36 research outputs found
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
Efficient and Robust Video Steganography Algorithms for Secure Data Communication
Over the last two decades, the science of secretly embedding and communicating data has gained 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 such as text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques are important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of noteworthy developments in advanced video over the Internet. The performance of any steganography method, ultimately, relies on the imperceptibility, hiding capacity, and robustness against attacks. Although many video steganography methods exist, several of them lack the preprocessing stages. In addition, less security, low embedding capacity, less imperceptibility, and less robustness against attacks are other issues that affect these algorithms. This dissertation investigates and analyzes cutting edge video steganography techniques in both compressed and raw domains. Moreover, it provides solutions for the aforementioned problems by proposing new and effective methods for digital video steganography. The key objectives of this research are to develop: 1) a highly secure video steganography algorithm based on error correcting codes (ECC); 2) an increased payload video steganography algorithm in the discrete wavelet domain based on ECC; 3) a novel video steganography algorithm based on Kanade-Lucas-Tomasi (KLT) tracking and ECC; 4) a robust video steganography algorithm in the wavelet domain based on KLT tracking and ECC; 5) a new video steganography algorithm based on the multiple object tracking (MOT) and ECC; and 6) a robust and secure video steganography algorithm in the discrete wavelet and discrete cosine transformations based on MOT and ECC. The experimental results from our research demonstrate that our proposed algorithms achieve higher embedding capacity as well as better imperceptibility of stego videos. Furthermore, the preprocessing stages increase the security and robustness of the proposed algorithms against attacks when compared to state-of-the-art steganographic methods
Building a Statistical Model to Detect Foreground Objects and using it in Video Steganography
أصبح إخفاء المعلومات بالفيديو خيارًا شائعًا لحماية البيانات السرية من محاولات القرصنة والهجمات الشائعة على الإنترنت. ومع ذلك ، عند استخدام إطار (إطارات) الفيديو بالكامل لتضمين بيانات سرية قد تؤدي إلى تشويه بصري. هذا العمل هو محاولة لإخفاء صورة سرية حساسة داخل الأجسام المتحركة في مقطع فيديو بناءً على فصل الكائن عن خلفية الإطار واختيارها وترتيبها حسب حجم الكائن لتضمين الصورة السرية. يتم استخدام تقنية XOR مع البتات العكسية بين بتات الصورة السرية وبتات الكائن المتحرك المكتشفة للتضمين. توفر الطريقة المقترحة مزيدًا من الأمان وعدم الإدراك حيث يتم استخدام الكائنات المتحركة للتضمين ، لذلك من الصعب ملاحظة التغييرات في الكائنات المتحركة بدلاً من استخدام منطقة الخلفية للتضمين في الفيديو. أظهرت النتائج التجريبية جودة بصرية أفضل لفيديو stego مع قيم PSNR تتجاوز 58 ديسيبل ، وهذا يشير إلى أن الطريقة المقترحة تعمل دون التسبب في تشويه كبير في الفيديو الأصلي والرسالة السرية المرسلة.Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the changes in the moving objects instead of using background area for embedding in the video. The experimental results showed the better visual quality of the stego video with PSNR values exceeding 58 dB, this indicates that the proposed method works without causing much distortion in the original video and transmitted secret message
Video Steganography Technique Based on Enhanced Moving Objects Detection Method
مقدمة:
أصبح إخفاء المعلومات عن طريق الفيديو خيارًا شائعًا لحماية البيانات السرية من محاولات القرصنة والهجمات الشائعة على الإنترنت. ومع ذلك ، عند استخدام إطار (إطارات) الفيديو بالكامل لتضمين بيانات سرية ، فقد يؤدي ذلك إلى تشويه بصري.
طرق العمل:
هذا العمل هو محاولة لإخفاء صورة سرية حساسة داخل الأجسام المتحركة في مقطع فيديو بناءً على فصل الكائن عن خلفية الإطار واختيارها وترتيبها حسب حجم الكائن لتضمين الصورة السرية. يتم استخدام تقنية XOR مع البتات العكسية بين بتات الصورة السرية وبتات الكائن المتحرك المكتشفة للتضمين. توفر الطريقة المقترحة مزيدًا من الأمان وعدم الإدراك حيث يتم استخدام الكائنات المتحركة للتضمين ، لذلك من الصعب ملاحظة التغييرات في الكائنات المتحركة بدلاً من استخدام منطقة الخلفية للتضمين في الفيديو. تم إجراء مزيد من التطوير للطريقة المقترحة في مجال إخفاء المعلومات بالفيديو من خلال تطبيق النموذج المكاني مع النموذج الإحصائي. تم أيضًا تطبيق أنماط LSB الإضافية لتقييم قدرة النهج المقترح في اكتشاف الأجسام المتحركة. بالإضافة إلى تقييم متانة الطريقة المقترحة ضد الهجمات المختلفة مثل ضوضاء الملح والفلفل والتصفية المتوسطة.
الاستنتاجات:
أظهرت النتائج التجريبية جودة بصرية أفضل لفيديو stego مع قيم PSNR تتجاوز 70 ديسيبل ، وهذا يشير إلى أن الطريقة المقترحة تعمل دون إحداث تشويه كبير في الفيديو الأصلي والرسالة السرية المرسلة.Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion.
Materials and Methods:
This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The proposed approach reverses the secret image bits and uses XOR technique between the reversed bits and the detected moving object bits for embedding. The proposed approach provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the changes in the moving objects instead of using background area for embedding in the video. Further development to the proposed approach in the area of video steganography has been done by applying spatial model in combination with statistical model. Additional LSB styles have been also applied to evaluate the ability of the proposed approach in detecting moving objects. In addition to evaluating the robustness of the proposed approach against different attacks such as salt and pepper noise and median filtering.
Results:
The experimental results showed the better visual quality of the stego video with PSNR values exceeding 70 dB, this indicates that the proposed method works without causing much distortion in the original video and transmitted secret message.
Conclusion:
The experimental proof of the proposed approach can successfully detect and embed secret image. Also, it provides more security and imperceptibility as the data was hidden in the moving objects and the updates in the moving objects are difficult to notice rather than the static region in a vide
Video steganography based on DCT psychovisual and object motion
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
Haar Transformation for Compressed Speech Hiding
علم الكتابة المغطاة هو واحد من أكثر العلوم شيوعا في مجال امنية المعلوم. في هذا البحث ، سيتم تعديل خوارزمية لتضمين صوتك مكبوس داخل صورة رمادية باستخدام تحويل المويجات المتقطعة (Haar) . في البداية تم كبس بيانات الصوت الى نصف حجمها الأصلي ومن ثم تحويل البيانات المكبوسة من الترميز العشري إلى الترميز الثنائي وتضمينه داخل معاملات الحزم الاتجاهية الاربعة (cA :Low Low ,cH :High Low ,cV:Low High,cD:High High) الناتجة من تحليل صورة الغطاء Cover_Image باستخدام تحويل المويجة المتقطع Haar حيث ان cA تمثل حزمة الترددات الواطئة و cH ,cV ,cD تمثل حزم الترددات العالية .
تم اختبار كفاءة الخوارزمية بقياس معاملات كفاءة الاخفاء (MSE,PSNR,SNR,Correlation) واظهرت النتائج صعوبة اكتشاف المراقب لصورة الغطاء الحاوية على البيانات السرية المطمورة.
تظهر نتائج هذا البحث أنه يمكننا بنجاح إخفاء بيانات الكلام (الصوت) في صورة رمادية ثم استخراجها مع معدل سعة خزن (1) خلية ثنائية (bit) لكل نقطة ضوئية اي ان سعة الخزن باستخدام الطريقة المقدمة يعتمد على حجم صورة الغطاء وكذلك تبين انه معاملات الترددات العالية تكون افضل للاخفاء من حيث عدم ادراك المتطفلين بانه يوجد بيانات سرية داخل الوسط الحامل لها stego_imag. Steganography science is one of the most popular field in security direction. In this paper an algorithm will be adopted to embed a compressed speech inside a gray image using discrete wavelet (Haar transformation). In the beginning the speech was compressed up to its half original size by applying (Daubechies) then convert the speech data from decimal code to binary code and embed it inside Haar coefficients of the cover _image using the Four sub bands (cA : Low Low,cH: High Low,cV:Low High,cD: High High) which got by applying the wavelet on the cover_ image. Measuring Peak Signal to Noise Ratio (PSNR) to determine the accuracy of the stego_image with respect to the original image, MSE and the correlation factors were checked show that the proposed algorithm has positive effect in field of speech hiding.The proposed technique in this research turned out to be able to hide speech data (audio) in the cover image and then extract the hidden data with storage rate (1) bits per pixel. Hiding capacity can be achieved using this method proportionally depends on cover_image size. High frequency coefficients have also been shown to be better for data hiding in terms of perceptibility and intruders' cannot be able to recognize the cover medium (stego_image) which included secret data
Image Steganography: A Review of the Recent Advances
Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography, has received increased attention recently. The main goal of this paper is to explore and discuss various deep learning methods available in image steganography field. Deep learning techniques used for image steganography can be broadly divided into three categories - traditional methods, Convolutional Neural Network-based and General Adversarial Network-based methods. Along with the methodology, an elaborate summary on the datasets used, experimental set-ups considered and the evaluation metrics commonly used are described in this paper. A table summarizing all the details are also provided for easy reference. This paper aims to help the fellow researchers by compiling the current trends, challenges and some future direction in this field
Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes
Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity.
In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis.
As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods.
The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms.
Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4.
In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications.
Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh.
By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms.
Chapter 9 concludes this thesis and also suggests some potential directions for future work
Robust digital image watermarking algorithms for copyright protection
Digital watermarking has been proposed as a solution to the problem of resolving copyright ownership of multimedia data (image, audio, video). The work presented in this thesis is concerned with the design of robust digital image watermarking algorithms for copyright protection.
Firstly, an overview of the watermarking system, applications of watermarks as well as the survey of current watermarking algorithms and attacks, are given. Further, the implementation of feature point detectors in the field of watermarking is introduced. A new class of scale invariant feature point detectors is investigated and it is showed that they have excellent performances required for watermarking.
The robustness of the watermark on geometrical distortions is very important issue in watermarking. In order to detect the parameters of undergone affine transformation, we propose an image registration technique which is based on use of the scale invariant feature point detector. Another proposed technique for watermark synchronization is also based on use of scale invariant feature point detector. This technique does not use the original image to determine the parameters of affine transformation which include rotation and scaling. It is experimentally confirmed that this technique gives excellent results under tested geometrical distortions.
In the thesis, two different watermarking algorithms are proposed in the wavelet domain. The first algorithm belongs to the class of additive watermarking algorithms which requires the presence of original image for watermark detection. Using this algorithm the influence of different error correction codes on the watermark robustness is investigated. The second algorithm does not require the original image for watermark detection. The robustness of this algorithm is tested on various filtering and compression attacks. This algorithm is successfully combined with the aforementioned synchronization technique in order to achieve the robustness on geometrical attacks.
The last watermarking algorithm presented in the thesis is developed in complex wavelet domain. The complex wavelet transform is described and its advantages over the conventional discrete wavelet transform are highlighted. The robustness of the proposed algorithm was tested on different class of attacks. Finally, in the thesis the conclusion is given and the main future research directions are suggested