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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
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Exploring permissions in android applications using ensemble-based extra tree feature selection Howida Abuabker Alkaaf; Aida Ali; Siti Mariyam Shamsuddin; Shafaatunnur Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp543-552

Abstract

The fast development of mobile apps and its usage has led to increase the risk of exploiting user privacy. One method used in Android security mechanism is permission control that restricts the access of apps to core facilities of devices. However, that permissions could be exploited by attackers when granting certain combinations of permissions. So, the aim of this paper is to explore the pattern of malware apps based on analyzing permissions by proposing framework utilizing feature selection based on ensemble extra tree classifier method and machine learning classifier. The used dataset had 25458 samples (8643 malware apps & 16815 benign apps) with 173 features. Three dataset with 25458 samples and 5, 10 and 20 features respectively were generated after using the proposed feature selection method. All the dataset was fed to machine learning. Support Vector machine (SVM), K Neighbors Classifier, Decision Tree, Naïve bayes and Multilayer Perceptron (MLP) classifiers were used. The classifiers models were evaluated using true negative rate (TNR), false positive rate (FNR) and accuracy metrics. The experimental results obtained showed that Support Vector machine and KNeighbors Classifiers with 20 features achieved the highest accuracy with 94 % and TNR with rate of 89 % using KNeighbors Classifier. The FNR rate is dropped to 0.001 using 5 features with support vector machine (SVM) and Multilayer Perceptrons (MLP) classifiers. The result indicated that reducing permission features improved the performance of classification and reduced the computational overhead.
Face Tracking Based on Particle Filter with Multi-feature Fusion Zhiyu Zhou; Dichong Wu; Xiaolong Peng; Zefei Zhu; Chuanyu Wu; Jinbin Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Traditional particle filter cannot accommodate to the environment of background interferences, illumination variations and occlusions. This paper presents a face tracking method with fusion of color histogram, contour features and grey model based on particle filter. First, it brought in contour features as the main cue of multiple features when tracking the face without stable color histogram. Then, as prior information was neglected in traditional particle filter, this paper employed GM(1,1) model to yield proposal distribution, such that the proposal distribution would bear a higher approximation to posterior probability. Finally, in the importance sampling step, sampling was corresponded to the particle weight in case of the particle degradation. The experiments show that our method outperformed the previous with more accuracy and flexibility, particularly under the condition of color background interferences, drastic illumination variations and complete occlusions. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3381
Chord-based Quantum Botnet Research Wang Xin-Liang; Lu Nan; Gao Qing-Hua
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp7046-7053

Abstract

In order to make the controller better to master the botnet, the traditional chord-based botnets ensure that all adjacent nodes can maintain the periodic communication so that the routing table of every node could keep accurate and efficient. The periodic communication behavior will also increase the risk of exposure of the traditional chord-based botnets. Once one of the peers is captured by network security device, more peers will be captured based on periodic communication behavior of chord-based botnets that leads to affect the botnet robustness. For the aforementioned problems in the traditional chord-based botnet, this paper will construct a quantum botnet control platform based on the improved B92 protocol. The in-depth analysis showed that the infected hosts in the chord-based quantum botnet can more quickly be increased, and can maintain a larger scale compared with the traditional chord-based botnet. So the chord-based quantum botnet owns better robustness and stability.
Distributed Searchable Asymmetric Encryption Shoulin Yin; Lin Teng; Jie Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp684-694

Abstract

Searchable asymmetric encryption (SAE) can also be called Public Key Encryption with Keyword Search (PEKS), which allows us to search the keyword on the data of having been encrypted. The essence of Asymmetric searchable encryption is that users exchange the data of encryption, one party sends a ciphertext with key encryption, the other party with another key receives the ciphertext. Encryption key is not the same as the decryption key, and cannot deduce another key from any one of the key, thus it greatly enhances the information protection, and can prevent leakage the user's search criteria—Search Pattern. Secure schemes of SAE are practical, sometimes, however the speed of encryption/decryption in Public-key encryption is slower than private key. In order to get higher efficiency and security in information retrieval, in this paper we introduce the concept of distributed SAE, which is useful for security and can enable search operations on encrypted data. Moreover, we give the proof of security.
Survey On The Role Of IoT In Intelligent Transportation System Varun Chand H; Karthikeyan J
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp936-941

Abstract

Precise and appropriate traffic related data allows travellers to choose suitable travelling modes, travelling paths, and departure time, which is crucial for the success of Intelligent Transportation System (ITS). With the growth of vehicles, the rate of pollution and consumption of fuel has increased, it also creates traffic congestions. For the recent years there has been a rapid growth in technology, which can be explored to solve traffic issues. However, depending upon the available technologies each countries ITS research area may be different. The objective of this literature review is to integrate ITS with internet of things and it also discusses the prospect of clustering, controller system, location identification and resource privacy in ITS.
Indonesian news classification using convolutional neural network Muhammad Ali Ramdhani; Dian Sa’adillah Maylawati; Teddy Mantoro
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1000-1009

Abstract

Every language has unique characteristics, structures, and grammar. Thus, different styles will have different processes and result in processed in natural language processing (NLP) research area. In the current NLP research area, data mining (DM) or machine learning (ML) technique is popular, especially for deep learning (DL) method. This research aims to classify text data in the Indonesian language using convolutional neural network (CNN) as one of the DL algorithms. The CNN algorithm used modified following the Indonesian language characteristics. Thereby, in the text pre-processing phase, stopword removal and stemming are particularly suitable for the Indonesian language. The experiment conducted using 472 Indonesian news text data from various sources with four categories: ‘hiburan’ (entertainment), ‘olahraga’ (sport), ‘tajuk utama’ (headline news), and ‘teknologi’ (technology). Based on the experiment and evaluation using 377 training data and 95 testing data, producing five models with ten epoch for each model, CNN has the best percentage of accuracy around 90,74% and loss value around 29,05% for 300 hidden layers in classifying the Indonesian News data.
Automatic moving foreground extraction using random walks Idir Boulfrifi; Khalid Housni; Abdelaziz Mouloudi
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp511-516

Abstract

In this paper, we propose a novel approach for automatic foreground extraction in video frames by analyzing the spatiotemporal aspect. We divide our contribution to tree steps: Automatic seeds detection, formulating the energy function, and using the random walk algorithm to minimize this function. First, we detect seeds by extracting a sparse of good features to track in the current frame and compute the difference between those pixels and its adjacent in the previous frame, the difference of pixels is treated in HSV color space to make the result more accurate, we thresholds this difference, and we classify moving and stationary pixels. Secondly, we formulate our foreground extraction as a graph based problem, then we define an energy function to evaluate spatiotemporal smoothness. Finally, we applied the random walk algorithm with seeds detected in the first step to minimize the energy function problem, the solution leads to evaluate the potential that every pixel in the video sequences is marked in motion or a stationary pixel. We suggest that our unsupervised method has the potential to be used for many kinds of motion detection and real-time video.
Competitive intelligence: Leaven of a New Managerial Device for Decision Support Salima El Fadili; Firdaous Gmira
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp167-175

Abstract

In a highly competitive environment saturated in information traversing the earth in nanosecond, the major challenge for companies is to have the right information at the right time, to exploit it and transform it into useful organizational knowledge for strategy formulation and decision-making. Nowadays, several management practices have been developed and designed to cope with the complexity that exists in the business environment and to maintain a sustained competitive advantage. Competitive intelligence is one of these innovative strategic management practices that play an increasingly important role in decision-making. This article attempts to present an overview of its fundamental concepts, functions and process and to explain how information is utilized in supporting decision-making process. The findings of this research suggest that decision makers should focus on developing competitive intelligence process in their organizations. This paper falls under a research task that was not confronted yet with the test of the terrain survey.
An Improved Apriori Algorithm for Association Rules Xingli Liu; Huali Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 11: November 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

According Apriori algorithm characteristic achieve its improvement and apply it to the knowledge correlation of the curriculum in sumulation experiment. Firstly, it is mainly by simplifying the binary storage method to change data in the database, and then to get the largest frequent itemsets.The experiment results showed that the improved algorithm obviously improve the efficiency ;secondly ,establish a new database to simulate applied experiment ,consisted of student achievement of various knowledge points in the computer programming course,and then using this optimized algorithm to found the course knowledge frequent itemsets in a database, which is closely interrelated knowledge points mainly by setting up different minimum support value to get various frequent itemsets .According to these frequent itemsets of the course it can be applied to reestablish a new course knowledge system to further improve the teaching quality, this method can also be achieved the knowledge system reform of other course or course group.  DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3491 
Visualization Analysis of Dynamic Evolution of the Theme in Improvisation Studies Peng-bin Gao; Weiwei Wu; Bo Yu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The field of improvisation is composed of a multiplicity of topics leading to a vast array of management literature. However, the research does not provide a chronological picture of the topics it addresses, making it difficult to develop an overview of the evolution and trends in the literature. To address this issue, co-word analysis was employed to reveal patterns and trends in the improvisation field by measuring the association strengths of keywords of relevant documents. Data were collected from Web of Knowledge database for the period 1997-2012. Using the co-occurrence matrix of keywords, the results of multivariate statistical techniques show that the improvisation research involves many fields including innovation, strategy, learning, change, leadership, metaphor, entrepreneurship, capability.In order to trace the dymamic changes of the improvisation field, the whole period was further separated into three periods: 1997-2002, 2003-2007 and 2008-2012. The strategic diagram and social network analysis was used to trace the dynamic changes of the improvisation research, and results show that improvisation field has some established research themes and it also changes rapidly to embrace new themes. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4927

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