Ramadhan J. Mstafa

A video steganography algorithm based on Kanade-Lucas-Tomasi tracking algorithm and error correcting codes

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.

A highly secure video steganography using Hamming code (7, 4)

Due to the high speed of internet and advances in technology, 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 systems 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 schemes robustness. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that we have obtained. Regarding the systems 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 videos quality.

A novel video steganography algorithm in the wavelet domain based on the KLT tracking algorithm and BCH codes

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.

A high payload video steganography algorithm in DWT domain based on BCH codes (15, 11)

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.

A New Video Steganography Algorithm Based on the Multiple Object Tracking and Hamming Codes

In the modern world, video steganography has become a popular option for 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 new video steganography algorithm based on the multiple object tracking algorithm and Hamming codes. The proposed algorithm includes four different stages. First, the secret message is preprocessed, and Hamming codes (n, k) are applied in order to produce an encoded message. Second, a motion-based multiple object tracking algorithm is applied on cover videos in order to identify the regions of interest of the moving objects. Third, the process of embedding 3 and 6 bits of the encoded message into the 1 LSB and 2 LSBs of RGB pixel components is performed for all motion regions in the video using the foreground mask. Fourth, the process of extracting the secret message from the 1 LSB and 2 LSBs for each RGB component of all moving regions is accomplished. Experimental results of the proposed video steganography algorithm have demonstrated a high embedding efficiency and a high embedding payload.

Compressed and raw video steganography techniques: a comprehensive survey and analysis

In the last two decades, the science of covertly concealing and communicating data has acquired tremendous significance due to the technological advancement in communication and digital content. Steganography is the art of concealing secret data in a particular interactive media transporter, e.g., text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques have become important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of the noteworthy development of advanced video over the Internet. The performance of any steganographic method ultimately relies on the imperceptibility, hiding capacity, and robustness. In the past decade, many video steganography methods have been proposed; however, the literature lacks of sufficient survey articles that discuss all techniques. This paper presents a comprehensive study and analysis of numerous cutting edge video steganography methods and their performance evaluations from literature. Both compressed and raw video steganography methods are surveyed. In the compressed domain, video steganography techniques are categorized according to the video compression stages as venues for data hiding such as intra frame prediction, inter frame prediction, motion vectors, transformed and quantized coefficients, and entropy coding. On the other hand, raw video steganography methods are classified into spatial and transform domains. This survey suggests current research directions and recommendations to improve on existing video steganography techniques.

A Robust and Secure Video Steganography Method in DWT-DCT Domains Based on Multiple Object Tracking and ECC

Over the past few decades, the art of secretly embedding and communicating digital data has gained enormous attention because of the technological development in both digital contents and communication. The imperceptibility, hiding capacity, and robustness against attacks are three main requirements that any video steganography method should take into consideration. In this paper, a robust and secure video steganographic algorithm in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains based on the multiple object tracking (MOT) algorithm and error correcting codes is proposed. The secret message is preprocessed by applying both Hamming and Bose, Chaudhuri, and Hocquenghem codes for encoding the secret data. First, motion-based MOT algorithm is implemented on host videos to distinguish the regions of interest in the moving objects. Then, the data hiding process is performed by concealing the secret message into the DWT and DCT coefficients of all motion regions in the video depending on foreground masks. Our experimental results illustrate that the suggested algorithm not only improves the embedding capacity and imperceptibility but also enhances its security and robustness by encoding the secret message and withstanding against various attacks.

A DCT-based robust video steganographic method using BCH error correcting codes

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.

A novel video steganography algorithm in DCT domain based on hamming and BCH codes

In the past decade, the science of information hiding has gained tremendous significance due to advances in information and communication technology. 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 novel video steganography method in DCT domain based on Hamming and 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 experiential results of the proposed algorithm are compared with three existing methods. The comparison results show that our proposed algorithm outperformed other algorithms. The hidden ratio of the proposed algorithm is approximately 27.53%, which is considered as a high hiding capacity with a minimal tradeoff of the visual quality. The robustness of the proposed algorithm was tested under different attacks.

Video steganography techniques: Taxonomy, challenges, and future directions

Nowadays, video steganography has become important in many security applications. The performance of any steganographic method ultimately relies on the imperceptibility, hiding capacity, and robustness. In the past decade, many video steganography methods have been proposed; however, the literature lacks of sufficient survey articles that discuss all techniques. This paper presents a comprehensive study and analysis of numerous cutting edge video steganography methods and their performance evaluations from literature. Both compressed and raw video steganographic methods are surveyed. In the compressed domain, video steganographic techniques are categorized according to the video compression stages as venues for data hiding such as intra frame prediction, inter frame prediction, motion vectors, transformed and quantized coefficients, and entropy coding. 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.