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2020 RIVF International Conference on Computing and Communication Technologies (RIVF)最新文献

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Drug-Drug Interaction Extraction from Biomedical Texts via Relation BERT 基于关系BERT的生物医学文本药物-药物相互作用提取
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140783
Dinh Phuong Nguyen, T. Ho
{"title":"Drug-Drug Interaction Extraction from Biomedical Texts via Relation BERT","authors":"Dinh Phuong Nguyen, T. Ho","doi":"10.1109/RIVF48685.2020.9140783","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140783","url":null,"abstract":"There is a large number of drugs introduced every year and a number of interactions between drugs also has quick growth. As a result, biomedical texts following new drugs and interactions expand [15]. Several published studies of drug safety have revealed that drug-drug interactions (DDIs) may be detected too late, when millions of patients have already been exposed [25]. Therefore, the management of drug drug interactions is critical issue since the importance of known drug drug interaction and the giant amount of available information around them [5]. Thus, the issue creates an imperative need for the development of high-reliable automatic DDI extraction methods while manual DDI extraction is time-consuming and could lead to out-of-date information. However, the accuracy of the current automatic DDI extraction method is still insufficient for the practical application. In this research, we explore the Relation Bidirectional Encoder Representations from Transformers (Relation BERT) architecture [32] to detect and classify DDIs from biomedical texts using the DDI extraction 2013 corpus [5] and present three proposed models namely R-BERT∗, R-BioBERT1, and R-BioBERT2. From our knowledge, we are the first to investigate the potential of Relation BERT for the aim of accuracy improvement in DDI extraction. By using the state-of-the-art word representation method, three models produce macro-average F1-score of over 79%. Moreover, the accuracy of extracting Advice and Mechanism interaction achieves 90.63% and 97% respectively in terms of F1-score. The high accuracy of the model in Advice and Mechanism interaction creates motivation for wide application of automatic DDI extraction to the practice with high-reliable and humanless.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"626 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123336421","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}
引用次数: 7
Forensic analysis of TikTok application to seek digital artifacts on Android smartphone 对TikTok应用程序进行取证分析，寻找Android智能手机上的数字文物
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140739
Nghi Hoang Khoa, Phan The Duy, Hien Do Hoang, Do Thi Thu Hien, V. Pham
{"title":"Forensic analysis of TikTok application to seek digital artifacts on Android smartphone","authors":"Nghi Hoang Khoa, Phan The Duy, Hien Do Hoang, Do Thi Thu Hien, V. Pham","doi":"10.1109/RIVF48685.2020.9140739","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140739","url":null,"abstract":"Emerging with highlight features as a global phenomenon, TikTok - the international version of Douyin application in China market, is a social media video app for creating and sharing short lip-syncing. This social video platform has seen astounding growth by reaching 1.5 billion users in 2019 by capturing the cultural zeitgeist among teenage smartphone owners in unprecedented fashion. However, criminals have been paid attention to this platform where young users become the target of abusers or predators. In this paper, we introduce the forensic analysis of the artifacts left on Android phones by TikTok application. In more detail, we indicate a complete description of all the artifacts obtained in TikTok. Furthermore, by using the results discussed in the paper, an investigator can rebuild the list of followers, searching keywords, favorites, messages that have been exchanged by users. It is helpful to examine and determine which artifacts could be considered as evidence for criminal investigation on popular social networking application.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134110917","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}
引用次数: 14
Efficient Graph Classification via Graph Encoding Networks 基于图编码网络的高效图分类
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140729
Tuyen-Thanh-Thi Ho, H. Vu, H. Le
{"title":"Efficient Graph Classification via Graph Encoding Networks","authors":"Tuyen-Thanh-Thi Ho, H. Vu, H. Le","doi":"10.1109/RIVF48685.2020.9140729","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140729","url":null,"abstract":"Graph neural networks have been attracted attention in recent years due to their superior performance in many tasks including graph classification. Unlike deep networks for image data, in which deep networks can work directly on raw data, graph neural networks usually require to be thoughtfully designed to integrate topological information (via adjacency matrices) to the networks, rendering high-computational cost and complicating the networks. This paper introduces a novel framework, which first employs an effective process to convert adjacency matrices into more convenient Column Ordering Free (COF) matrices and then builds a deep network to learn high-level representations from these matrices for graph classification. Our framework is not only permutation invariant but also has computational efficiency. In particular, we show that our network achieves comparable performance with other existing graph neural networks but at least 3 times faster in speed on a set of both biological and social network benchmark datasets.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122344742","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}
引用次数: 1
IoT Malware Classification Based on System Calls 基于系统调用的物联网恶意软件分类
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140763
Kien Hoang Dang, D. Nguyen, Duy Loi Vu
{"title":"IoT Malware Classification Based on System Calls","authors":"Kien Hoang Dang, D. Nguyen, Duy Loi Vu","doi":"10.1109/RIVF48685.2020.9140763","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140763","url":null,"abstract":"IoT devices play an important role in the industrial revolution 4.0. However, this type of device may exhibit specific security vulnerabilities that can be easily exploited to cause botnet attacks and other malicious activities. In this paper, we introduce a new method for classification and clustering of IoT malware behaviors through system call monitoring. Our method is constructed from multiple one-class SVM classifiers and has the ability to classify known malware with F1-Score over 98% and probability to detect unknown malware up to 97%. Unknown malware instances with similar behaviors can also be grouped together so new classes of malware will be discovered.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128635084","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}
引用次数: 3
Measurements of errors in large-scale computational simulations at runtime 运行时大规模计算模拟中的误差测量
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140785
M. N. Dinh, Q. M. Nguyen
{"title":"Measurements of errors in large-scale computational simulations at runtime","authors":"M. N. Dinh, Q. M. Nguyen","doi":"10.1109/RIVF48685.2020.9140785","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140785","url":null,"abstract":"Verification of simulation codes often involves comparing the simulation output behavior to a known model using graphical displays or statistical tests. Such process is challenging for large-scale scientific codes at runtime because they often involve thousands of processes, and generate very large data structures. In our earlier work, we proposed a statistical framework for testing the correctness of large-scale applications using their runtime data. This paper studies the concept of ‘distribution distance’ and establishes the requirements in measuring the runtime differences between a verified stochastic simulation system and its larger-scale counterpart. The paper discusses two types of distribution distance including the χ2 distance and the histogram distance. We prototype the verification methodology and evaluate its performance on two production simulation programs. All experiments were conducted on a 20,000-core Cray XE6.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114191301","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}
引用次数: 0
Improvement of feature set based on Apriori algorithm in Android malware classification using machine learning method 基于Apriori算法的Android恶意软件分类特征集改进
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140779
Le Duc Thuan, V. H. Pham, H. Hiep, Nguyen Kim Khanh
{"title":"Improvement of feature set based on Apriori algorithm in Android malware classification using machine learning method","authors":"Le Duc Thuan, V. H. Pham, H. Hiep, Nguyen Kim Khanh","doi":"10.1109/RIVF48685.2020.9140779","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140779","url":null,"abstract":"A well-constructed feature set plays an important role in accuracy improvement in malware detection. However, research and evaluation of the relations between features to acquire a good feature set have not been received much attention. In this work, a method based on Apriori algorithm was proposed to improve the feature set. The method studies association rules from the initial feature set to devise the highly correlated and informative features, which will be added to the initial set. The improved feature set will be evaluated via cross validation test using various machine learning algorithms, such as SVM, Random forest and CNN. The accuracy of the test reached is 96.49% with 96.71% improved compared with the test using initial set.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128198080","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}
引用次数: 2
Development of the Smart Localization Techniques For Low-Power Autonomous Rover For Predetermined Environments 预定环境下小功率自动漫游车智能定位技术研究
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140741
Sachintha Balasooriya, Thanh Pham Chi, I. Kavalchuk
{"title":"Development of the Smart Localization Techniques For Low-Power Autonomous Rover For Predetermined Environments","authors":"Sachintha Balasooriya, Thanh Pham Chi, I. Kavalchuk","doi":"10.1109/RIVF48685.2020.9140741","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140741","url":null,"abstract":"Autonomous ground vehicles have become the growing research trend nowadays. One branch of this trend is development of the unmanned robots. The key challenges include sensing of the surrounding environment, position determination and path planning for the global and immediate Conditions. This paper presents the comparison between various localization and tracking technologies for low power design of an autonomous rover platform, the robot is designed with point to point travel in mind. Once the destination coordinates are given the robot travels from point A to point B with no further commands given by the operator. It has capability of determining the most efficient path to travel while avoiding collisions with its surroundings. Environment sensing is done using LIDAR rather than cameras to reduce data generation rate and the processing load. Motor encoders and potentiometers are used to solve the localization problem to achieve low power consumption in comparison with the commonly used GPS techniques and provide capabilities of operation in enclosed environments, like factories and warehouses. Developed system compares reliability and the performance of several techniques to determine the best approach for a mobile autonomous system.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"24 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127184672","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}
引用次数: 1
A Design Theory-Based Gamification Approach for Information Security Training 基于设计理论的信息安全培训游戏化方法
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140730
T. Nguyen, H. Pham
{"title":"A Design Theory-Based Gamification Approach for Information Security Training","authors":"T. Nguyen, H. Pham","doi":"10.1109/RIVF48685.2020.9140730","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140730","url":null,"abstract":"This study reviews previous information security (InfoSec) training studies and identifies three significant gaps. They are (1) lacking pedagogical theories developed specifically in IS training context, therefore, lacking appropriate pedagogical theory-based training approaches; (2) ineffectiveness of InfoSec training delivery methods due to unengaging, non-authentic security risks and training activities; and (3) and lacking an effective way of measuring effectiveness of InfoSec training. The paper proposes employing design theory as the theoretical basis for InfoSec training, and gamification as the main training and testing method to overcome these gaps. We argue that the design theory for InfoSec training associated with gamification can improve learning results for training and effectiveness testing through providing a joyful, realistic and interactive training. An action research is proposed to further evaluate the effectiveness of the approach.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125212260","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}
引用次数: 2
A Way to Estimate TCP Throughput under Low-Rate DDoS Attacks: One TCP Flow 一种估计低速率DDoS攻击下TCP吞吐量的方法:一个TCP流
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140777
M. Kieu, D. Nguyen, Thanh Thuy Nguyen
{"title":"A Way to Estimate TCP Throughput under Low-Rate DDoS Attacks: One TCP Flow","authors":"M. Kieu, D. Nguyen, Thanh Thuy Nguyen","doi":"10.1109/RIVF48685.2020.9140777","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140777","url":null,"abstract":"TCP-targeted low-rate distributed denial-of-service (LDDoS) attacks were first introduced by A. Kuzmanovic and E. Knightly in 2003. The authors also proposed a simple model to quantify TCP throughput under LDDoS attacks. Since then, there have been many researchers attemping to estimate the throughput, such as Luo et al. We agree with them upon the sketch of TCP congestion window under a successful LDDoS attack but we find out that there are more cases than what has been specified. Moreover, the relative error of Luo’s estimation method is still high. Our goal in this paper is to propose a simple but more accurate method to estimate TCP throughput of a single TCP flow under such DDoS attacks. Our estimation values in various scenarios are compared with the results of simulations performed with NS-2 simulator, so that the effectiveness of our method is illustrated.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129752148","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}
引用次数: 4
Novel ZigBee-Based Smart Anti-Theft System for Electric Bikes for Vietnam 新型基于zigbee的越南电动自行车智能防盗系统
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140758
Veerandi Kulasekara, Pasan Dharmasiri, Pham Chi Thanh, I. Kavalchuk
{"title":"Novel ZigBee-Based Smart Anti-Theft System for Electric Bikes for Vietnam","authors":"Veerandi Kulasekara, Pasan Dharmasiri, Pham Chi Thanh, I. Kavalchuk","doi":"10.1109/RIVF48685.2020.9140758","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140758","url":null,"abstract":"One of the greatest challenges for the personal vehicles owners has become the exposure to the thefts due to the technical limitations, specifically location detection accuracy, of the existing security systems. Modern positioning solutions can provide relatively accurate data, but they are required advanced communication technologies and constant access to the power source, which becomes a challenge for electric transport applications with limited energy resources. The concept of a novel smart anti-theft system, that is designed to enrich the usability of an electric bike and to inform the owner about the vehicle’s location, is presented in this paper. The developed solution herein provides the capability to perform the basic queries to determine the current location of the electric bike using Received Signal Strength Indicator (RSSI) of the Radio Frequency (RF) modules which gives the user ability to track the bike in the indoor and outdoor environments, improving personal security with the reduced power consumption in comparison with the existing technologies. An analysis of the system design along with the network architecture and the implemented approach to determine the location using ZigBee topology are discussed in the paper. Furthermore, a prototype of the system was tested, and the performance is analysed herein.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130045719","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}
引用次数: 1
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