International Journal of Computer Science and Information Security

Vol. 12 No. 2 FEB 2014

Vol. 12 No. 2 FEBRUARY 2014 International Journal of Computer Science and Information Security

Publication FEBRUARY 2014, Volume 12 No. 2 (Download Full Journal) (Archive) (Download 2)

Copyright © IJCSIS. This is an open access journal distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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1. Paper 31011408: Security in VoIP (pp. 1-4)

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Elsayed M. Elshamy, Osama S. Faragalla, Sayed El-Rabaie, Osama Elshakankiry and Fathi Sayed

Computer Sciences and Engineering Department, Faculty of Electronic Engineering, Menouf 32951, Menoufia University, Egypt

Abstract — In recent years, result of the significant in the field of information technology, secure communication techniques have increased widely and unexpectedly, Specially with VoIP communication network. In order to establish reliable communication technology and to ensure that voice reaches its intended end and to be accessible to all through the shared network, there is a need to secure communication in VoIP communication networks and encrypt the transmitted voice “VOICE MAIL”. The proposed system is performed in two stages, the first stage includes cryptosystem with Chaotic Encryption of voice. The second stage using fingerprint authentication.

Keywords — VoIP, Fingerprint Authentication, Chaotic Encryption, Cryptosystem.

2. Paper 31011412: Performance Comparison of Column Hybrid Row Hybrid and full Hybrid Wavelet Transform on Image compression using Kekre Transform as Base Transform (pp. 5-17)

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Dr. H. B. Kekre, Sr. Professor, MPSTME, Department of Computer Engineering, NMIMS University, Mumbai, India

Dr. Tanuja Sarode, Associate Professor, Department of Computer Engineering, TSEC, Mumbai University, Mumbai, India

Prachi Natu, Assistant Professor and Ph. D. Research Scholar, MPSTME, NMIMS University, Mumbai, India

Abstract - This paper proposes color image compression using hybrid wavelet transform. Hybrid wavelet transform is generated using two different orthogonal component transforms. Kekre transform is used as base transform. It is combined with other transforms like DCT, DST, Hartley, Walsh, Real-DFT and Slant transform. Generated hybrid wavelet transform is applied on image as column transform, row transform and full hybrid wavelet transform to compress the image. Root mean square error is computed in these three cases at various compression ratios and compared. It has been observed that Full hybrid wavelet transform gives error which is nearly half of the error generated in column and row hybrid wavelet transform. DKT-DCT hybrid wavelet shows least RMSE than DKT-DST, DKT-Hartley, DKT-Walsh, DKT-Real-DFT and DKT-Slant hybrid wavelet transform. DKT-DCT full hybrid wavelet transform gives RMSE 11.17 at compression ratio 32, whereas using column hybrid wavelet error value is 27.85 at the same compression ratio. It shows that to save number of computations, column hybrid wavelet transforms or row wavelet transform can be used at the cost of compression ratio.

Keywords- Hybrid Wavelet Transform; Real DFT; Kekre Transform; Image Compresion; Bit Rate

3. Paper 31011417: An Optimized Multiplier Architecture for a Dual Field Processor For ECC (pp. 18-24)

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Nagaraja Shylashree, Research Scholar, Department of E & C Engineering, VTU, PESCE, Mandya, Karnataka, India

Venugopalachar Sridhar, Department of E & C Engineering, VTU, PESCE, Mandya, Karnataka, India

Abstract — This paper presents an optimized multiplier architecture for a Dual field Elliptic curve cryptographic (DFECC) processor for both Galois prime field GF(p) and binary field GF(2m), by the selection of proper type of coordinates in the Elliptic curve cryptographic (ECC) arithmetic unit. In this unit, multiplication plays important role to perform scalar multiplication (kP) .We present two multiplier architectures, using FPGA Virtex-5 as the target device. These are, multiplier using carry save adder (CSA) and vedic multiplier. The proposed Dual field ECC processor using Vedic multiplier can reach a speed up to 151MHz.

Keywords - Dual Field ECC; Galois Field; Elliptic curve scalar multiplication; Elliptic curve point addition; Elliptic curve point doubling; Dual field multiplier; Dual field adder; Vedic multiplier; FPGA.

4. Paper 31011422: Wavelet based Iris Recognition for Biometric Systems (pp. 25-29)

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Jitendra Singh Uriaya, Department of Electronics and Communication, Jabalpur Engineering College, Jabalpur India (482011)

Agya Mishra, Department of Electronics and Communication, Jabalpur Engineering College, Jabalpur India (482011)

Abstract ─ Iris recognition is a critical area of research in the field of security system and personal identification. In this paper, a novel, efficient technique for iris recognition is presented. The aim is to develop a lifting wavelet based algorithm. This method reduces the noise to the maximum extent possible, and extracts important information from the image. In this paper recognition is being done biorthogonal wavelet based method which is then compared with other wavelet family. The method was tested on the CASIA dataset of iris image. For matching the iris template Hamming Distance technique is used and checks the accuracy of the system. The present algorithm provides the 94.4% recognition rate and accuracy approx. 99 % on the CASIA iris data base version 1.

Keywords─ Iris recognition, Biorthogonal wavelet, Haar wavelet, Daubechies wavelet, Iris template, Hamming distance, Match score.

5. Paper 31011429: Performance of Watermarking System using Wavelet Column Transform under Various Attacks (pp. 30-35)

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Dr. H. B. Kekre, Senior Professor, Computer Engineering Department MPSTME, NMIMS University, Vile Parle, Mumbai, India,

Dr. Tanuja Sarode, Associate Professor, Computer Department, Thadomal Shahani Engg. College, Bandra, Mumbai 50, India

Shachi Natu, Ph.D. Research Scholar, Computer Engineering Department MPSTME, NMIMS University, Vile Parle, Mumbai, India

Abstract — In this paper a novel wavelet transform based color image watermarking technique has been proposed. Column wise DCT wavelet transform has been applied to cover image. A watermark of size 128*128 is compressed and embedded in the cover image of size 256*256 using DCT wavelet column transform. Compression of watermark reduces the payload of information to be embedded in the cover image without significant loss of information. Robustness of proposed technique is tested against three types of attacks namely, cropping, Binary distributed run length noise and Gaussian distributed run length noise. Performance of proposed technique is observed for various compression ratios 1.45, 1.6, 1.77, 2, 2.285 and 2.67 beyond which the distortion in compressed watermark is perceptible. This technique proves to be exceptionally robust for Binary distributed run length noise attack. For Gaussian distributed run length noise attack also acceptable robustness is achieved. For cropping also it gives good performance except compression ratio 2. Higher compression of watermark results in better imperceptibility of watermarked image. Also higher compression ratio leads to increased robustness against attacks on watermarked image.

Index Terms — Watermarking, DCT wavelet, Column transform, Binary distributed Run length noise, Gaussian distributed Run length noise.

6. Paper 31011433: Content Based Image Retrieval Through Distance Similarity Metrics (pp. 36-40)

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Praveen Mishra, Department of Computer Science, VNS Institute of Technology Bhopal, India

Prof. G.S Prajapati, Department of Computer Science, VNS Institute of Technology

Abstract - Searching Test Image from Image databases using features extraction from the content is currently an active research area. In this work we present novel feature extraction approaches for content-based image retrieval when the query image is color image. To facilitate robust man-machine interfaces, we accept query images with color attributes. Special attention is given to the similarity measure with different distance matrices properties since the Test Image and Object Image from database finding the distance measuring. Several applicable techniques within the literature are studied for these conditions. The goal is to present the user with a subset of images that are more similar to the Object Image. One of the most important aspects of the proposed methods is that the accuracy measurement of the different database images. This significantly improves the feature extraction process and enables the methods to be used for other computer vision applications.

Keyword - Color image, Image retrieval, Euclidean metrics, Manhattan metrics and Correlation.

7. Paper 31121329: Evolutionary Neural Network Model For Dynamic Channel Allocation In Mobile Communication Network (pp. 41-55)

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Ojesanmi Olusegun and Ugege Peter, Department of Computer Science, Federal University of Agriculture, Abeokuta, Nigeria.

Abstract - Mobile communication aims at transmitting multimedia data and at the same time provides guaranteed quality of service (QoS) to all the applications. The challenge is to develop an efficient allocation scheme for assigning resources without compromising the QoS. In meeting this challenge, this paper proposes an evolutionary neural network approach with dynamic allocation to utilize frequency spectrum efficiently and to reduce call blocking probabilities.

Keywords: Neural Network, Mobile network, call blocking probabilities, dynamic channel, QoS, Multimedia.

8. Paper ID45 : Segmentation of Kannada Handwritten Text Line through Computation of Variance (pp. 56-60)

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Sunanda Dixit (1), Suresh Hosahalli Narayan (2)

(1)Information Science and Engineering Department, Dayananda Sagar, College of Engineering, Bangalore, India

(2) Department of Instrumentation Technology, Bangalore Institute of Technology, Bangalore, India

Abstract — Handwritten text line segmentation is an important task of Optical Character Recognition. The proposal discusses a novel technique for Segmentation of Lines for the handwritten text document written in Kannada Language. The algorithm imbibes the approach of finding the Components, bounding box and computing the coefficient of variance. Preprocessing steps such as correction of skewness due to improper scanning as well as removal of noise is assumed to have been performed on the data. Our technique of line segmentation addresses the key complexity issue of variations in the gaps between and across lines as well as curly and skew character text of handwritten document. The purpose of this paper is to segment line by connecting the centroids within the bounding box and employing the coefficient of variance. The method has been tested on unconstrained Kannada scripts. An experimental result obtained by executing the proposed method of line segmentation has achieved high degree of accuracy and high performance.

Keywords— Centroids, Coefficient of Variance, Document Image Processing, Optical Character Recognition, Text line segmentation

9. Paper ID64: Incremental Classification using Feature Tree (pp. 61-65)

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N N Vadnere #, R G Mehta *, D P Rana *, N J Mistry *, M M Raghuwanshi **

# M.Tech, Computer Science Department, Manipal University Jaipur, Jaipur, India

* SVNIT, Surat, India

**RGCET, Nagpur, India

Abstract — In recent years, stream data have become an immensely growing area of research for the database, computer science and data mining communities. Stream data is an ordered sequence of instances. In many applications of data stream mining data can be read only once or a small number of times using limited computing and storage capabilities. Some of the issues occurred in classifying stream data that have significant impact in algorithm development are size of database, online streaming, high dimensionality and concept drift. The concept drift occurs when the properties of the historical data and target variable change over time abruptly in such a case that the predictions will become inaccurate as time passes. In this paper the framework of incremental classification is proposed to solve the issues for the classification of stream data. The Trie structure based incremental feature tree, Trie structure based incremental FP (Frequent Pattern) growth tree and tree based incremental classification algorithm are introduced in the proposed framework.

Keywords— Stream Data, Trie, Discretization, Incremental Classification, Feature-Tree

10. Paper ID69: Discretization of Temporal Data: A Survey (pp. 66-69)

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P. Chaudhari *, D. P. Rana *, R. G. Mehta *, N. J. Mistry *, M. M. Raghuwansh i#

*SVNIT, Surat, India

#RGCET, Nagpur, India

Abstract — In real world, the huge amount of temporal data is to be processed in many application areas such as scientific, financial, network monitoring, sensor data analysis. Data mining techniques are primarily oriented to handle discrete features. In the case of temporal data the time plays an important role on the characteristics of data. To consider this effect, the data discretization techniques have to consider the time while processing to resolve the issue by finding the intervals of data which are more concise and precise with respect to time. Here, this research is reviewing different data discretization techniques used in temporal data applications according to the inclusion or exclusion of: class label, temporal order of the data and handling of stream data to open the research direction for temporal data discretization to improve the performance of data mining technique.

Keywords— Temporal data, Discretization, Supervised, Incremental, Nonparametric

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