptibility, security of hidden data and robustness is increased for secure communication.
... The hiding ratio can be computed using the following formula: HR = size of secret data size of cover video (10) And The maximum number of bits allotted for encoding the secret data within the cover frame is represented by the payload, which is determined in terms of bits per pixel using the Eq. (11) that follows (bpp) [26]. Where S indicates how many secret bits are going to be inserted into the cover frame. ...
... As it is challenging for human eyes to observe the small changes marked as forgeries in digital videos, video steganography emerges as technology that buries a message into a video and covers the fact of the transmission [54]. Mstafa et al. [65] describe that a successful steganography system has three essential factors: imperceptibility, robustness, and embedding capacity. Imperceptibility can better relate to the safety of steganography methods and hiding the confidential message in the lodge video. ...
The massive dependence on digital interaction via multimedia tools like audio, images, and videos is leading to an era that will be digitized in almost every aspect. This credible development in multimedia technology with the easy availability of advanced cheap editing or tampering tools/techniques attracts the researcher’s community to ensure the multimedia content’s authenticity. This paper reviews video forensics, the statistical ways manipulations have been deployed on the data, and detection approaches for tracing the tampering attacks and challenges. The study gives better clarity for understanding the demand of direct relation for video content to be shared on social media platforms as the legal evidence towards the growth of tampering detection tools/technology. This paper gives a detailed review of the existing forgery attacks and passive forgery detection techniques. The video forensics algorithm is studied extensively, along with its limitations for varying datasets in an ordered manner. This discussion explores current active challenges in video forensics, raising scientific investigation and developing reliable multimedia forensics approaches.
... Imperceptibility, on the other hand, relates to the degree of efficiency in which data is embedded, as a higher efficiency implies a lower likelihood of detection by potential hackers. Lastly, embedding capacity refers to the amount of data that can be concealed within a cover video [6]. ...
... The performance of proposed FrWEWO-Deep CNN technique is analyzed using various existing techniques, such as DWT+DCT [6], DCNN+DWT [31], DCNN+LSB [12], proposed WEWO-DeepRNN [29] and 3D-CNN [9]. ...
Video steganography is used to conserve the confidential information in various security applications. To give advance protection to the secrete message, pixels locations are optimized using nature inspired algorithm. The input video is separated into a sequence of still image frames then key frames are extracted. The proposed Required Pixel Density (RPD) value calculation and feature extraction are carried out on the extracted frames to perform the frame classification. The frame classification is done using proposed Fractional Water-Earth Worm optimization algorithm based Deep Convolutional Neural Network (FrWEWO-Deep CNN) in order to classify the frames as high, low and medium quality. Thus pixel location prediction is carried out using trained Deep CNN then secret image is hide within high quality frame with Wavelet Transform (WT) and Inverse WT (IWT). Peak Signal to Noise Ratio (PSNR) and Correlation Coefficient (CC) are performance evaluation parameters. For efficient video steganography better imperceptibility and robustness are required. Imperceptibility is a scale of PSNR value showing similarity between original and stego video frames. The robustness of video steganography is measured by CC between embedded and extracted secret images. The proposed algorithm gives enhanced performance is compared with previous state of art such as WEWO-Deep RNN. The PSNR value is progressed from 41.8492 to 46.5728 dB and CC value improved from 0.9660 to 0.9847.
... It was secure to steganalysis. The increasing resemblance between the secret image bitstream and the cover image LSB plane was researched in [24] for increased efficiency. Instead than using traditional binary, a compression-like approach called secret image size reduction (SISR) was shown to minimise the secret image bit-stream and deconstructed cover image pixel values using the Fibonacci scheme. ...
This paper presents an optimal data hiding in videos using optimization based on multi-objective constraints such as, the energy of wavelet, intensity, edge details, and energy of Local Binary Patterns (LBP). The Fractional-Cat swarm optimization (Fractional-CSO) is modelled with the inclusion of fractional calculus in Cat swarm optimization (CSO). Initially, an input video is selected from which frames are generated. The key frames are extracted from those frames using the Contourlet Transform (CT) and Structural Similarity Index (SSIM). Regions are formed on the selected key frames with the help of grid lines. Finally, the optimal region for embedding is interpreted using the proposed optimization algorithm along with multi-objective cost functions to embed the secret message. The secret data is hidden in the optimal region using the Lifting Wavelet Transform (LWT). Then the embedded video is subsequently sent across the network to its intended recipient. The experimental analysis is done using two videos which reveal the effectiveness of the proposed video steganography. The comparative analysis based on the MSE (Mean-Square Error), Peak Signal to Noise Ratio (PSNR) and correlation measure reveals the effectiveness of the method. With MSE of 0.0001, maximal PSNR of 82.273 dB and correlation of 0.9529 respectively shows increase in security of the data with a better quality embedded image. For noise free image, the correlation acquired using the proposed video steganography is 0.9934.
... The practice of inserting a private message into a cover video is known as video steganography. It is utilized in a variety of applications, including copyright, remote access, health fields, and enforcement agencies [14][15][16]. ...
The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information in today's Internet era, digital steganography is vital. Many academics are interested in digital video because it has a great capability for concealing important data. There have been a vast number of video steganography solutions developed lately to guard against the theft of confidential data. The visual imperceptibility, robustness, and embedding capacity of these approaches are all challenges that must be addressed. In this paper, a novel solution to reversible video steganography based on Discrete Wavelet Transform (DWT) and Quick Response (QR) codes is proposed to address these concerns. In order to increase the security level of the suggested method, an enhanced ElGamal cryptosystem has also been proposed. Prior to the embedding stage, the suggested method uses the modified ElGamal algorithm to encrypt secret QR codes. Concurrently, it applies two-dimensional DWT on the Y-component of each video frame resulting in Approximation (LL), Horizontal (LH), Vertical (HL), and Diagonal (HH) sub-bands. Then, the encrypted Low (L), Medium (M), Quantile (Q), and High (H) QR codes are embedded into the HL sub-band, HH sub-band, U-component, and V-component of video frames, respectively, using the Least Significant Bit (LSB) technique. As a consequence of extensive testing of the approach, it was shown to be very secure and highly invisible, as well as highly resistant to attacks from Salt & Pepper, Gaussian, Poisson, and Speckle noises, which has an average Structural Similarity Index (SSIM) of more than 0.91. Aside from visual imperceptibility, the suggested method exceeds current methods in terms of Peak Signal-to-Noise Ratio (PSNR) average of 52.143 dB, and embedding capacity 1 bpp.
... In this paper, we have provided an extensive survey on the stego-crypto methods available in the literature with technical analysis. Although, there exists a number of review articles on the similar topic [4][5][11][12]19,23,33,[45][46]50,52,[68][69], where the authors have mostly classified and discussed the stego-crypto approaches in terms of the mechanism used followed by the comparison amongst those with respect to the cryptographic algorithms and steganographic algorithms that employed. We have, to the contrary, focused on the application oriented stego-crypto models and tried to establish their feasibility issues. ...
Secret message passing through an open channel needs an extreme level of privacy to protect it from theft or misuse. To achieve this objective, two parallel approaches are frequently used in digital media namely – Cryptography and Steganography. Cryptography encrypts the secret data into some unreadable format before sending through shared channel whereas Steganography conceals the secret message within an ordinary, non-secret file in such a way that an eavesdropper cannot suspect its existence. One layer of security, however, may be vulnerable from various security attacks. Hence, both the methods can be combined to achieve more secure as well as powerful model termed as Crypto-stego model. In this paper, an extensive survey is presented on Stegano-encryption techniques that are applied to various real-world systems which need high security. The survey also provides a thematic approach to classify available state-of-the-arts with regards to different application domains where it could be used. The rigorous survey follows the security threats along with various security-analysis that can establish a system as robust and safe from attacks.
... Cover and secret data could be of any type of digital data, such as a text file, an image, a sound file or a video [3]. Steganography methods can be categorized as substitution methods, spread spectrum methods, statistical methods, transform domain methods, distortion and cover generation methods [1]. ...
... Steganography is mainly used in secret communications through an unsecured communication channel and a cover media. The most commonly used cover media are texts, images, sounds and videos [6][7][8][9]. ...
Distributed steganography is an approach to concealing the secret in several files, leaving fewer traces than the classical approach. Recent work proposed by Moyou and Ndoumdan have improved this approach by preserving the integrity of these files in a multi-cloud storage environment. However, the approach requires a large size of the stego-key and the management of several cloud storage environments. Our contribution consists is to improve this approach by using a single cloud storage environment and reducing the size of the stego-key. In this work, a single cloud storage environment is used to solve the problems of managing several credentials, monetary costs and data controls associated with multi-cloud storage environments. The comparisons showed interesting results with simpler operations to be performed by the participants during the process.
... Seeing that the PSNR value of the original image and the stego-image is only slightly different. In addition, the studies [11,12,13,16] listed some video steganography methods, difficulties, challenges as well as the advantages and disadvantages of video steganography techniques. Besides, Spaulding et al. [14] presented the BPCS steganography method with the embedded zerotree wavelet (EZW) lossy compression. ...
... Mstafa et al. (Mstafa & Elleithy, 2017) presented a comprehensive survey on raw and compressed video format-based steganography techniques in which theoretical analysis of some of the latest techniques has been done. Further, Mstafa et al. (Mstafa et al., 2017b) also presented the classification scheme for video steganography with some of the challenges, and future recommendations for the researchers intended to research in this field. ...
Videos are nowadays the most frequent and easy mode of communication over the internet; the reason behind the growth is the accessibility to video processing software available on the internet. Video steganography is a field where the data is embedded in video keeping the visual quality of the video intact. This study presents a new video steganography scheme with a stable trade-off between robustness and imperceptibility using 2D-DWT (Discrete Wavelet Transform) based on object detection and tracking. The main contribution of this paper includes embedding of secret data in the moving objects after applying object detection for the video frames where the secret bits are embedded in middle frequency sub-bands after applying 2D-DWT. To highlight the effectiveness of the proposed scheme, experimental results are carried out both quantitatively and qualitatively where quantitative analysis is done using different metrics such as PSNR, SSIM, BER and qualitative analysis is done using visual results of the frames. The experimental results illustrated that the proposed approach outperforms existing techniques in terms of qualitative and quantitative evaluation with high imperceptibility and robustness against noise attack. Eventually, the scheme has also been tested against existing steganalysis techniques to ensure the security of the proposed scheme.
... Video steganography is the process of embedding a confidential message into a cover video. Where, it is used in many fields such as copyright protection, access control, medical systems, law enforcement [17]- [19]. ...
Recent developments in the speed of the Internet and information technology have made the rapid exchange of multimedia information possible. However, these developments in technology lead to violations of information security and private information. Digital steganography provides the ability to protect private information that has become essential in the current Internet age. Among all digital media, digital video has become of interest to many researchers due to its high capacity for hiding sensitive data. Numerous video steganography methods have recently been proposed to prevent secret data from being stolen. Nevertheless, these methods have multiple issues related to visual imperceptibly, robustness, and embedding capacity. To tackle these issues, this paper proposes a new approach to video steganography based on the corner point principle and LSBs algorithm. The proposed method first uses Shi-Tomasi algorithm to detect regions of corner points within the cover video frames. Then, it uses 4-LSBs algorithm to hide confidential data inside the identified corner points. Besides, before the embedding process, the proposed method encrypts confidential data using Arnold's cat map method to boost the security level. Experimental results revealed that the proposed method is highly secure and highly invisible, in addition to its satisfactory robustness against Salt & Pepper noise, Speckle noise, and Gaussian noise attacks, which has an average Structural Similarity Index (SSIM) of more than 0.81. Moreover, the results showed that the proposed method outperforms state-of-the-art methods in terms of visual imperceptibility, which offers excellent peak signal-to-noise ratio (PSNR) of average 60.7 dB, maintaining excellent embedding capacity. INDEX TERMS Arnold's Cat map, corner detector, embedding capacity, imperceptibility, robustness, security, video steganography.
... With the passage of time, attackers developed tools to decrypt steganography messages and hence the protection of sensitive information once again emerged problematic. More on this science and surrounding issues can be learned from [12][13][14]. Some of these issues are listed below. ...
The great developments in the world of communications and the advancement of the associated technologies, such as the Internet of Things (IoT) with web-based and mobile applications, have changed our way of life. This has created a kind of linkage between virtual and real worlds, rendering applications and services to be ubiquitous. We are also witnessing a phenomenon in which the electronic devices that connect to the Internet and are widespread making use of technology and providing a better level of service to users. However, sending and receiving information over the Internet generates many issues and problems. The most serious of them is the security and protection of transmitted information. This issue has become one of the most important things which is a matter of concern to researchers as well as the users themselves. Ensuring privacy and security of the transmitted data is a matter of urgency and cannot be neglected while dealing with the transmission of data using the services and tools in the IoT. In this article, we provide an improved algorithm to increase the protection level of transmitted information by means of cryptographic encryption so that this information cannot be seen by others or disclosed to anybody. This algorithm has been evolved as an application that works on mobile phones so that any user can benefit from it when exchanging sensitive and confidential information such as account numbers and passwords with other users.
... More especially, since the last two decades many information hiding techniques have been developed such as digital watermarking, Cryptography and Steganography [12]. The common objective of both steganography and cryptography is to provide confidentiality and protection of data [3]. Indeed, Cryptography and Steganography are two popular ways of sending essential information in a confidential way. ...
Communication security has taken vital role with the advancement in digital communication. The universal use of internet for communication has increased the attacks to users. The security of information is the present issue related to privacy and safety during storage and communication. This paper deals with the proposition of a multilayered secure channel to transfer sensitive data/video over an unreliable network. The secret video is first encrypted using the NOLSB algorithm. The cipher video produced is hidden in a video file with more size. This video file is in turn encrypted following the (m,k) firm technique to maximize resource utilization and to optimize the bandwidth. Then video shares are sent over many channels in the network in order to assure security. This method guarantee that, even if some shares got lost over network, video files could be recovered at the end receiver without need to resend the video file by the sender.
... These techniques have been preferred recently for information hiding as information could be hidden in the frames so that its security can be improved. This is due to the fact that human eyes cannot recognize it compared to the simple data [17,18]. ...
... Steganography is an art of hiding different kinds of information such as texts, sounds and images in another different digital media. So, only the transmitter and receiver know the existence of hidden information [1,2,3,4]. inside cover digital media such as video. It is different from cryptography science in terms that the attacker does not suspect there is hidden information inside digital cover while the encryption converts plain information into another apparent scrambled information. ...
Multimedia steganography is one of the most important technologies to secure different kinds of data in today networked environment. It can embed large amounts of data safely inside multimedia files in objective to deviate the attention of attackers of existing data. In addition, the data encryption techniques can be added with steganography technologies to strength data protection. In this paper, we proposed a method to hide image and text files inside a video using LSB technique and chaotic systems. Two keys are used to secure data such that first key employed to select specific frames form video and the second key to select columns inside selected frame images to embed data. Three image quality measures are used to compute the quality of Stego images in our experiments including MSE, PSNR and SSIM. Experimental results show that the proposed method is secure enough to prevent attackers from stealing encrypted images and text files.
... DFT techniques are discussed. A complete analysis based upon embedding capacity, video quality and robustness of all existing techniques is also represented in this paper [15]. Achmad Solichin et al. (2016) represent Least Significant Frame method in which a frame is used to embed secret data based on optical flow. ...
... Further, Mstafa et al. [20] also discussed some of the latest techniques of video steganography in the compressed and raw domain in a comprehensive survey. In addition, Mstafa et al. [22] presented some of the challenges faced by researchers in video steganography with some future directions to help interested researchers in the field of video steganography. ...
In this era of internet transfer of information is in digital form using multimedia files such as image, video, audio, etc. which relies on secure communication techniques to convey information safely. Due to the frequent transfer of videos over the internet nowadays they have become a good cover media for secure and covert communication in the form of video steganography. For efficient video steganography, it must fulfill its basic requirements such as capacity, imperceptibility, and robustness. In order to make a balance between imperceptibility and robustness, an efficient video steganography scheme is proposed for Standard Definition (SD) and High Definition (HD) videos. This scheme employs DWT (discrete wavelet transforms) for embedding the secret message inside the video frames utilizing only luminance (Y) component, and the security of the proposed scheme is strengthen by pre-processing the secret message with encryption before embedding. The embedding process is done by utilizing the middle-frequency sub-bands after applying second level 2-D DWT to the video frames to decompose it into 16 sub-bands. The performance of the proposed scheme is tested on different videos with quality metrics including peak signal to noise ratio (PSNR), structural similarity (SSIM) index, bit error rate (BER) and also by applying Gaussian and salt & pepper noise attacks. Moreover, the scheme is tested for the different level of compression on stego-video and also compared with U and V components used while embedding. Experimental results show that for both types of videos (HD and SD) the proposed scheme is able to achieve high imperceptibility. Further, it also provides robustness against different types of noise attacks and different compression levels which makes the proposed scheme evident for secure data transmission.
Steganography is the art of concealing information within other data to obscure the transmission process. Digital photos are the preferred carrier files due to their ubiquity online. Various steganography techniques exist for hiding sensitive data in video frames, each with distinct strengths and weaknesses. Some applications require total invisibility for critical information, while others can accommodate larger secret messages. Our project conceals messages within visuals, enabling users to select replacement bits instead of employing less secure LSB substitution. Data transmission, the process of sending data from source to destination, often involves slower mediums like coaxial cables and twisted pair wires, which can result in data leaks or losses. To address these issues, fiber optics are employed. Fiber optics transmited data as light beams, minimizing data leakage and incorporating security measures. In our proposed system, we enhance fiber optic encryption through the use of images. Key Words: Steganography, data concealment, digital photos, steganography techniques, data invisibility, LSB substitution, data transmission, coaxial cables, twisted pair wires, fiber optics, data security, image encryption.
The steganography is applied on text, image, video, and audio files. The steganography is useful
for safe and secure data transmission. Video steganography is used to preserve confidential information of
security applications. To improve security of the message, pixels locations are optimized using nature
inspired algorithm. As conventional algorithms have a low convergence rate a new algorithm is proposed.
A New algorithm is developed by combining two model algorithms namely, Water wave optimization
(WWO) and Earth worm optimization (EWO) and is renamed as proposed Water-Earth Worm Optimization
(WEWO) algorithm. The frames are preprocessed and extracted using Discrete Cosine transform (DCT) and
Structured Similarity index (SSIM), respectively, as regular processing. For pixel prediction, the fitness
function is obtained from neighborhood entropies in proposed algorithm. In this method, secret message is
embedded with two level decomposition of Wavelet Transform (WT). In the proposed work is tested with
‘CAVIAR’ dataset. The Proposed WEWO-Deep RNN algorithm performance is tested with modular noises
such as, pepper, salt and pepper noises. The proposed method gives enhanced performance, which is seen
with the parameters, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Correlation
Coefficient (CC) which defines image quality indices.
Information has always constituted a prized commodity over time, with the strong globalization of exchanges and communications. The provenance, acquisition, protection and integrity of information has always asked major questions, with the strong growth of security needs in many areas around the world. Numerous approaches have been proposed with a view mainly to increase information security. One of them is steganography, where the goal is to conceal the very presence of secret information in a media during a communication. However, this one generally modifies the properties of the cover media used to conceal secret information. Thus, this modification constitutes a vulnerability during the detection and extraction of information concealed in the media, by various steganography attacks. To overcome this problem, Moyou and Ndoundam have proposed a distributed method of data hiding in a multi-cloud storage environment that preserves the property of the cover media, by using different types of media as an index of a part of the secret. However, a security problem is revealed when sharing key between the participating entities in the communication, and the process of managing cloud storage environments between the participating entities can turns to be tedious, depending on the number of cloud accounts used in the method. In order to solve these problems, in this paper we propose a new approach of the method that uses a single cloud storage environment, and strengthens the security of key sharing between the participating entities.
Presently, fraud in online data transmission becomes a more critical and serious issue due to its security and authentication. This paper contributes and provides the correct path to these problems. Till date, many such aspects have been developed using the data embedding approach to embed the one-bit secret data into the video which produces less security and authentication. The implemented concept provides authentication and security aspects where more than three bits are embedded into video pixels using the forensic pixel adjustment mapping (FPAM) technique. The different types of image processing attacks are also tested which do not create any distortion. The extensive observed and verified software results of implemented approach have been compared to the state-of-the-art video data embedding methods. It is observed that the implemented forensic video data embedding technique is better as compared to any existing approaches.
The current coverless text steganography methods have a low steganographic capacity, and yet some of them cannot assure a message can be concealed. How to achieve a high steganographic capacity has become the research hotspot in text steganography. This paper proposes a text coverless steganography method by encoding the Chinese characters’ component structures. Its main idea is that a binary bit string can be conveyed by the Chinese characters’ component structures. The positions of Chinese characters that carry a secret message will be expressed in two systems of the linear remainder equations, whose solutions will be secretly sent to the receiver to extract the secret message. In the method, a single Chinese character can express p bits. The analyses and statistics show that its capacity will be much higher when the same Chinese character is used more than once than existing methods, and it can conceal any message successfully. In addition, this method can also be employed in other languages.
Securing information has been very anxious regarding the advancement of data science, technology as well as research fields. To resolve the security issues, information hiding algorithms have developed based on deep learning technique. Steganography refers to the process of hiding information within specific files whereas Steganalysis refers the process of recognition of hidden information within those files. In this chapter, we have reviewed several existing work done by various researchers on steganography videos and images using both machine learning and deep learning algorithms. In addition, we focused on Convolutional Neural Network framework, block diagrams for performing Steganalysis process especially hidden information that referred by several researchers. It has five sections namely image steganography, video steganography, automatic detection, integration of audio and video steganography, and finally state of art using deep learning algorithms have illustrated. This proposed review creates an entire idea on steganography videos and image data hiding based on both ML and DL technique.
The steganography is applied on text, image, video, and audio files. The steganography is useful for safe and secure data transmission. Video steganography is used to preserve confidential information of security applications. To improve security of the message, pixels locations are optimized using nature inspired algorithm. As conventional algorithms have a low convergence rate a new algorithm is proposed. A New algorithm is developed by combining two model algorithms namely, Water wave optimization (WWO) and Earth worm optimization (EWO) and is renamed as proposed Water-Earth Worm Optimization (WEWO) algorithm. The frames are preprocessed and extracted using Discrete Cosine transform (DCT) and Structured Similarity index (SSIM), respectively, as regular processing. For pixel prediction, the fitness function is obtained from neighborhood entropies in proposed algorithm. In this method, secret message is embedded with two level decomposition of Wavelet Transform (WT). In the proposed work is tested with 'CAVIAR' dataset. The Proposed WEWO-Deep RNN algorithm performance is tested with modular noises such as, pepper, salt and pepper noises. The proposed method gives enhanced performance, which is seen with the parameters, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Correlation Coefficient (CC) which defines image quality indices.
Background
In terms of data-hiding areas, video steganography is more advantageous compared to other steganography techniques since it uses video as its cover medium. For any video steganography, the good trade-off among robustness, imperceptibility, and payload must be created and maintained. Even though it has the advantage of capacity, video steganography has the robustness problem especially regarding spatial domain is used to implement it. Transformation operations and statistical attacks can harm secret data. Thus, the ideal video steganography technique must provide high imperceptibility, high payload, and resistance towards visual, statistical and transformation-based steganalysis attacks.
Methods
One of the most common spatial methods for hiding data within the cover medium is the Least Significant Bit (LSB) method. In this study, an LSB-based video steganography application that uses a poly-pattern key block matrix (KBM) as the key was proposed. The key is a 64 × 64 pixel block matrix that consists of 16 sub-pattern blocks with a pixel size of 16 × 16. To increase the security of the proposed approach, sub-patterns in the KBM are allowed to shift in four directions and rotate up to 270° depending on the user preference and logical operations. For additional security XOR and AND logical operations were used to determine whether to choose the next predetermined 64 × 64 pixel block or jump to another pixel block in the cover video frame to place a KBM to embed the secret data. The fact that the combination of variable KBM structure and logical operator for the secret data embedding distinguishes the proposed algorithm from previous video steganography studies conducted with LSB-based approaches.
Results
Mean Squared Error (MSE), Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR) parameters were calculated for the detection of the imperceptibility (or the resistance against visual attacks ) of the proposed algorithm. The proposed algorithm obtained the best MSE, SSIM and PSNR parameter values based on the secret message length as 0.00066, 0.99999, 80.01458 dB for 42.8 Kb of secret message and 0.00173, 0.99999, 75.72723 dB for 109 Kb of secret message, respectively. These results are better than the results of classic LSB and the studies conducted with LSB-based video steganography approaches in the literature. Since the proposed system allows an equal amount of data embedding in each video frame the data loss will be less in transformation operations. The lost data can be easily obtained from the entire text with natural language processing. The variable structure of the KBM, logical operators and extra security preventions makes the proposed system be more secure and complex. This increases the unpredictability and resistance against statistical attacks. Thus, the proposed method provides high imperceptibility and resistance towards visual, statistical and transformation-based attacks while acceptable even high payload.
The proposed research work presents a comparative analysis of Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) based video steganography in compressed domain. In this method, the random numbered secret frames are selected from the sequence of RGB cover video. This method increases the complexity level of video steganography by considering the specific host to conceal secret data. It extracts the specific non-dynamic region from secret frame, transforms the pixel value of non-dynamic region into frequency domain using transform coefficient DCT or DST. The random Least Significant Bit (LSB) of integer component of DCT and DST is used as a carrier object that leads to good video quality and secret data-carrying capacity. Furthermore, the secure compressed stego video is reconstructed by using H.264 video compression technique facilitates communication over the network channel between sender and receiver. The proposed method has been experimented on some well-known video datasets by considering RGB images with different resolutions as a secret message. The efficiency of proposed video steganography method is evaluated by performance evaluation parameters; imperceptibility, robustness, and embedding capacity and the improved results of proposed method have been compared with reported methodologies.
Kulkarni, VinayJoshi, YashwantManthalkar, RamchandraBrain–Computer Interface (BCI) is a vibrant topic in rehabilitation engineering. It is essential to have informative features and practical classification algorithms for the appropriate communication between humans and machines. This paper focuses on improving accuracy in detecting elbow movements and analyzing the effect of kinematic movement variability over the sensory-motor cortex with 10–20 EEG system. The EEG data from healthy volunteers was acquired by training them for a proposed protocol. These healthy volunteers were asked to play a PC game intended for rehabilitation with his/her elbow movement utilizing the ArmeoSpring treatment instrument. The input raw EEG signal is passed through 8–30 Hz bandpass filter. The Common Spatial Pattern (CSP), Event-Related Desynchronization (ERD)/Synchronization (ERS), and Autoregressive Moving Average (ARMA) modeling features are estimated and tested with SVM classifier. The proposed framework can differentiate and classify the kinematic movements of the elbow with an average accuracy of 84.61, 92.77, and 97.26% for CSP, ARMA, and ERD/ERS features, respectively. The experimental results on the proposed dataset demonstrate that the combination of feature extraction techniques and classifiers improves the classification performance, which would benefit the BCI rehabilitation community.
The proposed research work presents a novel data hiding method for video steganography in the compressed domain. In this method, the random numbered secret frames are selected from the RGB cover video sequence. This method increases the complexity level of video steganography by considering the specific host to conceal confidential data. It extracts the specific non-dynamic region from the secret frame and transforms the pixel value to the frequency domain using Fast Fourier Transform (FFT). The usage of random Least Significant Bit (LSB) of the real part of FFT as a carrier object leads to good video quality and secret data-carrying capacity. Furthermore, the secure compressed stego video is reconstructed using the H.264 video compression technique. The proposed method is experimented on some well-known video datasets by considering RGB images with different resolutions as a secret message. Performance evaluation parameters evaluate the proposed method’s efficiency, imperceptibility, robustness, and embedding capacity, and the improved results are compared with reported methodologies. The results show a significant improvement in the imperceptibility as a Peak Signal-to-Noise Ratio (PSNR) value is reached up to infinity (Inf) in some cases. At the same time, the similarity between embedded and extracted message is achieved nearer to 1 with the negligible Bit Error Rate (BER) less than 0.1%, and the embedding capacity greater than 0.5% in all cases indicates an excellent sign of carrying a big amount of confidential data.
Steganography is the art of hiding messages or files in a way that prevents the detection of the existence of these hidden messages. It encompasses several techniques, including physical methods like invisible ink on paper and digital techniques like hiding text on multimedia files like images and music files. In the modern digital era, steganography has become a useful tool to evade detection and perusal of secret messages. With the advent of social media, it is very easy to encode a message or file onto an image and upload it online for the intended recipients to access, decode, and read or use. In this case of digital steganography of messages or files onto images, an important factor to consider is the effect of image compression on the hidden message. Since most social media and other online image posting websites run some sort of compression, cropping, and other image transformations on the uploaded images, understanding these techniques and their effect on the hidden text can help one choose the most suitable steganography technique to use for a particular use case.
In this research work, an efficient robust video steganography in compressed domain is presented based on discrete cosine transform (DCT) encoded with H.264 codec. In this method, a compressed video (.mp4) of different resolutions, frame rates and sizes are used as a cover and RGB image is used as a secret message. Using appropriate stego key, the secret frames from the sequence of video frames are selected and the non-dynamic pixels of these frames are identified. The least significant bits (LSB) of the DCT component of these non-dynamic pixels are used as carrier object for hiding the R, G, and B components of secret message individually. An appropriate embedding key is designed to embed secret message in cover video such that the quality assessment parameters viz. Peak signal-to-noise ratio (PSNR) and mean square error (MSE) of imperceptibility can be optimized. Also, the successful extraction of secret message from the cover stego video is assessed by the robustness parameters viz. Bit error rate (BER) and similarity (Sim). The hiding capacity of proposed video steganography with respect to secret message and cover frame is measured by using hiding ratio (HR). The efficiency of proposed video steganography method is compared with the reported methodologies on the basis of the parameters of imperceptibility and robustness.
In the last few decades, information security has gained huge importance owing to the massive growth in digital communication; hence, driving steganography to the forefront for secure communication. Steganography is a practice of concealing information or message in covert communication which involves hiding the information in any multimedia file such as text, image, or video. Many contributions have been made in the domain of image steganography; however, due to the low embedding capacity and robustness of images; videos are gaining more attention of academic researchers. This paper aims to provide a qualitative as well as quantitative analysis of various video steganography techniques by highlighting their properties, challenges, pros, and cons. Moreover, different quality metrics for the evaluation of distinct steganography techniques have also been discussed. The paper also provides an overview of steganalysis attacks which are commonly employed to test the security of the steganography techniques. The experimental analysis of some of the prominent techniques using different quality metrics has also been done. This paper also presented a critical analysis driven from the literature and the experimental results. The primary objective of this paper is to help the beginners to understand the basic concepts of this research domain to initiate their research in this field. Further, the paper highlighted the real-life applications of video steganography and also suggested some future directions which require the attention of the research community.
The proposed research work is presenting a novel approach in the field of steganography, especially in the compressed video domain with optimum imperceptibility to secure the secret information. In this approach, the specific secret cover video frames are selected from the sequence of video frame from which the non-dynamic region is separated. Discrete sine transform (DST) transforms this non-dynamic region from spatial domain to frequency domain. The least significant bits (LSBs) of the integer part of DST components are used to conceal the secret data. The H.264 codec is used to construct the compressed stego video using intra-frame, inter-frame prediction, motion vector estimation, transform coefficient, i.e., Discrete Cosine Transform (DCT), quantization, and entropy coding. The efficiency of the proposed hybrid technique “DST- Secret Bit Positions of Non-dynamic Region for Message (DST-SBPNRM)” for video steganography is measured by evaluating imperceptibility, robustness and embedding capacity. Moreover, the proposed technique is experimented on the well-defined video dataset and the obtained results are compared with the related work to validate the significance of the proposed work.
Video steganography is becoming an important research area in various data hiding technologies, which has become a promising tool because not only the security requirement of secret message transmission is becoming stricter but also video is more favored. In this paper, according to the embedded position of secret message, video steganography is divided into three categories: intra-embedding, pre-embedding and post-embedding. Intra-embedding methods are categorized according to the video compression stages such as intra-prediction, motion vectors, pixels interpolation, transform coefficients. Pre-embedding methods are manipulated on the raw video, which can be classified into spatial and transform domains. Post-embedding methods are mainly focused on the bitstreams, which means the procedure of embedding and extraction of video steganography are all manipulated on the compressed bit stream. Then we introduce the performance assessment for video steganography and the future popular video steganography including H.265 video steganography, robust video steganography and reversible video steganography. And challenges are finally discussed in this paper.
Due to the significant growth of video data over the Internet, it has become a popular choice for data hiding field. The performance of any steganographic algorithm relies on the embedding efficiency, embedding payload, and robustness against attackers. Low hidden ratio, less security, and low quality of stego videos are the major issues of many existing steganographic methods. In this paper, we propose a DCT-based robust video steganographic method using BCH codes. To improve the security of the proposed algorithm, a secret message is first encrypted and encoded by using BCH codes. Then, it is embedded into the discrete cosine transform (DCT) coefficients of video frames. The hidden message is embedded into DCT coefficients of each Y, U, and V planes excluding DC coefficients. The proposed algorithm is tested under two types of videos that contain slow and fast moving objects. The results of the proposed algorithm are compared with three existing methods. The results demonstrate better performance for the proposed algorithm than for the others. The hidden ratio of the proposed algorithm is approximately 27.53%, which is evaluated as a high hiding capacity with a minimal tradeoff of the visual quality. The robustness of the proposed algorithm was tested under different attacks.
Due to the significant growth of video data over the Internet, video steganography has become a popular choice. The effectiveness of any steganographic algorithm depends on the embedding efficiency, embedding payload, and robustness against attackers. The lack of the preprocessing stage, less security, and low quality of stego videos are the major issues of many existing steganographic methods. The preprocessing stage includes the procedure of manipulating both secret data and cover videos prior to the embedding stage. In this paper, we address these problems by proposing a novel video steganographic method based on Kanade-Lucas-Tomasi (KLT) tracking using Hamming codes (15, 11). The proposed method consists of four main stages: a) the secret message is preprocessed using Hamming codes (15, 11), producing an encoded message, b) face detection and tracking are performed on the cover videos, determining the region of interest (ROI), defined as facial regions, c) the encoded secret message is embedded using an adaptive LSB substitution method in the ROIs of video frames. In each facial pixel 1 LSB, 2 LSBs, 3 LSBs, and 4 LSBs are utilized to embed 3, 6, 9, and 12 bits of the secret message, respectively, and d) the process of extracting the secret message from the RGB color components of the facial regions of stego video is executed. Experimental results demonstrate that the proposed method achieves higher embedding capacity as well as better visual quality of stego videos. Furthermore, the two preprocessing steps increase the security and robustness of the proposed algorithm as compared to state-of-the-art methods.
Bit-plane complexity segmentation (BPCS) steganography is advantageous in its capacity and imperceptibility. The important step of BPCS steganography is how to locate noisy regions in a cover image exactly. The regular method, black-and-white border complexity, is a simple and easy way, but it is not always useful, especially for periodical patterns. Run-length irregularity and border noisiness are introduced in this paper to work out this problem. Canonical Cray coding (CGC) is also used to replace pure binary coding (PBC), because CGC makes use of characteristic of human vision system. Conjugation operation is applied to convert simple blocks into complex ones. In order to contradict BPCS steganalysis, improved BPCS steganography algorithm adopted different bit-planes with different complexity. The higher the bit-plane is, the smaller the complexity is. It is proven that the improved BPCS steganography is superior to BPCS steganography by experiment.
Image Steganography is a thriving research area of information security where secret data is embedded in images to hide its existence while getting the minimum possible statistical detectability. This paper proposes a novel magic least significant bit substitution method (M-LSB-SM) for RGB images. The proposed method is based on the achromatic component (I-plane) of the hue-saturation-intensity (HSI) color model and multi-level encryption (MLE) in the spatial domain. The input image is transposed and converted into an HSI color space. The I-plane is divided into four sub-images of equal size, rotating each sub-image with a different angle using a secret key. The secret information is divided into four blocks, which are then encrypted using an MLE algorithm (MLEA). Each sub-block of the message is embedded into one of the rotated sub-images based on a specific pattern using magic LSB substitution. Experimental results validate that the proposed method not only enhances the visual quality of stego images but also provides good imperceptibility and multiple security levels as compared to several existing prominent methods.
Recently, video steganography has become a popular option for a secret data communication. The performance of any steganography algorithm is based on the embedding efficiency, embedding payload, and robustness against attackers. In this paper, we propose a novel video steganography algorithm in the wavelet domain based on the KLT tracking algorithm and BCH codes. The proposed algorithm includes four different phases. First, the secret message is preprocessed, and BCH codes (n, k, t) are applied in order to produce an encoded message. Second, face detection and face tracking algorithms are applied on the cover videos in order to identify the facial regions of interest. Third, the process of embedding the encoded message into the high and middle frequency wavelet coefficients of all facial regions is performed. Forth, the process of extracting the secret message from the high and middle frequency wavelet coefficients for each RGB components of all facial regions is accomplished. Experimental results of the proposed video steganography algorithm have demonstrated a high embedding efficiency and a high embedding payload.
Video steganography has become a popular topic due to the significant growth of video data over the Internet. The performance of any steganography algorithm depends on two factors: embedding efficiency and embedding payload. In this paper, a high embedding payload of video steganography algorithm has been proposed based on the BCH coding. To improve the security of the algorithm, a secret message is first encoded by BCH(n,k,t) coding. Then, it is embedded into the discrete wavelet transform (DWT) coefficients of video frames. As the DWT middle and high frequency regions are considered to be less sensitive data, the secret message is embedded only into the middle and high frequency DWT coefficients. The proposed algorithm is tested under two types of videos that contain slow and fast motion objects. The results of the proposed algorithm are compared to both the Least Significant Bit (LSB) and [1] algorithms. The results demonstrate better performance for the proposed algorithm than for the others. The hiding ratio of the proposed algorithm is approximately 28%, which is evaluated as a high embedding payload with a minimal tradeoff of visual quality. The robustness of the proposed algorithm was tested under various attacks. The results were consistent.
people are becoming more worried about information being hacked by attackers. Recently, many algorithms of steganography and data hiding have been proposed. Steganography is a process of embedding the secret information inside the host medium (text, audio, image and video). Concurrently, many of the powerful steganographic analysis software programs have been provided to unauthorized users to retrieve the valuable secret information that was embedded in the carrier files. Some steganography algorithms can be easily detected by steganalytical detectors because of the lack of security and embedding efficiency. In this paper, we propose a secure video steganography algorithm based on the principle of linear block code. Nine uncompressed video sequences are used as cover data and a binary image logo as a secret message. The pixels' positions of both cover videos and a secret message are randomly reordered by using a private key to improve the system's security. Then the secret message is encoded by applying Hamming code (7, 4) before the embedding process to make the message even more secure. The result of the encoded message will be added to random generated values by using XOR function. After these steps that make the message secure enough, it will be ready to be embedded into the cover video frames. In addition, the embedding area in each frame is randomly selected and it will be different from other frames to improve the steganography scheme's robustness. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that we have obtained. Regarding the system's quality, the Pick Signal to Noise Ratio (PSNR) of stego videos are above 51 dB, which is close to the original video quality. The embedding payload is also acceptable, where in each video frame we can embed 16 Kbits and it can go up to 90 Kbits without noticeable degrading of the stego video's quality.
In this paper, a robust lossless data hiding scheme on uncompressed video data based on histogram distribution constrained (HDC) scheme is proposed. The proposed method is a reversible data hiding algorithm which enables exact recovery of the original video without any distortion after extracting hidden information, if the watermarked video is not affected by any other process. The algorithm is robust against H.246/AVC video compression. In the proposed method, the luminance components of video frames are used to embed the watermark data bits. The luminance component is divided into non-overlapping blocks and the arithmetic difference of each block is computed. In the next step, the hiding data are embedded into the blocks by shifting the arithmetic difference values. The performance of the proposed algorithm is evaluated with respect to imperceptibility, robustness against H.264 video coding and data payload capacity by simulations. Simulation results demonstrate a high performance for the proposed method.
This paper proposes two data hiding approaches using compressed MPEG video. The first approach hides message bits by modulating the quantization scale of a constant bitrate video. A payload of one message bit per macroblock is achieved. A second order multivariate regression is used to find an association between macroblock-level feature variables and the values of a hidden message bit. The regression model is then used by the decoder to predict the values of the hidden message bits with very high prediction accuracy. The second approach uses the flexible macroblock ordering feature of H.264/AVC to hide message bits. Macroblocks are assigned to arbitrary slice groups according to the content of the message bits to be hidden. A maximum payload of three message bits per macroblock is achieved. The proposed solutions are analyzed in terms of message extraction accuracy, message payload, excessive bitrate and quality distortion. Comparisons with previous work reveal that the proposed solutions are superior in terms of message payload while causing less distortion and compression overhead.
Using the least significant bits in an image, in this paper we propose two new techniques that use truth table based and determinate array on RGB indicator that utilizes the idea of pixel manipulation and stegokey and deploy them together using the least two significant bits of one of existing channels in the purpose to indicate to data existence in other channels using a (bmp) image format . This technique has come with amazing results especially in data-bit capacity that is hidden and related to the RGB image pixels.
In this work we propose a new algorithm for fragile, high capacity yet file-size preserving watermarking of MPEG-2 streams. Watermarking is done entirely in the compressed domain, with no need for full or even partial decompression. The algorithm is based on a previously developed concept of VLC mapping for compressed domain watermarking. The entropy-coded segment of the video is first parsed out and then analyzed in pairs. It is recognized that there are VLC pairs that never appear together in any intra-coded block. The list of unused pairs is systematically generated by the intersection of "pair trees." One of the trees is generated from the main VLC table given in ISO/IEC 13818-2:2000 standard. The other trees are dynamically generated for each intra coded blocks. Forcing one VLC pairs in a block to one of the unused ones generates a watermark block. The change is done while maintaining run/level change to a minimum. At the decoder, the main pair tree is created offline using publicly available VLC tables. Through a secure key exchange, the indices to unused code pairs are communicated to the receiver. We show that the watermarked video is reasonably resistant to forgery attacks and remains secure to watermark detection attempts.
In this paper, we present a novel data-embedding system with high embedding capacity. The embedding algorithm is based on the quantized projection embedding method with some enhancement to achieve high embedding rates. In particular, our system uses a random permutation of the columns of a Hadamard matrix as projection vectors and a fixed perceptual mask based on the JPEG default quantization table for the quantization step design. As a result, the data-embedding system achieves 1/167 (1 bit out of 167 raw image bits) to 1/84 hiding ratios with a BER of around 0.1% in the presence of JPEG compression attacks, while maintaining visual distortion at a minimum.
A content authentication watermarking algorithm based on the CABAC entropy coding for the H.264/AVC is proposed in this paper. The specific motion vector difference in P and B frames are selected according to the characteristic of the CABAC, the watermarks are embedded by replacing the binary sequence of the selected syntax elements regularly. The watermarks can be extracted just by decoding part of the motion vector difference and do not need the original video stream, which meets the requirement of the modern detection of real-time perfectly. Simulation results show that the algorithm can achieve a great embedding capability as well as the slight bit-rate increase and visual distortion.
Steganography is the art of secret communication. Since the advent of modern steganography, in the 2000s, many approaches based on the error correcting codes (Hamming, BCH, RS, STC ...) have been proposed to reduce the number of changes of the cover medium while inserting the maximum bits. The works of LDiop and al [1], inspired by those of T. Filler [2] have shown that the LDPC codes are good candidates in minimizing the impact of insertion. This work is a continuation of the use of LDPC codes in steganography. We propose in this paper a steganography scheme based on these codes inspired by the adaptive approach to the calculation of the map detectability. We evaluated the performance of our method by applying an algorithm for steganalysis.
Analyze H.264 standard's excellent, an information hiding scheme compatible with H.264 baseline is proposed. The scheme takes into account the features of Context Adaptive Variable Length Coding (CAVLC) which is used in H.264 baseline entropy coding. By modifying trailing ones sign flag and levels' words in CAVLC, embedding information can be achieved. This scheme directly operates on the 4×4 residual data blocks. New codeword replacing original one make the embedding algorithm has a greater capacity and does not increase the rate. Meanwhile, the scheme modifies the high-frequency coefficients, which has good invisibility.
A matrix embedding (ME) code is a commonly used steganographic technique that used linear block codes to perform the embedding process. However, a lack of low-complexity maximum-likelihood decoding schemes in linear block codes limited the embedding efficiency for sufficiently large lengths. This paper proposes a novel and practical hiding algorithm for binary data based on convolutional codes. Compared to a matrix embedding algorithm that uses linear block codes, the method proposed in this study is appropriate for embedding a sufficiently long message into a cover object. The proposed method employs the Viterbi decoding algorithm for embedding to identify the coset leader of convolutional codes for large payloads. Experimental results show that the embedding efficiency of the proposed scheme using convolutional codes is substantially superior to that of the scheme using linear block codes.
Visual steganography is the most widely practiced form of steganography. It started with concealing messages within the lowest bits of noisy images or sound files. We shall perform steganography on video files and hide the message in an encrypted format, thus achieving a multiple cryptographic system. The most commonly used technique is Least Significant Bit steganography (LSB steganography). But instead of traditional LSB encoding, we will use a modified encoding technique which will first transform the video using a Lazy Lifting Wavelet transform and then apply LSB in the sub-bands of the video that has been obtained. The proposed approach to video steganography utilizes the visual as well as the audio component. The lazy wavelet transform is applied to the visual frames, and the data is stored in the coefficients of the visual component. The length up to which it is stored is hidden using LSB in the audio component. Experimental results show that the proposed technique does not affect the higher and lower ends of the frequency distribution of the signal. Moreover, it has a high payload capacity and low computational requirements.
This paper presents an improved data hiding technique based on BCH (n,k,t ) coding. The proposed embedder hides data into a block of input data by modifying some coefficients in the block in order to null the syndrome. The proposed embedder can hide data with less computational time and less storage capacity compared to the existing methods. The complexity of the proposed method is linear while that of other methods are exponential for any block size n. Thus, it is easy to extend this method to a large n. The BCH syndrome coding for steganography is now viable ascribed to the reduced complexity and its simplicity of the proposed embedder.
This paper proposes an adaptive watermarking scheme for e-government document images. The adaptive scheme combines the discrete cosine transform (DCT) and the singular value decomposition (SVD) using luminance masking. As a core of masking model in the human visual system (HVS), luminance masking is implemented to improve noise sensitivity. Genetic algorithm (GA), subsequently, is employed for the optimization of the scaling factor of the masking. Involving a number of steps, the scheme proposed through this study begins by calculating the mask of the host image using luminance masking. It is then continued by transforming the mask on each area into all frequencies domain. The watermark image, following this, is embedded by modifying the singular values of DCT-transformed host image with singular values of mask coefficient of host image and the control parameter of DCT-transformed watermark image using Genetic Algorithm (GA). The use of both the singular values and the control parameter respectively, in this case, is not only to improve the sensitivity of the watermark performance but also to avoid the false positive problem. The watermark image, afterwards, is extracted from the distorted images. The experiment results show the improved adaptive performance of the proposed scheme is in resistant to several types of attacks in comparison with the previous schemes; the adaptive performance refers to the adaptive parameter of the luminance masking functioned to improve the performance or robustness of an image from any attacks.
Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. This paper presents a novel technique for image steganography based on Huffman Encoding. Two 8 bit gray level image of size M X N and P X Q are used as cover image and secret image respectively. Huffman Encoding is performed over the secret image/message before embedding and each bit of Huffman code of secret image/message is embedded inside the cover image by altering the least significant bit (LSB) of each of the pixel's intensities of cover image. The size of the Huffman encoded bit stream and Huffman Table are also embedded inside the cover image, so that the Stego-Image becomes standalone information to the receiver. The experimental result shows that the algorithm has a high capacity and a good invisibility. Moreover Peak Signal to Noise Ratio (PSNR) of stego image with cover image shows better result in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing the decoding rules and Huffman table.
Based on the H.264/AVC Video coding standard, a new video steganography algorithm is proposed and realized in this paper. The algorithm designed a motion vector component feature to control embedding, and also to be the secret carrier. The information embedded will not significantly affect the video sequence's visual invisibility and statistical invisibility. Experiments show that the algorithm has a large embedding capacity with high carrier utilization, and can be implement fast and effectively.
A novel video steganography scheme based on motion vectors and linear block codes has been proposed in this paper. Our method embed secret messages in the motion vectors of cover media during the process of H.264 compressing. Linear block codes has been used to reducing the modification rate of the motion vectors. The proposed steganographic scheme is not only has lowly computational complexity, but also has highly imperceptible to human being. Furthermore, the secret information can be extracted directly without using the original video sequences. Experiments are designed to prove the feasibility of the proposed method. Experimental results show that our proposed scheme can embed large amounts of information and can maintain good video quality as well.
Data hiding is a type of information hiding technology. A data hiding method based on H.264 encoded video sequences is presented in this paper. The proposed method uses the parity of the coefficients after transformation and quantization to hide the desirable data. The digital data hidden by this approach can be recovered correctly by data recovering process and extracted directly from the encoded stream without using the original host video. Experimental results demonstrate that the proposed method can obtain good performance.
This paper presents a steganography method based on an embedded zerotree wavelet compression scheme and bit-plane complexity segmentation steganography. The proposed steganography enables us to use lossy compressed images as dummy files in bit-plane-based steganographic algorithms. Large embedding rates of around 25% of the compressed image size were achieved with little noticeable degradation in image quality.
Challenges face biometrics researchers and particularly those who are dealing with skin tone detection include choosing a colour space, generating the skin model and processing the obtained regions to fit applications. The majority of existing methods have in common the de-correlation of luminance from the considered colour channels. Luminance is underestimated since it is seen as the least contributing colour component to skin colour detection. This work questions this claim by showing that luminance can be useful in the segregation of skin and non-skin clusters. To this end, here we use a new colour space which contains error signals derived from differentiating the grayscale map and the non-red encoded grayscale version. The advantages of the approach are the reduction of space dimensionality from 3D, RGB, to 1D space advocating its unfussiness and the construction of a rapid classifier necessary for real time applications. The proposed method generates a 1D space map without prior knowledge of the host image. A comprehensive experimental test was conducted and initial results are presented. This paper also discusses an application of the method to image steganography where it is used to orient the embedding process since skin information is deemed to be psycho-visually redundant.
In this paper, a steganographic algorithm in MPEG compressed video stream was proposed. In each GOP, the control information for to facilitate data extraction was embedded in I frame, in P frames and B frames, the actually transmitted data were repeatedly embedded in motion vectors of macro-blocks that have larger moving speed, for to resist video processing. Data extraction was also performed in compressed video stream without requiring original video. On a GOP by GOP basis, control information in I frame should be extracted firstly, then the embedded data in P and B frames can be extracted based on the control information. Experimental results show that the proposed algorithm has the characteristics of little degrading the visual effect, larger embedding capacity and resisting video processing such as frame adding or frame dropping.
This paper proposes a novel Video Steganography which can hide an uncompressed secret video stream in a host video stream with almost the same size. Each frame of the secret video will be Non-uniform rectangular partitioned and the partitioned codes obtained can be an encrypted version of the original frame. These codes will be hidden in the Least 4 Significant Bits of each frames of the host video. Experimental results showed that this algorithm can hide a same-size video in the host video without obvious distortion in the host video.
This paper presents an improved data hiding technique based on BCH (n,k,t) syndrome coding. The proposed data hiding method embeds data to a block of input data (for example, image pixels, wavelet
or DCT coefficients, etc.) by modifying some coefficients in a block in order to null the syndrome of the BCH coding. The
proposed data hiding method can hide the same amount of data with less computational time compared to the existed methods.
Contributions of this paper include the reduction of both time complexity and storage complexity as well. Storage complexity
is linear while that of other methods are exponential. Time complexity of our method is almost negligible and constant for
any n. On the other hand, time complexity of the existing methods is exponential. Since the time complexity is constant and storage
complexity is linear, it is easy to extend this method to a large n which allows us to hide data with small embedding capacity. Note that small capacities are highly recommended for steganography
to survive steganalysis. The proposed scheme shows that BCH syndrome coding for data hiding is now practical ascribed to the
reduced complexity.
This article reports that digital multimedia is exposed to a broad spectrum of security problems. From the standpoint of the media provider, protection of materials from unauthorized distribution or modification is a primary concern. At the delivery end, recipients want to ensure that downloads are virus-free and legitimately obtained. Ironically, encryption and digital branding tools can be employed both for securing multimedia as well as for circumventing laws pertaining to content and use. The most popular of these techniques are steganography and watermarking or the addition of an unremovable identifier to tag the content, indicating ownership. One popular method used for data encoding in digital audio files is Least Significant Bit, where the low bit of each sound sample is successively replaced by digits from a binary string. Another is phase coding, where the phase of an audio signal is replaced by a reference phase used to modulate a data signal. Echoes can even be altered in order to conceal information. All these techniques rely on the fact that the perception of sound is rather inaccurate.
A new data hiding scheme for scene change detection in H.264 streams is presented. The proposed scheme takes advantage of the different block sizes used by the H.264 encoder during the inter prediction stage in order to hide the scene change information inside the encoded sequence. This information enables real time scene change detection directly from the H.264 stream.
The recent finalization of MPEG-4 will make this standard very attractive for a large range of applications such as video editing, Internet video distribution, wireless video communications. Some of these applications are likely to get great benefit from watermarking technology, since it can enable a number of innovative services, such as conditional access policies, data annotation, data labeling, content authentication, to be implemented at a low price. One of the key points of the MPEG-4 standard is the possibility to access and manipulate objects within a video sequence. Thus object watermarking has to be achieved in such a way that, while a video object is transferred from a sequence to another, it is still possible to correctly access the data embedded within the object itself. The algorithm proposed in this paper embeds a watermark in each video object by imposing a particular relationship between some predefined pairs of quantized discrete cosine transform (DCT) coefficients in the luminance blocks of pseudo-randomly selected macroblocks (MBs). Watermarks are equally embedded into intra and inter MBs. Experimental results are presented validating the effectiveness of the proposed approach.
One of challenges encountered in information bit hiding is the reliability of information bit detection. This paper addresses the issue and presents an algorithm in the discrete cosing transform (DCT) domain with a communication theory approach. It embeds information bits (first) in the DC and (then in the) low-frequency AC coefficients. To extract the hidden information bits from a possibly corrupted marked image with a low error probability, we model information hiding as a digital communication problem and apply Bose??Chaudhuri??Hocquenghen channel coding with soft-decision decoding based on matched filtering. The robustness of the hidden bits has been tested with StirMark. The experimental results demonstrate that the embedded information bits are perceptually transparent and can successfully resist common signal processing procedures, jitter attack, aspect ratio variation, scaling change, small angle rotation, small amount cropping, and JPEG compression with quality factor as low as 10. Compared with some information hiding algorithms reported in the literature, it appears that the hidden information bits with the proposed approach are relatively more robust. While the approach is presented for gray level images, it can also be applied to color images and video sequences.
A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image
- K Muhammad
- M Sajjad
- I Mehmood
- S Rho
- S Baik