scholarly journals Video steganography based on DCT psychovisual and object motion

2020 ◽  
Vol 9 (3) ◽  
pp. 1015-1023 ◽  
Author(s):  
Muhammad Fuad ◽  
Ferda Ernawan
Keyword(s):  
Video Quality ◽  
Object Motion ◽  
Multimedia Data ◽  
Secret Message ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Limited Bandwidth ◽  
Video Frames ◽  
Dct Coefficients ◽  
Video Reconstruction

Steganography is a technique of concealing the message in multimedia data. Multimedia data, such as videos are often compressed to reduce the storage for limited bandwidth. The video provides additional hidden-space in the object motion of image sequences. This research proposes a video steganography scheme based on object motion and DCT-psychovisual for concealing the message. The proposed hiding technique embeds a secret message along the object motion of the video frames. Motion analysis is used to determine the embedding regions. The proposed scheme selects six DCT coefficients in the middle frequency using DCT-psychovisual effects of hiding messages. A message is embedded by modifying middle DCT coefficients using the proposed algorithm. The middle frequencies have a large hiding capacity and it relatively does not give significant effect to the video reconstruction. The performance of the proposed video steganography is evaluated in terms of video quality and robustness against MPEG compression. The experimental results produce minimum distortion of the video quality. Our scheme produces a robust of hiding messages against MPEG-4 compression with average NC value of 0.94. The proposed video steganography achieves less perceptual distortion to human eyes and it's resistant against reducing video storage.

scholarly journals An ECC/DCT-Based Robust Video Steganography Algorithm for Secure Data Communication

2017 ◽  
Author(s):  
Ramadhan J. Mstafa ◽  
Khaled M. Elleithy
Keyword(s):  
Moving Objects ◽  
Data Communication ◽  
Error Correcting Codes ◽  
Secret Message ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Embedding Efficiency ◽  
Video Frames ◽  
Comparison Results ◽  
Dct Coefficients

Nowadays, 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 discrete cosine transform (DCT) domain based on error correcting codes (ECC). To improve the security of the proposed algorithm, a secret message is first encrypted and encoded by using Hamming and BCH codes. Then, it is embedded into the 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.  

scholarly journals A Secure Video Steganography Based on the Intra-Prediction Mode (IPM) for H264

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5242
Author(s):  
Mingyuan Cao ◽  
Lihua Tian ◽  
Chen Li
Keyword(s):  
Video Quality ◽  
Relevant Information ◽  
Intra Prediction ◽  
Video Encoding ◽  
Secret Message ◽  
Adaptive Steganography ◽  
Video Steganography ◽  
Mapping Rules ◽  
Distortion Functions ◽  
Prediction Mode

Recently, many video steganography algorithms based on the intra-prediction mode (IPM) have been adaptive steganography algorithms. These algorithms usually focus on the research about mapping rules and distortion functions while ignoring the fact that adaptive steganography may not be suitable for video steganography based on the intra-prediction mode; this is because the adaptive steganography algorithm must first calculate the loss of all cover before the first secret message is embedded. However, the modification of an IPM may change the pixel values of the current block and adjacent blocks, which will lead to the change of the loss of the following blocks. In order to avoid this problem, a new secure video steganography based on a novel embedding strategy is proposed in this paper. Video steganography is combined with video encoding. Firstly, the frame is encoded by an original encoder and all the relevant information is saved. The candidate block is found according to the relevant information and mapping rules. Then every qualified block is analyzed, and a one-bit message is embedded during intra-prediction encoding. At last, if the IPM of this block is changed, the values of the residual are modified in order to keep the optimality of the modified IPM. Experimental results indicate that our algorithm has good security performance and little impact on video quality.

A Secure Video Steganography Based on ECC and DCT

2012 ◽  
Vol 433-440 ◽  
pp. 5378-5383 ◽  
Author(s):  
Li Xian Wei ◽  
Peng Yang ◽  
Xiao Yuan Yang
Keyword(s):  
Error Correcting Code ◽  
High Capacity ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Secret Information ◽  
Dct Coefficients

Video steganographic algorithm has the advantage of large hiding capacity, but we neglect the security when seek the capacity. In order to balance the two aspects, both to meet the high capacity of improving the load of video carrier and can safely protect the secret information. This paper presents the error-correcting code which can effectively correct burst errors and use it in video steganography. The secret information is hidden in error-correcting code first and then integrated the code with secret information with the video carrier’s DCT coefficients to insert the secret information in video carrier. The experiment results show that: this algorithm not only has great visual and statistical invisibility, also the safety of secret information is more significant. And achieve the objective of effective protect the secret information.

scholarly journals Video steganography using 3D distance calculator based on YCbCr color components

2021 ◽  
Vol 24 (2) ◽  
pp. 831
Author(s):  
Esraa Jaffar Baker ◽  
Adil Abbas Majeed ◽  
Sundos Abdulameer Alazawi ◽  
Shahreen Kasim ◽  
Rohayanti Hassan ◽  
...  
Keyword(s):  
Hash Function ◽  
Mean Squared Error ◽  
Video Quality ◽  
Structural Similarity ◽  
Hidden Information ◽  
Video Steganography ◽  
Multimedia Contents ◽  
Squared Error ◽  
Video Frames ◽  
Hide Information

Steganography techniques have taken a major role in the development in the field of transferring multimedia contents and communications. Therefore, field of steganography become interested as the need for security increased significantly. Steganography is a technique to hide information within cover media so that this media does not change significantly. Steganography process in a video is to hide the information from the intruder and prevent him access to that hidden information. This paper presents the algorithm of steganography in the video frames. The proposed algorithm selected the best frames to hide the message in video using 3D distance equation to increasing difficulty onto the intruder to detect and guess the location of the message in the video frames. As well as selected the best frames in this algorithm increased the difficulty and give us the best stego-video quality using structural similarity (SSIM). Also, the hash function was used to generate random positions to hide the message in the lines of video frames. The proposed algorithm evaluated with mean squared error (MSE), peak signalto-noise ratio (PSNR) and SSIM measurement. The results were acceptable and shows that is the difficulty of distinguishing the hidden message in stego-video with the human eye.

A DCT-Domain System for Digital Watermarking

2013 ◽  
Vol 321-324 ◽  
pp. 2609-2612
Author(s):  
Yan Liang ◽  
Gao Yan ◽  
Chun Xia Qi
Keyword(s):  
Signal Processing ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Random Sequence ◽  
Multimedia Data ◽  
Dct Domain ◽  
Digital Document ◽  
Dct Coefficients ◽  
Processing Techniques ◽  
Signal Processing Techniques

Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data in a networked environment. It makes possible to tightly associated to a digital document a code allowing the identification of the data creator, owner, authorized consumer, and so on. In this paper a new DCT-domain system for digital watermarking algorithm for digital images is presented: the method, which operates in the frequency domain, embeds a pseudo-random sequence of scrambled image in a selected set of DCT coefficients. After embedding, the watermark is adapted to the image by exploiting the masking characteristics of the human visual system, thus ensuring the watermark invisibility. By exploiting the statistical properties of the embedded sequence, the mark can be reliably extracted without resorting to the original uncorrupted image. Experimental results demonstrate that the watermark is robust to several signal processing techniques, including JPEG compression, cut, fuzzy, addition of noise, and sharpen.

Feature extraction-based image steganalysis using deep learning

2021 ◽  
pp. 188-198
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Secure Communication ◽  
Information Technologies ◽  
Network Models ◽  
Error Rates ◽  
Multimedia Data ◽  
Secret Message ◽  
Neural Network Models

The innovations in advanced information technologies has led to rapid delivery and sharing of multimedia data like images and videos. The digital steganography offers ability to secure communication and imperative for internet. The image steganography is essential to preserve confidential information of security applications. The secret image is embedded within pixels. The embedding of secret message is done by applied with S-UNIWARD and WOW steganography. Hidden messages are reveled using steganalysis. The exploration of research interests focused on conventional fields and recent technological fields of steganalysis. This paper devises Convolutional neural network models for steganalysis. Convolutional neural network (CNN) is one of the most frequently used deep learning techniques. The Convolutional neural network is used to extract spatio-temporal information or features and classification. We have compared steganalysis outcome with AlexNet and SRNeT with same dataset. The stegnalytic error rates are compared with different payloads.

Secret Communication Techniques

2019 ◽  
pp. 1-19
Keyword(s):  
Digital Media ◽  
Quality Parameters ◽  
Image Steganography ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Communication Techniques ◽  
Secret Communication ◽  
Text Steganography ◽  
Distortion Measure

This chapter introduces the reader to cryptography, steganography, watermarking, and quality parameters of image steganography techniques. Cryptography is a technique for secret communication. Steganography is a technique for secret and unnoticeable communication. The watermarking techniques hide watermarks inside the digital media. There are four types of steganography techniques: (1) image steganography, (2) audio steganography, (3) video steganography, and (4) text steganography. The quality of image steganographic algorithms can be measured by three parameters like (1) hiding capacity, (2) distortion measure, and (3) security check.

Adaptive Retransmission Scheme for Video Streaming Applications

2010 ◽  
pp. 248-262
Author(s):  
Árpád Huszák
Keyword(s):  
Video Streaming ◽  
Mobile Networks ◽  
Video Quality ◽  
Multimedia Applications ◽  
Limited Bandwidth ◽  
Streaming Applications ◽  
Congestion Control Algorithm ◽  
Negative Effect ◽  
Audio Video

In this chapter we present a novel selective retransmission scheme, based on congestion control algorithm. Our method is efficient in narrowband networks for multimedia applications, which demand higher bandwidth. Multimedia applications are becoming increasingly popular in IP networks, while in mobile networks the limited bandwidth and the higher error rate arise in spite of its popularity. These are restraining factors for mobile clients using multimedia applications such as video streaming. In some conditions the retransmission of lost and corrupted packets should increase the quality of the multimedia service, but these retransmissions should be enabled only if the network is not in congested state. Otherwise the retransmitted packet will intensify the congestion and it will have negative effect on the audio/video quality. Our proposed mechanism selectively retransmits the corrupted packets based on the actual video bit rate and the TCP-Friendly Rate Control (TFRC), which is integrated to the preferred DCCP transport protocol.

Making Image Retrieval and Classification More Accurate Using Time Series and Learned Constraints

2011 ◽  
pp. 145-170 ◽  
Author(s):  
Chotirat “Ann” Ratanamahatana ◽  
Eamonn Keogh ◽  
Vit Niennattrakul
Keyword(s):  
Time Series ◽  
Image Retrieval ◽  
Data Storage ◽  
Distance Measure ◽  
Series Representation ◽  
Feedback System ◽  
Multimedia Data ◽  
Video Frames ◽  
Computationally Intensive ◽  
Dynamic Time

After the generation of multimedia data turning digital, an explosion of interest in their data storage, retrieval, and processing, has drastically increased in the database and data mining community. This includes videos, images, and handwriting, where we now have higher expectations in exploiting these data at hand. We argue however, that much of this work’s narrow focus on efficiency and scalability has come at the cost of usability and effectiveness. Typical manipulations are in some forms of video/image processing, which require fairly large amounts for storage and are computationally intensive. In this work, we will demonstrate how these multimedia data can be reduced to a more compact form, that is, time series representation, while preserving the features of interest, and can then be efficiently exploited in Content-Based Image Retrieval. We also introduce a general framework that learns a distance measure with arbitrary constraints on the warping path of the Dynamic Time Warping calculation. We demonstrate utilities of our approach on both classification and query retrieval tasks for time series and other types of multimedia data including images, video frames, and handwriting archives. In addition, we show that incorporating this framework into the relevance feedback system, a query refinement can be used to further improve the precision/recall by a wide margin.

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