176 research outputs found

    An improved security and message capacity using AES and Huffman coding on image steganography

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    Information security is very important and has been widely implemented. Cryptography and steganography are two common methods that can be implemented to secure and conceal the information. In this research, the proposed AES algorithm for cryptography and DWT for steganography. However, in case of implementing DWT as steganography, there is a weakness which is a lower capacity. Based on DWT’s problem, proposed Huffman Coding to reduce the total of the message’s bit and increase the capacity. In the implementation, a message will be processed by using AES and compressed by using Huffman Coding then conceal in a cover using DWT. After doing several experiments using a 128x128 pixel message image and a 512x512 pixel of the cover image, achieved the average of MSE is 1.5676 and the average of PSNR result is above 40db which is 46.1878

    Methods of covert communication of speech signals based on a bio-inspired principle

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    This work presents two speech hiding methods based on a bio-inspired concept known as the ability of adaptation of speech signals. A cryptographic model uses the adaptation to transform a secret message to a non-sensitive target speech signal, and then, the scrambled speech signal is an intelligible signal. The residual intelligibility is extremely low and it is appropriate to transmit secure speech signals. On the other hand, in a steganographic model, the adapted speech signal is hidden into a host signal by using indirect substitution or direct substitution. In the first case, the scheme is known as Efficient Wavelet Masking (EWM), and in the second case, it is known as improved-EWM (iEWM). While EWM demonstrated to be highly statistical transparent, the second one, iEWM, demonstrated to be highly robust against signal manipulations. Finally, with the purpose to transmit secure speech signals in real-time operation, a hardware-based scheme is proposedEsta tesis presenta dos métodos de comunicación encubierta de señales de voz utilizando un concepto bio-inspirado, conocido como la “habilidad de adaptación de señales de voz”. El modelo de criptografía utiliza la adaptación para transformar un mensaje secreto a una señal de voz no confidencial, obteniendo una señal de voz encriptada legible. Este método es apropiado para transmitir señales de voz seguras porque en la señal encriptada no quedan rastros del mensaje secreto original. En el caso de esteganografía, la señal de voz adaptada se oculta en una señal de voz huésped, utilizando sustitución directa o indirecta. En el primer caso el esquema se denomina EWM y en el segundo caso iEWM. EWM demostró ser altamente transparente, mientras que iEWM demostró ser altamente robusto contra manipulaciones de señal. Finalmente, con el propósito de transmitir señales de voz seguras en tiempo real, se propone un esquema para dispositivos hardware

    Haar Transformation for Compressed Speech Hiding

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    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

    RABS: Rule-Based Adaptive Batch Steganography

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    Video Steganography Techniques: A Survey

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    In digital world, information security is the major issue in digital communication on a network from the third party hackers. Steganography techniques play an important role in information security. These are the secure techniques, used for concealing existence of secret information in any digital cover object viz. image, audio, video files. In last several decades, significant researches have been done on video and image steganography techniques because data embedding and data extraction is very simple. However, many researchers also take the audio file as a cover object where robustness and undetectability of information is very difficult task. The main objective of steganography is hiding the existence of the embedded data in any digital cover object. Steganography technique must be robust against the various image-processing attacks. Nowadays, video files are more accepted because of large size and memory requirements. This paper intends to provide a survey on video techniques and provide the fundamental concept of the steganography and their uses

    Color image steganography in YCbCr space

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    Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized

    Strengthening steganoghraphy by using crow search algorithm of fingerprint image

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    In image steganography, secret communication is implemented to hide secret information into the cover image (used as the carrier to embed secret information) and generate a stego-image (generated image carrying hidden secret information).Nature provides many ideas for computer scientists. One of these ideas is the orderly way in which the organisms work in nature when they are in groups. If the group itself is treated as an individual (the swarm), the swarm is more intelligent than any individual in the group. Crow Search Algorithm (CSA) is a meta-heuristic optimizer where individuals emulate the intelligent behavior in a group of crows. It is based on simulating the intelligent behavior of crow flocks and attempts to imitate the social intelligence of a crow flock in their food gathering process. This paper presents a novel meta-heuristic approach based on the Crow Search Algorithm (CSA), where at the beginning the color cover image is converted into three channels (RGB) and then those channels are converted into three spaces, which are Y, Cb, Cr. After applying Discrete wavelet transform (DWT) on each space separately, the CSA algorithm is used on each space (YCbCr) to find the best location that will be used to hide secret information, the CSA is used to increase the security force by finding the best locations that have high frequency and are invulnerable to attacks, the DWT is used to increase robustness against noise. The proposed system is implemented on three fingerprint cover images for experiments, for the quality of stego image the histogram, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Number of Pixel Change Rate Test (NPCR), Structural Similarity Index Metric (SSIM) and Correlation Coefficients (CC) are computed. The result demonstrated the strength of the CSA to hide data, also discovered that using CSA may lead to finding favorable results compared to the other algorithm
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