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

Digital watermark technology in security applications

With the rising emphasis on security and the number of fraud related crimes around the world, authorities are looking for new technologies to tighten security of identity. Among many modern electronic technologies, digital watermarking has unique advantages to enhance the document authenticity. At the current status of the development, digital watermarking technologies are not as matured as other competing technologies to support identity authentication systems. This work presents improvements in performance of two classes of digital watermarking techniques and investigates the issue of watermark synchronisation. Optimal performance can be obtained if the spreading sequences are designed to be orthogonal to the cover vector. In this thesis, two classes of orthogonalisation methods that generate binary sequences quasi-orthogonal to the cover vector are presented. One method, namely "Sorting and Cancelling" generates sequences that have a high level of orthogonality to the cover vector. The Hadamard Matrix based orthogonalisation method, namely "Hadamard Matrix Search" is able to realise overlapped embedding, thus the watermarking capacity and image fidelity can be improved compared to using short watermark sequences. The results are compared with traditional pseudo-randomly generated binary sequences. The advantages of both classes of orthogonalisation inethods are significant. Another watermarking method that is introduced in the thesis is based on writing-on-dirty-paper theory. The method is presented with biorthogonal codes that have the best robustness. The advantage and trade-offs of using biorthogonal codes with this watermark coding methods are analysed comprehensively. The comparisons between orthogonal and non-orthogonal codes that are used in this watermarking method are also made. It is found that fidelity and robustness are contradictory and it is not possible to optimise them simultaneously. Comparisons are also made between all proposed methods. The comparisons are focused on three major performance criteria, fidelity, capacity and robustness. aom two different viewpoints, conclusions are not the same. For fidelity-centric viewpoint, the dirty-paper coding methods using biorthogonal codes has very strong advantage to preserve image fidelity and the advantage of capacity performance is also significant. However, from the power ratio point of view, the orthogonalisation methods demonstrate significant advantage on capacity and robustness. The conclusions are contradictory but together, they summarise the performance generated by different design considerations. The synchronisation of watermark is firstly provided by high contrast frames around the watermarked image. The edge detection filters are used to detect the high contrast borders of the captured image. By scanning the pixels from the border to the centre, the locations of detected edges are stored. The optimal linear regression algorithm is used to estimate the watermarked image frames. Estimation of the regression function provides rotation angle as the slope of the rotated frames. The scaling is corrected by re-sampling the upright image to the original size. A theoretically studied method that is able to synchronise captured image to sub-pixel level accuracy is also presented. By using invariant transforms and the "symmetric phase only matched filter" the captured image can be corrected accurately to original geometric size. The method uses repeating watermarks to form an array in the spatial domain of the watermarked image and the the array that the locations of its elements can reveal information of rotation, translation and scaling with two filtering processes

Visual cryptography scheme with digital watermarking in sharing secret information from car number plate digital images

In this paper a visual cryptography scheme with a binary additive stream cipher is used to form the meaningless shares (share images or multiple layers) of original digital image, hiding some secret information. Each share image holds some information, but at the receiver side only when all of them are superimposed, the secret information is revealed by human vision without any complex computation. Proposed algorithm for generating shares is applied in MATLAB programming environment, using MATLAB built-in functions to create sequences of pseudorandom numbers or streams, which are used to make share images of original digital image. The input image is first converted into a binary image, shares are generated using pixel expansion scheme, and after that are sent to the receiver. At the received side, the shares could be printed in separate transparent sheets and overlapped in order to reveal the secret image, with some loss in contrast when compared to the original image. An algorithm is applied to car number plate digital images with watermark. Digital image watermarking method is used to embed some data in a car number plate digital image in order to verify the credibility of the content or the identity of the owner

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

Visual Discovery in Multivariate Binary Data

This paper presents the concept of Monotone Boolean Function Visual Analytics (MBFVA) and its application to the medical domain. The medical application is concerned with discovering breast cancer diagnostic rules (i) interactively with a radiologist, (ii) analytically with data mining algorithms, and (iii) visually. The coordinated visualization of these rules opens an opportunity to coordinate the rules, and to come up with rules that are meaningful for the expert in the field, and are confirmed with the database. This paper shows how to represent and visualize binary multivariate data in 2-D and 3-D. This representation preserves the structural relations that exist in multivariate data. It creates a new opportunity to guide the visual discovery of unknown patterns in the data. In particular, the structural representation allows us to convert a complex border between the patterns in multidimensional space into visual 2-D and 3-D forms. This decreases the information overload on the user. The visualization shows not only the border between classes, but also shows a location of the case of interest relative to the border between the patterns. A user does not need to see the thousands of previous cases that have been used to build a border between the patterns. If the abnormal case is deeply inside in the abnormal area, far away from the border between normal and abnormal patterns, then this shows that this case is very abnormal and needs immediate attention. The paper concludes with the outline of the scaling of the algorithm for the large data sets

High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity. The suggested technique of image steganography is achieved using both spatial and cepstral domains, where the Mel-frequency cepstral coefficients (MFCCs) are adopted, as very efficient features of the speech signal. The presented technique in this paper contributes to improving the image steganography features through two approaches. First is to support the hiding capacity by the usage of the extracted MFCCs features and pitches extracted from the speech signal and embed them inside the cover color image rather than directly hiding the whole samples of the digitized speech signal. Second is to improve the data security by hiding the secret data (MFCCs features) anywhere in the host image rather than directly using the least significant bits substitution of the cover image. At the recovering side, the proposed approach recovers these hidden features and using them to reconstruct the speech waveform again by inverting the steps of MFCCs extraction to recover an approximated vocal tract response and combine it with recovered pitch based excitation signal. The results show a peak signal to noise ratio of 52.4 dB of the stego-image, which reflect a very good quality and a reduction ratio of embedded data to about (6%–25%). In addition, the results show a speech reconstruction degree of about 94.24% correlation with the original speech signal