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International Journal of Information, Control and Computer Sciences

ISSN: 2517-9942

Total 41 content found

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An Anonymity-Based Secure On-Demand Routing for Mobile Ad Hoc Networks

Year: 2014 Volume: 8 Issue: 1 105 - 114 Pages

Abstract: Privacy and Security have emerged as an important research issue in Mobile Ad Hoc Networks (MANET) due to its unique nature such as scarce of resources and absence of centralized authority. There are number of protocols have been proposed to provide privacy and security for data communication in an adverse environment, but those protocols are compromised in many ways by the attackers. The concept of anonymity (in terms of unlinkability and unobservability) and pseudonymity has been introduced in this paper to ensure privacy and security. In this paper, a Secure Onion Throat (SOT) protocol is proposed to provide complete anonymity in an adverse environment. The SOT protocol is designed based on the combination of group signature and onion routing with ID-based encryption for route discovery. The security analysis demonstrates the performance of SOT protocol against all categories of attacks. The simulation results ensure the necessity and importance of the proposed SOT protocol in achieving such anonymity.

A Model for Test Case Selection in the Software-Development Life Cycle

Year: 2014 Volume: 8 Issue: 1 100 - 104 Pages

Abstract: Software maintenance is one of the essential processes of Software-Development Life Cycle. The main philosophies of retaining software concern the improvement of errors, the revision of codes, the inhibition of future errors, and the development in piece and capacity. While the adjustment has been employing, the software structure has to be retested to an upsurge a level of assurance that it will be prepared due to the requirements. According to this state, the test cases must be considered for challenging the revised modules and the whole software. A concept of resolving this problem is ongoing by regression test selection such as the retest-all selections, random/ad-hoc selection and the safe regression test selection. Particularly, the traditional techniques concern a mapping between the test cases in a test suite and the lines of code it executes. However, there are not only the lines of code as one of the requirements that can affect the size of test suite but including the number of functions and faulty versions. Therefore, a model for test case selection is developed to cover those three requirements by the integral technique which can produce the smaller size of the test cases when compared with the traditional regression selection techniques.

Prediction of Research Topics Using Ensemble of Best Predictors from Similar Dataset

Year: 2014 Volume: 8 Issue: 1 93 - 99 Pages

Abstract: Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.

FPGA Implementation of RSA Encryption Algorithm for E-Passport Application

Year: 2014 Volume: 8 Issue: 1 89 - 92 Pages

Abstract: Securing the data stored on E-passport is a very important issue. RSA encryption algorithm is suitable for such application with low data size. In this paper the design and implementation of 1024 bit-key RSA encryption and decryption module on an FPGA is presented. The module is verified through comparing the result with that obtained from MATLAB tools. The design runs at a frequency of 36.3 MHz on Virtex-5 Xilinx FPGA. The key size is designed to be 1024-bit to achieve high security for the passport information. The whole design is achieved through VHDL design entry which makes it a portable design and can be directed to any hardware platform.

Optimal Dynamic Economic Load Dispatch Using Artificial Immune System

Year: 2014 Volume: 8 Issue: 1 82 - 88 Pages

Abstract: The The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Rough Neural Networks in Adapting Cellular Automata Rule for Reducing Image Noise

Year: 2014 Volume: 8 Issue: 1 78 - 81 Pages

Abstract: The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Optimal Dynamic Economic Load Dispatch Using Artificial Immune System

Year: 2014 Volume: 8 Issue: 1 71 - 77 Pages

Abstract: The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand.  Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Requirements Gathering for Improved Software Usability and the Potential for Usage-Centred Design

Year: 2014 Volume: 8 Issue: 1 65 - 70 Pages

Abstract: Usability is an important software quality that is often neglected at the design stage. Although methods exist to incorporate elements of usability engineering, there is a need for more balanced usability focused methods that can enhance the experience of software usability for users. In this regard, the potential for Usage-Centred Design is explored with respect to requirements gathering and is shown to lead to high software usability besides other benefits. It achieves this through its focus on usage, defining essential use cases, by conducting task modeling, encouraging user collaboration, refining requirements, and so on. The requirements gathering process in UgCD is described in detail.

Enhancing Privacy-Preserving Cloud Database Querying by Preventing Brute Force Attacks

Year: 2014 Volume: 8 Issue: 1 58 - 64 Pages

Abstract: Considering the complexities involved in Cloud computing, there are still plenty of issues that affect the privacy of data in cloud environment. Unless these problems get solved, we think that the problem of preserving privacy in cloud databases is still open. In tokenization and homomorphic cryptography based solutions for privacy preserving cloud database querying, there is possibility that by colluding with service provider adversary may run brute force attacks that will reveal the attribute values. In this paper we propose a solution by defining the variant of K –means clustering algorithm that effectively detects such brute force attacks and enhances privacy of cloud database querying by preventing this attacks.

Dissolved Oxygen Prediction Using Support Vector Machine

Year: 2014 Volume: 8 Issue: 1 53 - 57 Pages

Abstract: In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Review and Comparison of Associative Classification Data Mining Approaches

Year: 2014 Volume: 8 Issue: 1 41 - 52 Pages

Abstract: Associative classification (AC) is a data mining approach that combines association rule and classification to build classification models (classifiers). AC has attracted a significant attention from several researchers mainly because it derives accurate classifiers that contain simple yet effective rules. In the last decade, a number of associative classification algorithms have been proposed such as Classification based Association (CBA), Classification based on Multiple Association Rules (CMAR), Class based Associative Classification (CACA), and Classification based on Predicted Association Rule (CPAR). This paper surveys major AC algorithms and compares the steps and methods performed in each algorithm including: rule learning, rule sorting, rule pruning, classifier building, and class prediction.

A Weighted Approach to Unconstrained Iris Recognition

Year: 2014 Volume: 8 Issue: 1 37 - 40 Pages

Abstract: This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Development of a Vegetation Searching System

Year: 2014 Volume: 8 Issue: 1 34 - 36 Pages

Abstract:   This paper describes the development of a Vegetation Searching System based on Web Application in case of Suan Sunandha Rajabhat University. The model was developed by PHP, JavaScript and MySQL database system and it was designed to support searching for endemic and rare species of trees on Web site. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for the system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 4.30 and 4.50, and standard deviation for experts and users were 0.61and 0.73 respectively. Further analysis showed that the quality of the plant searching Website was also at a good level as well.

A Development of OTOP Web Application: In Case of Samut Songkhram Province

Year: 2014 Volume: 8 Issue: 1 31 - 33 Pages

Abstract: This paper aims to present the development of a web‑based system to serve the need of selling OTOP products in Samut Songkhram, Thailand. This system was designed to promote and sell OTOP products on Web site. We describe the design approaches and functional components of this system. The system was developed by PHP and JavaScript and MySQL database System. To evaluate the system performance, questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory as followed: Means for specialists and users were 4.05 and 3.97, and standard deviation for specialists and users were 0.563 and 0.644 respectively. Further analysis showed that the quality of One Tambon One Product (OTOP) Website was also at a good level as well.

Mining Educational Data to Support Students’ Major Selection

Year: 2014 Volume: 8 Issue: 1 28 - 30 Pages

Abstract: This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well. 

Analysis of Users’ Behavior on Book Loan Log Based On Association Rule Mining

Year: 2014 Volume: 8 Issue: 1 25 - 27 Pages

Abstract: This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, Apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Enhanced Automated Teller Machine Using Short Message Service Authentication Verification

Year: 2014 Volume: 8 Issue: 1 21 - 24 Pages

Abstract: The use of Automated Teller Machine (ATM) has become an important tool among commercial banks, customers of banks have come to depend on and trust the ATM conveniently meet their banking needs. Although the overwhelming advantages of ATM cannot be over-emphasized, its alarming fraud rate has become a bottleneck in it’s full adoption in Nigeria. This study examined the menace of ATM in the society another cost of running ATM services by banks in the country. The researcher developed a prototype of an enhanced Automated Teller Machine Authentication using Short Message Service (SMS) Verification. The developed prototype was tested by Ten (10) respondents who are users of ATM cards in the country and the data collected was analyzed using Statistical Package for Social Science (SPSS). Based on the results of the analysis, it is being envisaged that the developed prototype will go a long way in reducing the alarming rate of ATM fraud in Nigeria.

Improved MARS Ciphering Using a Metamorphic-Enhanced Function

Year: 2014 Volume: 8 Issue: 1 17 - 20 Pages

Abstract: MARS is a shared-key (symmetric) block cipher algorithm supporting 128-bit block size and a variable key size of between 128 and 448 bits. MARS has a several rounds of cryptographic core that is designed to take advantage of the powerful results for improving security/performance tradeoff over existing ciphers. In this work, a new function added to improve the ciphering process it is called, Meta-Morphic function. This function use XOR, Rotating, Inverting and No-Operation logical operations before and after encryption process. The aim of these operations is to improve MARS cipher process and makes a high confusion criterion for the Ciphertext.

Development of a Vegetation Searching System

Year: 2014 Volume: 8 Issue: 1 14 - 16 Pages

Abstract: This paper describes the development of a Vegetation Searching System based on Web Application in case of Suan Sunandha Rajabhat University. The model was developed by PHP, JavaScript and MySQL database system and it was designed to support searching for endemic and rare species of trees on Web site. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for the system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 4.30 and 4.50, and standard deviation for experts and users were 0.61and 0.73 respectively. Further analysis showed that the quality of the plant searching Website was also at a good level as well.

Genetic Algorithm with Fuzzy Genotype Values and Its Application to Neuroevolution

Year: 2014 Volume: 8 Issue: 1 8 - 13 Pages

Abstract: The author proposes an extension of genetic algorithm (GA) for solving fuzzy-valued optimization problems. In the proposed GA, values in the genotypes are not real numbers but fuzzy numbers. Evolutionary processes in GA are extended so that GA can handle genotype instances with fuzzy numbers. The proposed method is applied to evolving neural networks with fuzzy weights and biases. Experimental results showed that fuzzy neural networks evolved by the fuzzy GA could model hidden target fuzzy functions well despite the fact that no training data was explicitly provided.