Vol. 13 No. 3 MAR 2015

Vol. 13 No. 3 MARCH 2015 International Journal of Computer Science and Information Security

Publication MARCH 2015, Volume 13 No. 3 (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 28021503: A Novel Approach to Malware Detection using Static Classification (pp. 1-5)

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Sanjam Singla, Department of Computer Science, PEC University of Technology Chandigarh, India

Ekta Gandotra, Department of Computer Science, PEC University of Technology Chandigarh, India

Divya Bansal, Department of Computer Science, PEC University of Technology Chandigarh, India

Sanjeev Sofat, Department of Computer Science, PEC University of Technology Chandigarh, India

Abstract — Malware, commonly called computer virus, is one of the top security threats to the computer systems around the globe. These are evolving at a very rapid pace and are continually finding new ways to exploit and infect the systems of various enterprises and businesses. Malwares use different techniques to camouflage themselves to make their lifetime longer. In this paper, we present a simple technique based on static features extracted from Windows PE files. The features used are not only extracted from the header part of the malware but also from the payload i.e. body of malware. The static features used are a combination of Function Call Frequency and Opcode Frequency for differentiating malwares from clean files. This combination of features set makes it a new approach for malware detection which provides an accuracy of 97% for a dataset of 1,230 executables files including 800 malware and 430 cleanwares. For classification purpose, we use machine learning algorithms available in WEKA library. Based on the results obtained, we conclude that both features considered in this work play a significant role in distinguishing malicious files from clean ones.

Keywords- Static Malware Analysis; Machine Learning; Classification;

2. Paper 28021509: Performance Evaluation of IEEE 802.15.6 Improvised and Scheduled Access Modes for Remote Patient Monitoring Applications (pp. 6-13)

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Anas Bouayad, Nour El Houda Chaoui, Moulhime El Bekkali, Mohammed El Ghazi

Transmission and Treatment of Information Laboratory, USMBA, FST, FEZ, MOROCCO

Abstract- In the past few years, substantial improvement has been made in the medical field to integrate communication and information technology especially Wireless Body Area Networks (WBANs) in healthcare systems for remote patient monitoring (RPM). The wide diffusion of healthcare monitoring systems allows continuous patient to be remotely monitored and diagnosed by doctors. WBANs have shown great potential in improving healthcare quality, and thus have found a wide range of applications from ubiquitous health monitoring and computer assisted rehabilitation to emergency medical response systems. WBAN operates in close vicinity to, on, or inside a human body and supports a variety of medical applications. Different standards and communications protocols are used in WBANs such as IEEE 802.15.6. The IEEE 802.15.6 standard offers a flexible superframe structure that can be adjusted by the hub to suit the communication requirements of the network and applications. However, the standard leaves the higher level questions open such as: should we use contention-based, scheduled, or improvised access, and under what conditions should we use them. To exploit these access modes we should have a clear understanding of their parameters and operating characteristics. In this work, we are interested in studying access methods and the polling access mechanism used in MAC layer of the IEEE 802.15.6 standard and the proposition of suitable access methods and parameters should be used to increase the performance of the MAC protocol in terms of successful received packets and low latency. Performance evaluation will be based on the simulation of a short range wireless Body Area Network based solution implementing the IEEE 802.15.6. Simulation will be performed on OMNet++ with the Castalia simulator.

Keywords: RPM, wireless Body Area Networks, IEEE 802.15.6, medium access control (MAC) protocols, access methods, polling.

3. Paper 28021505: Comparative Analysis based Classification of KDD’99 Intrusion Dataset (pp. 14-20)

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Shashikant Upadhyay, PG Scholar, Department of Computer Science & Engg, VNSIT, Bhopal, INDIA

Rajni Ranjan Singh, Assistant Professor, Department of Computer Science & Engg, VNSIT, Bhopal, INDIA

Abstract - Intrusion Detection System (IDS) which is used for classifies network traffic information. Mostly traffic information is classified on the basis of normal or anomaly behaviors. In this work an attack specific classification of KDD cup dataset is proposed. Here Naive Bayes, j48, j48 craft, Bayes net and random forest classifiers are explored for the classification. A comparative analysis is carried out to identify best classifiers for each individual attacks based on Precision, recall, f-measures and ROC Curve Area performance criteria’s. It is observed that random forest is the best classifier among all used methods. However despite of the high classification of random forest, BayesNet performed better in context of false positive rate of classification. Similarly ROC Curve Area rate of Bayes net is the best among the all used methods.

Keywords- Classification; KDD Cup ’99; Naive Bayes; BayesNet J48; J48graft and Random Forest.

4. Paper 28021511: Policy-Based Smart Adaptive Quality of Service for Network Convergence (pp. 21-27)

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Ayoub BAHNASSE, Dept. Physic, Lab STIC, Faculty of Sciences EL Jadida, University Chouaïb Doukkali, El Jadida, Morocco

Najib ELKAMOUN, Dept. Physic, Lab STIC, Faculty of Sciences EL Jadida, University Chouaïb Doukkali, El Jadida, Morocco

Abstract — the management of a convergent network has become one of the primordial and challenging tasks. Taking into account the rapid evolution of networks’ size and the diversity of deployed applications, and their requirements in terms of quality of service (QoS), it is quite difficult, on the one hand, to ensure through a manual customization of Quality of Service policies a level of performance required by some flows, on the other hand, to automatically and dynamically adapt QoS policies to instantly optimize the resources, in order to guaranty for applications the required bandwidth and to ensure low loss rates , latency and jitter. This paper presents a novel model of the policy-based Smart adaptive Quality of Service management for clients and Internet service providers. The model proposes separation and distribution of: Data, control and management plans, for a quick and effective treatment, as well as automatically and dynamically reallocates bandwidths, reduce the loss rate and minimize the delay and jitter in a converged network.

Keywords- Quality of service, Adaptive QoS, Smart QoS, Policy-based, network convergence.

5. Paper 28021515: Low Footprint Hybrid Finite Field Multiplier for Embedded Cryptography (pp. 28-32)

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Sunil D. Bobade, Research Scholar, S.G.B.Amravati University, Amravati, India

Dr. Vijay R. Mankar, Deputy Secretary, MSBTE, Pune Region, Pune, India

Abstract — Finite field multiplier contributes significantly to the area occupancy of cryptoprocessor. In this paper, we propose a novel hybrid finite field multiplier that invokes the more efficient multiplication algorithm. The proposed multiplier switches between two variants of multiplier depending on the size of multiplicands. The Karatsuba multiplier is efficient algorithm ensuring fewer LUTs and stable number of Flip-flops for the smaller bit multiplications, while the other systolic variant ensures fewer LUTs count for the bigger size multiplicands. The proposed hybrid multiplier does the initial recursion using the systolic variant while final small sized multiplications are accomplished using the Karatsuba algorithm. Area analysis report suggests that using a proposed hybrid multiplier instead of just traditional Karatsuba Multiplier, eventually helps in reducing FPGA footprint.

Keywords-Karatsuba Multiplier; Modular Multiplication; Cryptoprocessor; Area complexity.

6. Paper 28021520: Base Station Radiation’s Optimization using Two Phase Shifting Dipoles (pp. 33-42)

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Safaa BERRA, Laboratory RITM/ESTC, ENSEM,University of Hassan II, Casablanca, Morocco

Mounir Rifi, Laboratory RITM/ESTC, ENSEMUniversity of Hassan II, Casablanca, Morocco

Abstract — The electromagnetic pollution becomes a serious issue, with the increasing number of telecom operators by country. Certainly the technologies differ, in term of naming (BTS, NodeB, E-NodeB), in term of frequencies, but the problem remains the same: how to optimize the radiation of base station? Is there any intelligent system which allows us to reduce the radiation area and to channel it according to the demand? Far from the complicated and expensive networks of antennas, we are going to present in this paper the use of a simple system of antennas to optimize the base station’s radiation. We will start this article by presenting some techniques that improve the energy consumption in base station which represent an important ratio of the global energy in a cellular network. Then, we will study the phase shifting effect on the gain and the energy efficiency. This paper aims to use the found results to propose a new process to reduce the radiation of base station. In the third part, we propose a new architecture based on the use of two phased dipoles in the base station to cover in a smart way the subscribers as long as they are present in the cell. We propose a new system that allows us to reduce the radiation area.

Keywords — Smart antenna, Phased array system, Dipole, Base station, Energy consumption, Energy efficiency, Gain, Radiation.

7. Paper 28021529: An Efficient Model to Automatically Find Index in Databases (pp. 43-46)

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Mohammad H. Nadimi-Shahraki, Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran

Rezvan Shahriari, Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran

Mohamad Davar Panah Jazi, Department of Computer Engineering, Foulad Institute of Technology, Fouladshahr, Iran

Abstract — The high volume and increasing complexity of data in large organizations requires optimization methods for fast access to data in a database. Choosing the most appropriate index for the database is essential to optimization; the growing need of more complicated indexing makes reliance on current database administrators insufficient. Employing a skilled database administrator to work with complex database management systems is expensive and not an option in many organizations. A more cost-effective approach is use an automated data management system to find the index. Several such approaches have been developed to date. Although there have been many methods based on data mining for finding a proper index, their run time is still unacceptable. Particularly, in very large databases, faster methods for finding proper indexes are needed. In this paper, an efficient model is proposed to automatically find index in databases using maximal frequent patterns. The proposed model is evaluated by conducted benchmark dataset TPC-H to compare with previous methods. The evaluation results show that using the proposed model can decrease the time of finding indexes in databases.

Keywords- Optimization, automatic indexing, maximal frequent patterns

8. Paper 28021530: An Overview and Comparison of Hierarchical P2P-SIP Networks (pp. 47-58)

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Abel Diatta & Ibrahima Niang, Departement de Mathematiques et Informatique Laboratoire d’Informatique de Dakar (LID), Universite Cheikh Anta Diop de Dakar , Dakar, Senegal

Mandicou Ba, Universite de Reims Champagne-Ardenne, Laboratoire CReSTIC EA 3804 - Equipe SysCom, Reims, France

Abstract — P2P-SIP networks are emerging distributed communication technology introducing Scalability and Robustness. These networks propose to use a peer-to-peer network for user registration and user location in Session Initiation Protocol (SIP)-based voiceover- IP (VoIP) networks. Nevertheless, P2P-SIP systems are based on a pure flat DHT design which provides a uniform distribution of (equal) peers and resources that assures scalability and load balancing. Recent research works have proposed to organize P2P overlays into hierarchical architecture called HP2P-SIP. These later are motivated by supporting sophisticated search requirements, separating categories of use (content, personal communications,), scaling, etc. However, these works did not resolve the problem of overloading the bandwidth, which is still a head-case. In this paper, after highlighting the many challenges of hierarchical architectures, we show how to avoid overloading the physical network by acting on the overlay network. To do this, we have a physical network of size N with a number of super nodes (NSN). Our solution shows how many levels k we must build our overlay network so that in the physical network, the number of messages generated by the lookup nodes does not exceed a value x, initially fixed.

Index Terms—HP2P-SIP, Costing, Iterative, Recursive, Semi-recursive, Bandwidth overload

9. Paper 28021531: Unweighted Class Specific Soft Voting based ensemble of Extreme Learning Machine and its variant (pp. 59-65)

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Sanyam Shukla, CSE department, M.A.N.I.T, Bhopal, India

R. N. Yadav, ECE department, M.A.N.I.T, Bhopal, India

Abstract — Extreme Learning Machine is a fast real valued single layer feed forward neural network. Its performance fluctuates due to random initialization of weights between input and hidden layer. Voting based Extreme Learning Machine, VELM is a simple majority voting based ensemble of Extreme learning machine which was recently proposed to reduce this performance variation in Extreme Learning Machine. A recently proposed class specific soft voting based Extreme Learning Machine. CSSV-ELM further refines the performance of VELM using class specific soft voting. CSSV-ELM computes the weights assigned to each class of component classifiers using convex optimization technique. It assigns different weights assuming different classifiers perform differently for different classes. This work proposes Un-weighted Class Specific Soft Voting based ensemble, UCSSV-ELM a variants of CSSV-ELM. The proposed variant uses class level soft voting with equal weights assigned to each class of component classifiers. Here all the classifiers are assumed to be equally important. Soft voting is used with the classifiers that have probabilistic outputs. This work evaluates the performance of proposed ensemble using both ELM and a variant of ELM as base classifier. This variant of ELM differs from ELM as it uses sigmoid activation function at output layer to get probabilistic outcome for each class. The result shows that the Un-weighted class specific soft voting based ensemble performs better than majority voting based ensemble.

Keywords—Ensemble Pruning; Extreme learning Machine; soft voting, probabilistic output.

10. Paper 28021541: An Analysis of Various Algorithms For Text Spam Classification and Clustering Using RapidMiner and Weka (pp. 66-74)

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Zainal K., Faculty of Science & Technology, Islamic Science University of Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia

Sulaiman N.F., Faculty of Science & Technology, Islamic Science University of Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia

Jali M.Z., Faculty of Science & Technology, Islamic Science University of Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia

Abstract — This paper reported and summarized findings of spam management for Short Message Service (SMS) which consists of classification and clustering of spam using two different tools, namely RapidMiner and Weka. By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. From the simulation, both tools giving the similar results that the same classifiers are the best for SMS spam classification and clustering which are outperformed than other algorithms.

Keywords- SMS spam; RapidMiner; Weka; Naïve Bayesian (NB); Support Vector Machine (SVM); k-Nearest Neighbour (kNN); K-Mean; Cobweb; Hierarchical clustering; spam classification; spam clustering.

11. Paper 28021543: Security Architecture with NAC using Crescent University as Case study (pp. 75-78)

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Ayangbekun Oluwafemi J., Department of Information Systems, University of Cape Town, Cape Town, South Africa

Audu Zainab O., Department of Computer Science, Crescent University Abeokuta, Ogun State, Nigeria.

Abstract — A campus network implemented for a university is a medium for effective communication in such environment. The major advantage of having such network is the shared nature of resources and mobile nature of students, teachers and administrators. This research based on the low level of network capacity in Crescent University taking into consideration applying NAC and some selected protocols over both wired and wireless network. Star topology was employed to design the network, a network with centralized server because of the size of the school and the limitations it might encounter if other forms of technologies are deployed, as illustrated in the diagrams. Programmable switches was used to illustrate how the virtual devices and endpoint devices can be used to handle security threats. The use of Wired Equivalent Privacy (WEP) or WPA (Wi-fi Protected Access) which is a security algorithm for IEEE 802.11 wireless networks and other protocols for wired devices to target security challenges. As new ways to improve and achieve goals in a university is increasing, using modern technologies has made learning and teaching easier in which few universities have successfully adopted a standard networking model across Africa.

Keywords- Network Access Control (NAC), Switch, campus network, protocols

12. Paper 28021544: A Survey: Multimodal Systems of Finger vein and Iris (pp. 79-83)

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Priyam Kaur Sandhu, CSE Department, PEC University of Technology, Chandigarh, India

Manvjeet Kaur CSE Department, PEC University of Technology, Chandigarh, India

Abstract — Biometric systems are the systems those enable automatic individual recognition which is based on behavioral or physical features belonging to a specific individual. All the biometric features have their limits to an extent and no biometric system is flawless. Therefore, the unimodal biometric systems have a lot of drawbacks. To solve the mentioned inconvenience and limitations and to enhance the level of security the multimodal biometric systems are employed. Personal identification process is a very important process that resides a large portion of daily usages. Human is a rich subject having many features that can be used for identification purpose such as finger vein, iris, and face etc. Finger vein recognition is an encouraging biometric recognition technique; the verification of individuals is done on the basis of the vein patterns present in the fingers. Iris recognition has moved under more focus due to its high reliability and efficiency in personal identification in past few years. This paper discusses the advantages of multimodal biometric system over unimodal biometric system along with the fusion of traits using different techniques. It also discusses the techniques employed on finger vein and iris. Finally, future scope is presented for the possible work that can be done in the field of finger vein and iris.

Keywords- finger vein; iris; PCA; multimodal; unimodal

13. Paper 30011503: Embedded Mobile Agent (EMA) for Distributed Information Retrieval (pp. 84-89)

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Oguntunde B.O, Department of Computer Science, Redeemer’s University, Ede, Osun State, Nigeria

Osofisan A.O, Department of Computer Science, University of Ibadan, Ibadan, Oyo State, Nigeria.

Aderounmu G.A, Department of Computer Science and Engineering, Obafemi Awolowo university, Ile-ife, Osun State, Nigeria

Abstract — Mobile agent paradigm has been recognised as a viable approach for building distributed applications. Mobile agents migrate through the network, execute asynchronously and autonomously, conserve bandwidth, achieve better load balancing, adapt dynamically to changes in their environment, are robust and fault tolerant. Existing agents run and execute on agent platforms also called, the Mobile Agent System (MAS), which provides run-time execution and support facilities for mobile agent to accomplish it tasks. These MASs from different vendors are different in language, design, and implementation and are not interoperable, this impedes the achievement of the full potentials of mobile agent paradigm. This work is aimed at providing a robust structure for deploying mobile agents so they can execute independent of the MAS. We propose a lightweight agent to run in the kernel mode of the operating system as an operating system service, giving an impression of the agent directly communicating with the operating systems.

Keywords- embedded mobile agent, operating system service, lightweight agent, agent platform.

14. Paper 30011517: Fraudulent Electronic Transaction Detection Using Dynamic KDA Model (pp. 90-99)

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Massoud Vadoodparast, Prof. Abdul Razak Hamdan, Dr. Hafiz

Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia , 43600, UKM Bangi, Selangor, Malaysia

Abstract – Clustering analysis and Data mining methodologies were applied to the problem of identifying illegal and fraud transactions. The researchers independently developed model and software using data provided by a bank and using Rapidminer modeling tool. The research objectives are to propose dynamic model and mechanism to cover fraud detection system limitations. KDA model as proposed model can detect 68.75% of fraudulent transactions with online dynamic modeling and 81.25% in offline mode and the Fraud Detection System & Decision Support System. Software proposes a good supporting procedure to detect fraudulent transaction dynamically.

Keywords-component; Fraud detection, Data Mining, Clustering techniques, Decision Support System

15. Paper 28021512: Comparison between C++ console and graphic programming (pp. 100-107)

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Zhengyu Lu, Department of Computer Science, Jilin University, China, Jilin Province, China

Dimitar Pilev, Department of Informatics, Chemical Technology and Metallurgy in Sofia, Sofia, Bulgaria

Abstract - Nowadays, the new students of Computer Science learn programming starting with C or C++ in the black-white console. At first, they may feel very proud of themselves by calculating or print the result on the Screen. As time goes by, they may feel tired of the black-white box and prefer something new. Then the problem comes, they should learn the basic C++ code by heart or just skip it to the graphic programming which sometimes seems more interesting than black-white console programming. And after the Graphic programming like MFC, CLR programming, we can even release the program and make it a small software that can be set up in their own laptop. It is really more interesting. So we will look at one example that we build the program through console and released-version graphic programming to see the difference and disadvantages and advantages of them.

Keywords-C++; Console programming; Graphic programming; Comparison;