Ponpat Phetchai, Jema David Ndibwile, Doudou Fall, S. Kashihara, Suppawong Tuarob
{"title":"Securing Low-Computational-Power Devices Against ARP Spoofing Attacks Through a Lightweight Android Application","authors":"Ponpat Phetchai, Jema David Ndibwile, Doudou Fall, S. Kashihara, Suppawong Tuarob","doi":"10.1109/ICSEC.2017.8443953","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443953","url":null,"abstract":"ARP spoofing is one of the most common attacks in the network and it has been around for quite some time. It is one of the simplest attacks to launch and most difficult to defend. The attacking simplicity is due to ARP stateless nature, i.e., lacks an ARP reply authentication for a subsequent request. Moreover, the attack is convenient because of the vast amount of free online spoofing tools. Many solutions have been developed to address this issue; however, most of them suffer from a single point of failure (SPOF), high-computational overhead and unsuitability for low-computational-power devices such as smartphones. In this paper, we propose a solution for protecting those devices from the ARP spoofing attacks. Our solution is lightweight, scalable and immune to SPOF. The solution is fundamentally based on the followed concept: a legitimate ARP cache mapping of a device is replicated and saved to a secure long-term application memory, then later it periodically checks against the ARP cache map to determine the alteration and alert the user, so that appropriate actions can be taken. The results of our experiment show that the proposed solution significantly prevents the ARP spoofing attacks with a low-computational overhead on mobile devices while consuming less than 0.60% and 7.83% memory and CPU usage respectively.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126831464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Loss Reconfiguration for Distribution Network System","authors":"N. N. Yin, M. Thuzar, E. Thwe","doi":"10.1109/ICSEC.2017.8443899","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443899","url":null,"abstract":"Nowadays, the electricity demand is increasing daily so it is important not only to extract electrical energy from all possible new power resources but also to reduce power losses to an acceptable minimum level in the existing distribution networks where a huge amount of power dissipation occurred. The feeder reconfiguration problem highly nonlinear with multi objective and multiple constraints. The feeder reconfiguration is chosen by the on/off status of the switches in a distribution network in order to meet one or more objective such as power loss or cost or voltage regulation. An iterative algorithm is proposed by using ETAP 12.6 software in this paper, which follows an ac optimal power flow problem. The proposed method is tested on radial distribution system in Naypyitaw City, Pyinmana Township, where long-length, overloaded lines and high level of power dissipation is occurred in this system. According to simulation results of load flow analysis, voltage profile enhancement and power loss reduction for proposed system are revealed in this paper. The simulation results show that the voltage regulation is power losses.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122772729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Atom-Task Precondition Technique to Optimize Large Scale GUI Testing Time based on Parallel Scheduling Algorithm","authors":"Supaket Wongkampoo, S. Kiattisin","doi":"10.1109/ICSEC.2017.8443913","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443913","url":null,"abstract":"The modern software development mostly aims to reduce a development time. The product time to market must be fast for quick gathering feedback from the user. DevOps brings the continuous practice to improve software development process on both continuous integration and continuous delivery. In continuous processes, software testing is the most time-consuming part which significant for overall process especially graphic user interface or GUI. Several techniques can reduce GUI testing time such as a distributed testing which is help UI testing running in parallel on a distributed machine. By running distributed GUI testing initially without experience or knowledge from an expert lead to the un-optimized speed of running test or even the future problem such as an unpredictable number of worker, the bottleneck of the worker node. This paper has purpose the Atom-Task precondition technique, the technique for filtering the test before running the parallel testing process to optimize the testing time and avoiding worker bottleneck problem and also remain an ability to scale the worker process for desired testing time with predictable resource for large-scale testing in the distributed environment.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133446764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Fast Convolutional Denoising Autoencoder Based Extreme Learning Machine","authors":"Janebhop Sawaengchob, Punyaphol Horata, Pakarat Musikawan, Yanika Kongsorot","doi":"10.1109/ICSEC.2017.8443962","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443962","url":null,"abstract":"The convolutional autoencoder (CAE) was proposed on convolutional neural network (CNN) and denoising autoencoder (DAE). CAE can address the corrupted input samples and high dimensional problem. However, CAE has a shortcoming involving a large training timescale because the parameters of network are commonly tuned by gradient descent (GD) learning method. In order to alleviate this problem, this paper proposed a fast convolutional denoising autoencoder based extreme learning machine (ELM), called fast convolutional denoising autoencoder (FCDA). In FCDA, the random convolutional hidden nodes are used to reduce the dimension of input data. After that, the proposed denoising ELM autoencoder is used to reconstruct the cleaned data. The experimental results indicate that the proposed method not only speeds up the traditional CAE, but it also outperforms the CAE algorithm in terms of reconstruction error. Moreover, we applied the proposed method FCDA as the pre-processing method for ML-ELM classifier. The results illustrate the combination of the proposed FCDA, and ML-ELM achieves the classification performance better than the comparative methods.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133646510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic Topic Clustering Using Latent Dirichlet Allocation with Skip-Gram Model on Final Project Abstracts","authors":"Hendra Bunyamin, Lisan Sulistiani","doi":"10.1109/ICSEC.2017.8443795","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443795","url":null,"abstract":"Topic model has been an elegant method to discover hidden structures in knowledge collections, such as news archives, blogs, web pages, scientific articles, books, images, voices, videos, and social media. The basic model of topic model is Latent Dirichlet Allocation (LDA) and this paper utilizes LDA to automatically cluster topics from final project abstract collection. We compare two methods, that are LDA as a unigram model and LDA with Skip-gram model. Our results are evaluated by an expert on readily available categories. Overall, words from each topic are indeed keywords describing each topic; moreover, the combination of LDA and skip-gram model are capable to capture key phrases from each topic.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128901164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extension of Quadratic Means for Weighted Centroid Localization with ZigBee Technology","authors":"Kantaphon Torat, S. Promwong","doi":"10.1109/ICSEC.2017.8443933","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443933","url":null,"abstract":"Wireless indoor communications, the mobile robot tracking is the one of application in wireless sensor networks (WSNs). A one of promising localization algorithm in range-free algorithm is the weighted centroid algorithm (WCA). This work proposed the improved WCA with quadratic means based on received signal strength (RSS). The ZigBee operated at 2.45 GHz frequency was used to measure in the indoor environment. The results are discuss about the comparison of the typically WCA and the improved WCA. From the results, The 1 m. precision of improved WCA is 92% and WCA is 83%. Besides that, the improved WCA obtained the 17% no error estimated position.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124212135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Zikky, R. Hakkun, Ahmad Farizi Ainun Rizqi, Abdulloh Hamid, A. Basuki
{"title":"Development of Educational Game for Recognizing Indonesian Sign Language (SIBI) and Breaking Down the Communication Barrier with Deaf People","authors":"M. Zikky, R. Hakkun, Ahmad Farizi Ainun Rizqi, Abdulloh Hamid, A. Basuki","doi":"10.1109/ICSEC.2017.8443936","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443936","url":null,"abstract":"Born with physical limitations doesn't necessarily have to be different with the normal people in doing daily activities. The emersion of technology should have role as a bridge to the gaps that appears between people with disability and the normal one including the process of interaction and play games. This paper presents result of the research related to the development of game applications to educate society in providing basic understanding of Indonesian Sign Language / Sistem Isyarat Bahasa Indonesia (SIBI). SIBI is commonly used by the deaf and the mute people as the standard language in interacting with others. Gamers will be presented some questions or cases related with the basic things of sing language, then they have to answer with SIBI hand's gesture. From this activity, the players are not only playing but also learning the proper SIBI language. The players' sign language answer will be captured by the leap motion sensor, leap motion will be capturing the hand gestures and matching it with the SIBI dataset that has been created and stored. The game will be arranged with good levelling so that the improvement of SIBI learning can be measured properly","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123691487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"DVB-T2 Transmission Model in Bangkok Thailand with 626 MHz for DTT","authors":"A. Chaisang, S. Promwong","doi":"10.1109/ICSEC.2017.8443882","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443882","url":null,"abstract":"Digital television terrestrial (DTT) of Thailand used digital video broadcasting terrestrial 2nd generation (DVB-T2). The DVB-T2 transmission loss should be knowing and study. However the DVB-T2 propagation channels performance is very importance for Thailand. This paper evaluation of DVB-T2 propagation channel base on measurement data. In the experimental study of DVB-T2 propagation channel in Bangkok environment for DTT network for portable in urban areas in Bangkok Thailand at MCOT channel 40 at the frequency 626MHz. In these results to evaluate the power loss, probability density function (pdf), commutative distribution function (cdf).","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121923095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manil Vaidhya, B. Shrestha, Bishal Sainju, Kiran Khaniya, Aman Shakya
{"title":"Personality Traits Analysis from Facebook Data","authors":"Manil Vaidhya, B. Shrestha, Bishal Sainju, Kiran Khaniya, Aman Shakya","doi":"10.1109/ICSEC.2017.8443932","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443932","url":null,"abstract":"There has been an exponential increase in social media users and the amount of time they spend on various social sites such as Facebook. As the users interact in these sites, they reveal a lot about their characteristics in the form of profile description and status updates. This paper describes a system to analyze and predict the personality traits of facebook users using their status updates. KNN and SVM learning algorithms were used for personality classification. The well established Big Five personality model was used for the personality traits analysis. Five different models for each of the personality dimensions (Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism) were created and after the models were trained and their parameters fine tuned, these models were used to predict the personality in the form of a rating from 1 to 5. An online Facebook application has been developed to analyze the status texts of users and suggest their personality trait scores.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129525376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analyzing SQL Injection Statements Using Common Substructure of Parse Tree","authors":"Warradorn Sirisang, V. Suttichaya","doi":"10.1109/ICSEC.2017.8443774","DOIUrl":"https://doi.org/10.1109/ICSEC.2017.8443774","url":null,"abstract":"This paper proposes a SQL injection detection method by analyzing substructure of SQL statement. The proposed method consists of 2 parts, Automated Common Substructure Extracting (ACSE) and Parse Tree Substructure Matching (PTSM). ACSE attempts to extract the duplicated substructures that appear in parse trees of SQL injection statements. PTSM uses the extracted parse tree from ACSE for identifying malicious portions in user's input statements. It also calculates the similarity between the common substructure and input statements. Experimental results show that the proposed method gains an accuracy greater than 90 percent.","PeriodicalId":111111,"journal":{"name":"2017 21st International Computer Science and Engineering Conference (ICSEC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129680799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}