International Journal of Computer Science and Information Security

Vol. 12 No. 6 JUN 2014

Vol. 12 No. 6 JUNE 2014 International Journal of Computer Science and Information Security

Publication JUNE 2014, Volume 12 No. 6 (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 31121321: Fault Tolerance Mechanisms for Wireless Sensor Networks (pp. 1-8)

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Youness LYAZIDI*, Ahmed KAMIL#, Amina MERBAH#, Hicham BELHADAOUI#, Mohamed OUZZIF#

# GI Department, RITM-ESTC / CED-ENSEM, University Hassan II Km 7, Eljadida Street, B.P. 8012 Oasis, Casablanca, Morocco

*LEC – EMI, Rabat, Morocco

Abstract -- Wireless Sensor Networks have become a new information collection and monitoring solution for several applications. The failure of sensor node is either because of communication device failure, battery or the harsh environment where the sensor node is deployed and sensor device related problems. In order to maintain the high quality of WSN (Wireless Sensor Network), detection of failed or malfunctioning sensor node is essential to avoid further degradation of the service. This paper presents a new method to detect the sensor node failure or malfunctioning related to a specific platform for collecting data in wsn. We propose a localized fault detection method to identify the faulty sensors specific to each case of failure related to the platform. The method consists on a localized fault detection algorithm to identify the faulty sensors. In a large scale the complexity of the algorithm became high. Simulation results show that the algorithm can clearly identify the faulty sensors and faulty zones with high accuracy and lightly influence the energy consumptions of participated sensor nodes.

Keywords--- WSN, Fault tolerance, errors detection

2. Paper 31051403: Implementation of Two link Articulated Robot Kinematic Simulation using Echo state neural network (pp. 9-13)

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M. R Prapulla, Research Scholar, Department of EEE, VInayaka Mission and University, Salem, India,

Dr. Puttamadappa C., Principal, Sapthagiri College of Engineering, Bangalore, India

Abstract - This paper presents the estimation of joint angles of two link robot using echo state neural network (ESNN).The ESNN is trained with x,y coordinates and joint angles. The data used for training the ESNN corresponding to the robot working space. Estimation accuracy of the ESNN is good for estimating the joint angles.

Keyword: Echo state neural network; Forward Kinematics; Inverse Kinematics; Robotics; Degree of Freedom; joint transformations.

3. Paper 31051411: New Hybrid Intrusion Detection System based on Data Mining Technique to Enhanced Performance (pp. 14-19)

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Vidula Shukla & Sumit Vashishtha; CSE Dept, SIRT, Bhopal, India.

Abstract - Intrusion Detection Systems (IDSs) is an efficient defense technique against network attacks as well host attacks since they allow network/host administrator to detect any type policy violations. However, traditional IDS are vulnerable and they are not reliable to novel and original malicious attacks. Also, it is very inefficient to analyze from a big amount of data such as possibility logs. Moreover, there are high false positives and false negatives for the common OSs. There are many other techniques which can help to improve the quality and results of IDS in which data mining one of them where it has been popularly recognized/identify as an important way to mine useful information from big amount of data which is noisy, and random. Integration of various data mining techniques with IDS to improve efficiency is the motive of proposed research. Proposed research is combining three data mining technique to reduce over head and improve execution efficiency in intrusion detection system (IDS). The Proposed research that ensembles clustering (K-Mean), Apriori and a classifications (Decision Tree) approaches. Proposed IDS execute on the standard KDD’99 (knowledge Discovery and Data Mining) Data set; this data set is used for measuring the performance of intrusion detection systems. Proposed system can detect the intrusions and classify them into four categories: Probe, Denial of Service (DoS), U2R (User to Root), and R2L (Remote to Local). A presented experiment results is carried out to the performance of the proposed IDS using KDD 99’ dataset. Its shows that the proposed IDS performed better in term of accuracy, and efficiency.

Keywords— Internet; Intrusion detection; Data mining; Clustering, Classification, Data preprocessing.

4. Paper 31051412: Macro Variable Predictive Model in Determining Susceptibility Regions using Combined Methods of Double Exponential Smoothing and Fuzzy MCDM (Case Study: Central Java Province) (pp. 20-28)

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Alessandro C. Baramuli, Faculty of Information Technology, Satya Wacana Christian University Diponegoro Street, 52-60, Salatiga, 50711, Indonesia

Sri Yulianto J. P., Faculty of Information Technology, Satya Wacana Christian University, Diponegoro Street, 52-60, Salatiga, 50711, Indonesia

Kristoko D. Hartomo, Faculty of Information Technology, Satya Wacana Christian University, Diponegoro Street, 52-60, Salatiga, 50711, Indonesia

Abstract — The problem of regions that are vulnerable to be poor has been a particular concern in Central Java Province. One important aspect to support the reduction of regions that are vulnerable to be poor is the availability of accurate data. This study aims to provide an alternative solution by creating a predictive model of macro variable to determine areas which are vulnerable to be poor in the region of Central Java Province, which has poor population of as many as 4,704,870 people, with 14.44 percent of poor people in September 2013. The prediction model built is using combination methods of Double Exponential Smoothing (DES) and Fuzzy MCDM (FMCDM). DES method is used to predict the macro variable which is the rate percentage of the school of 7-12 years enrollment, the rate percentage of the school of 12-15 years enrollment, the percentage of the population working in the informal sector, the percentage of population working in the formal sector, and the percentage of contraceptive users. The validation results of the predictions are done by the approaches of MAPE, MSE and MAD. To determine the areas that are vulnerable to be poor, the macro variables data of the prediction results will be evaluated using the FMCDM method. The result of this study is a model that can provide visualization of predicted regions that are vulnerable to be poor in Central Java to the stakeholders as decision makers, by utilizing information technology that is based on geographic information systems, and is expected to assist in the planning of countermeasuring regions that are vulnerable to be poor.

Keywords— Prediction, Double Exponential Smoothing, Validation, Fuzzy MCDM, Poverty, Vulnerability.

5. Paper 31051416: The control model of security in the deployment of ERP systems (pp. 29-35)

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Setare Yaghubi, Department of Computer, Zanjan Branch, Islamic Azad University, Zanjan, Iran

Nasser modiri, Assoc. Prof, Department of Computer, Zanjan Branch, Islamic Azad University, Zanjan, Iran

Abstract - Systems ERP software packages are vast and its implementation is facing with many complexity and challenges. The successful implementation of ERP in an organization depends on many factors. The successful implementation of ERP in an organization depends on many factors. This is very important in case of ERP systems due to the specific nature and affect all processes and activities of the organization. With the development of Web-based software to Smart invasions need to improve security during the implementation process there is. In this study reviews key success factors in ERP systems implementation methodologies and factors are discussed, and an approach to improve security during critical phases of implementation are proposed.

Keywords: methodologies implementation of systems ERP, ERP Security Control, CSF, AIM, ASAP

6. Paper 31051417: A Survey of Power Management Techniques of Computing Systems (pp. 36-39)

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Valma Prifti, Polytechnic Unviersity of Tirana, Mechanical Faculty

Igli Tafa & Suida Ajdini, Faculty of Information Technology, Polytechnic University of Tirana

Abstract - All we know that in our days, battery lifetime is an important feature of personal computers, smart phones, tablets, i-pads etc. Consequently power consumption is becoming a big economical and ecological problem in IT industry. According to EPA, for every 1000 Kwh consumed electricity, is generated 0.73 tons CO2 [1]. Consequently It produces huge environment pollution. In this paper we review some techniques to decrease as much as we can power consumption while having the minimum of impact in our CPU performance.

Key words: CPU power consumption, power reducing, power management techniques, high performance computing, minimizing energy consumption, dynamic voltage scaling

7. Paper 31051420: Business Type Classification via E-commerce Stage Model in Oil Industry in Iran (pp. 40-47)

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Mohammad Nassiry, Faculty of Information Science & Technology, University Kebangsaan Malaysia, Tehran, Iran

Prof. Dr. Muriati Mukhtar, Faculty of Information Science & Technology, University Kebangsaan Malaysia Kuala Lumpur, Malaysia

Abstract — since the strategies and plans for e-commerce development are different for different industries and since the oil industry is one of the most important industries in Iran, the scope of this research is thus confined to that of the oil industry in Iran. The main aim of this study is to identify and classify the different features of e-commerce development stages and features based on the different business types present in companies in the oil industry in Iran. In order to achieve both of these objectives a questionnaire was developed and administered online. The questionnaire was distributed to forty representatives working in different companies. The collected data was classified and sorted and the priority e-commerce features was classified and displayed as triangles for each business type. Furthermore, the experts were asked to indicate the features which they implemented in their companies in order to know the most used features in each stage. The results of this study give an insight to the practice of e-commerce for Iranian oil companies and can be used to strategize future directions for the industry in terms of e-commerce.

Keywords-component; E-commerce, E-business Model, E-commerce Stage Model, Business Types, Oil Industry

8. Paper 31051424: Vulnerability analysis of E-transactions in the Banking Industry, with a specific reference to malwares and types of attacks (pp. 48-54)

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Mrs T. K. George & Dr. (Prof) Paulose Jacob, Dept. of Computer Science, Cochin University of Science and Technology

Abstract - One of the most important features of E-banking is to deliver the new banking services & products to the extended customer database by the effective use of internet technology with a lesser transaction cost and without the traditional constraints on time and place. E-banking makes use of computers and related technologies to retrieve and process the transactions with a bank or other financial service providers. In order to reduce the potential vulnerabilities against the security, many vendors have developed various solutions in both software-based and hardware-based systems. Finding a solution, to patch up security holes, is a quintessential element for the future of the banking Industry.

Key words: E-banking, transactions, constraints, patch, security, Vulnerability

9. Paper 31081317: Hybrid Encryption Technique Using RSA with SHA-1 Algorithm in Data-At-Rest and Data-In-Motion Level (pp. 55-61)

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Aarthi.G, Mother Therasa Women University, Kodaikanal, Tamil Nadu, India.

Dr. E. Ramaraj, Dept. Of Computer Sci.& Engg., Alagappa University,Karaikudi, Tamil Nadu, India.

Abstract - Data base security is the mechanisms that protect the data base against intentional or accidental threats. It is also a specialty within the broader discipline of computer security using encryption techniques. Encryption is one of the security methods in database security. To secure the data, it is an essential to propose a new methodology to avoid such kind of attacks for securing the data-at-rest and data-in-motion level. This paper proposes a hybrid encryption technique for secure the database. The proposed hybrid encryption technique used to secure data-at-rest and data-in-motion level with RSA and SHA-1algorithms that led to strong security. The aim of the proposed hybrid encryption technique is to provide better confidentiality, integrity and availability among other security protocols.

Keywords- Data-at-rest; Data-in-motion; RSA; SHA-1; Hybrid Encryption.

10. Paper 31041413: Efficiency Analysis of Materialized views in Data Warehouse Using Self-maintenance (pp. 62-66)

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Mehwish Aziz, Govt Post Graduate College, S/town, Rawalpindi

Shabnam Nawaz, Govt Post Graduate College, S/town, Rawalpindi

Pakeeza Batool, Govt Post Graduate College, S/town, Rawalpindi, Department of Information Technology

Abstract — A data warehouse is a large data repository for the purpose of analysis and decision making in organizations. To improve the query performance and to get fast access to the data, data is stored as materialized views (MV) in the data warehouse. When data at source gets updated, the materialized views also need to be updated. In this paper, we focus on the problem of maintenance of these materialized views and address the issue of finding such auxiliary views (AV) that together with the materialized views make the data self-maintainable and take minimal space. We propose an algorithm that uses key and referential constraints which reduces the total number of tuples in auxiliary views and uses idea of information sharing between these auxiliary views to further reduce number of auxiliary views.

Keywords—Materialized views (MV), Auxiliary views (AVs), Referential integrity (RI).

11. Paper 31051429: Heart Disease Diagnosis by Using FFBP and GRNN Algorithm of Neural Network (pp. 67-72)

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Shaikh Abdul Hannan, Department of Computer Science and IT, Albaha University, Albaha, Saudi Arabia

Abstract - An expert system is a computer program that simulates the thought process of a human expert to solve complex decision problems. The growth of expert systems is expected to continue for several years. In the last two decades, the use of Neural Network in medical analysis is increasing. This is mainly because the classification and detection system have improved a great deal to help the medical experts in diagnosing. Heart disease affects millions of people every year. As clinical decision making inherently requires reasoning under uncertainty, expert system and Neural Network technique are suitable for dealing with partial evidence. Medical trainee doctors other than specialist may not have enough expertise or experience to deal with certain high risk diseases. With this system the patients with high risk factors can recover. In this paper, the detail about patient data collection procedure, coding, normalization and tabulation is given. The experiments are perform on data collected using Feed-forward Backpropagation. In this work around 300 patients information has been collected from Sahara Hospital, Aurangabad under the observation of Dr. Abdul Jabbar. For data collection of 350 patients around 9 months has spend by sitting in OPD of Hospital along with concerned doctor. The final coded, normalized and tabulated data and results has been verified by Dr. Abdul Jabbar and is satisfied with the result.

Keywords: Expert System, ANN (Artificial Neural network), FFBP (Feed forward backpropagation algorithm), Generalized Regression Neural Network, Medicine, Symptoms.

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