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ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
Core Subject : Science, Engineering,
Computer Science & IT Engineering
ComEngApp-Journal (Collaboration between University of Sriwijaya, Kirklareli University and IAES) is an international forum for scientists and engineers involved in all aspects of computer engineering and technology to publish high quality and refereed papers. This Journal is an open access journal that provides online publication (three times a year) of articles in all areas of the subject in computer engineering and application. ComEngApp-Journal wishes to provide good chances for academic and industry professionals to discuss recent progress in various areas of computer science and computer engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 4 No 2 (2015)" : 5 Documents clear
Network Attacks Detection by Hierarchical Neural Network Mohammad Masoud Javidi; Mohammad Hassan Nattaj
Computer Engineering and Applications Journal Vol 4 No 2 (2015)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.132 KB) | DOI: 10.18495/comengapp.v4i2.108

Abstract

Intrusion detection is an emerging area of research in the computer security and net-works with the growing usage of internet in everyday life. Most intrusion detection systems (IDSs) mostly use a single classifier algorithm to classify the network traffic data as normal behavior or anomalous. However, these single classifier systems fail to provide the best possible attack detection rate with low false alarm rate. In this paper,we propose to use a hybrid intelligent approach using a combination of classifiers in order to make the decision intelligently, so that the overall performance of the resul-tant model is enhanced. The general procedure in this is to follow the supervised or un-supervised data filtering with classifier or cluster first on the whole training dataset and then the output are applied to another classifier to classify the data. In this re- search, we applied Neural Network with Supervised and Unsupervised Learning in order to implement the intrusion detection system. Moreover, in this project, we used the method of Parallelization with real time application of the system processors to detect the systems intrusions.Using this method enhanced the speed of the intrusion detection. In order to train and test the neural network, NSLKDD database was used. Creating some different intrusion detection systems, each of which considered as a single agent, we precisely proceeded with the signature-based intrusion detection of the network.In the proposed design, the attacks have been classified into 4 groups and each group is detected by an Agent equipped with intrusion detection system (IDS).These agents act independently and report the intrusion or non-intrusion in the system; the results achieved by the agents will be studied in the Final Analyst and at last the analyst reports that whether there has been an intrusion in the system or not. Keywords: Intrusion Detection, Multi-layer Perceptron, False Positives, Signature- based intrusion detection, Decision tree, Nave Bayes Classifier
Parallel Continuous Double Auction for Service Allocation in Cloud Computing Nima Farajian; Hossein Ebrahim pour-komleh
Computer Engineering and Applications Journal Vol 4 No 2 (2015)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.261 KB) | DOI: 10.18495/comengapp.v4i2.125

Abstract

Cloud Computing is a service oriented architecture in which every computing resources is delivered to users as a service. Nowadays market-oriented approach has attracted a lot of researchers because of its great ability to manage Cloud services efficiently and dynamically. Each service consists of various resources which all should be allocated to utilize the service. In this paper a parallel continuous double auction method for efficient service allocation in cloud computing is presented in which by using a novel parallel sorting algorithm at auctioneer, enables consumers to order various resources as workflow for utilizing requested services efficiently. Also in the presented method consumers and providers make bid and offer prices based on time factor. Experimental results show that proposed method is efficient in success rate, resource utilization and average connection time and also overall performance of system is improved by parallel approach.
Energy efficient virtual machine placement algorithm with balanced resource utilization based on priority of resources Amin Rahimi; Leili Mohammad Khanli; Saeid Pashazadeh
Computer Engineering and Applications Journal Vol 4 No 2 (2015)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1032.969 KB) | DOI: 10.18495/comengapp.v4i2.134

Abstract

The increasing energy consumption has become a major concern in cloud computing due to its cost and environmental damage. Virtual Machine placement algorithms have been proven to be very effective in increasing energy efficiency and thus reducing the costs. In this paper we have introduced a new priority routing VM placement algorithm and have compared it with PABFD (power-aware best fit decreasing) on CoMon dataset using CloudSim for simulation. Our experiments show the superiority of our new method with regards to energy consumption and level of SLA violations measures and prove that priority routing VM placement algorithm can be effectively utilized to increase energy efficiency in the clouds.
Proposing a novel method for clock synchronization by Reducing the Number of Synchronization Messages and Eliminating Non-Deterministic Errors in Wireless Sensor Network Seyed Kazem Kazeminezhad; Shahram Babaie; Amir Shiri
Computer Engineering and Applications Journal Vol 4 No 2 (2015)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (354.167 KB) | DOI: 10.18495/comengapp.v4i2.137

Abstract

Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.
Fingerprint Enhancement Algorithm Based-on Gradient Magnitude for the Estimation of Orientation Fields Saparudin Saparudin; Ghazali Sulong
Computer Engineering and Applications Journal Vol 4 No 2 (2015)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (715.022 KB) | DOI: 10.18495/comengapp.v4i2.154

Abstract

An accurate estimation of fingerprint orientation fields is an important step in the fingerprint classification process. Gradient-based approaches are often used for estimating orientation fields of ridge structures but this method is susceptible to noise. Enhancement of fingerprint images improves the ridge-valley structure and increases the number of correct features thereby conducing the overall performance of the classification process. In this paper, we propose an algorithm to improve ridge orientation textures using gradient magnitude. That algorithm has four steps; firstly, normalization of fingerprint image, secondly, foreground extraction, thirdly, noise areas identification and marking using gradient coherence and finally, enhancement of grey level. We have used standard fingerprint database NIST-DB14 for testing of proposed algorithm to verify the degree of efficiency of algorithm. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with other methods.

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