Secure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre

Most includeding techniques of digital watermark even now working through the direct inclusion in the pixel without taking into account the level of compression (attack) that can go wrong, which makes digital watermark can be discarded easily. In this research, a method was proposed to overcome this problem, which is based on DCT (after image partitioned into non overlapped blocks with size 8×8 pixel), accompanied by a quantization method. The watermark (digital image) is embedded in DCT frequency domain seeking the blocks have highest standard deviation (the checking is only on the AC coefficients) within a predetermined threshold value, then the covered image will compressed (attacked) varying degrees of compression. The suggested met

Algorithms for Arabic stemming available in two main types which are root-based approach and stem-based approach. Both types have problems which have been solved in the proposed stemmer which combined rules of both main types and based on Arabic patterns (Tafealat1) to find the added letters. The proposed stemmer achieved root exploration ratio (99.08) and fault ratio (0.9).

Image retrieval is an active research area in image processing, pattern recognition, and
computer vision. In this proposed method, there are two techniques to extract the feature
vector, the first one is applying the transformed algorithm on the whole image and the second
is to divide the image into four blocks and then applying the transform algorithm on each part
of the image. In each technique there are three transform algorithm that have been applied
(DCT, Walsh Transform, and Kekre’s Wavelet Transform) then finding the similarity and
indexing the images, useing the correlation between feature vector of the query image and
images in database. The retrieved method depends on higher indexing number. <

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

      In this paper an algorithm for Steganography using DCT for cover image and DWT for hidden image with an embedding order key is proposed. For more security and complexity the cover image convert from RGB to YIQ, Y plane is used and divided into four equally parts and then converted to DCT domain. The four coefficient of the DWT of the hidden image are embedded into each part of cover DCT, the embedding order based on the order key of which is stored with cover in a database table in both the sender and receiver sender. Experimental results show that the proposed algorithm gets successful hiding information into the cover image. We use Microsoft Office Access 2003 database as DBMS, the hiding, extracting algo

Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff

The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio