International Journal of Computer Science and Information Technology 

About: International Journal of Computer Science and Information Technology is an academic journal published by Academy and Industry Research Collaboration Center. The journal publishes majorly in the area(s): Computer science & Cloud computing. It has an ISSN identifier of 0975-3826. It is also open access. Over the lifetime, 676 publications have been published receiving 6088 citations.

Edge detection techniques for image segmentation

Abstract: Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.

Security threats on cloud computing vulnerabilities

Abstract: Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a “realistic” network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, countermeasures to cloud security breaches are presented.

Common phases of computer forensics investigation models

Abstract: The increasing criminal activities using digital information as the means or targets warrant for a structured manner in dealing with them. Since 1984 when a formalized process been introduced, a great number of new and improved computer forensic investigation processes have been developed. In this paper, we reviewed a few selected investigation processes that have been produced throughout the years and then identified the commonly shared processes. Hopefully, with the identification of the commonly shard process, it would make it easier for the new users to understand the processes and also to serve as the basic underlying concept for the development of a new set of processes. Based on the commonly shared processes, we proposed a generic computer forensics investigation model, known as GCFIM.

Diagonal Based Feature Extraction for Handwritten Alphabets Recognition System Using Neural Network

Abstract: An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described in the paper. A new method, called, diagonal based feature extraction is introduced for extracting the features of the handwritten alphabets. Fifty data sets, each containing 26 alphabets written by various people, are used for training the neural network and 570 different handwritten alphabetical characters are used for testing. The proposed recognition system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the conventional horizontal and vertical methods of feature extraction. This system will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.

A novel technique for image steganography based on Block-DCT and Huffman Encoding

Abstract: Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on DWT, where DWT is used to transform original image (cover image) from spatial domain to frequency domain. Firstly two dimensional Discrete Wavelet Transform (2-D DWT) is performed on a gray level cover image of size M × N and Huffman encoding is performed on the secret messages/image before embedding. Then each bit of Huffman code of secret message/image is embedded in the high frequency coefficients resulted from Discrete Wavelet Transform. Image quality is to be improved by preserving the wavelet coefficients in the low frequency subband. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.