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2020 7th NAFOSTED Conference on Information and Computer Science (NICS)最新文献

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Physical Layer Security in Multi-hop Relay Networks with Modified Dijkstra's Routing Algorithms 改进Dijkstra路由算法的多跳中继网络物理层安全性
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335844
Nguyen Thi Yen Linh, C. Thai, Vo Nguyen Quoc Bao, Huynh Van Hoa
{"title":"Physical Layer Security in Multi-hop Relay Networks with Modified Dijkstra's Routing Algorithms","authors":"Nguyen Thi Yen Linh, C. Thai, Vo Nguyen Quoc Bao, Huynh Van Hoa","doi":"10.1109/NICS51282.2020.9335844","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335844","url":null,"abstract":"The paper studies the physical layer security in multi-hop relay networks with multiple relaying nodes in which two of decode-and-forward (DF) scheme and decode-and- forward and amplify-and-forward (DFAF) scheme are considered. In the schemes, we also consider the presence of an eavesdropper overhearing in the transmission. In addition, we propose a novel algorithm for all of two schemes to find the best route networks from the source to the destination. The routes have to guarantee that the total transmission time is the smallest and the accumulated trust degrees (TD) is larger than a given trust degree threshold. To evaluate the system performance, we analyze the successful delivery ratio (SDR), the average delivery time (ADT) and the average number of regenerative hops (ANRH) for all two schemes. The numerical results show that the system performance of DFAF scheme is better than that of DF scheme due to the better secrecy rate.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133615840","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
DDoS attack detection and defense in SDN based on machine learning 基于机器学习的SDN DDoS攻击检测与防御
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335867
Tan-Khang Luong, Trung-Dung Tran, Giang-Thanh Le
{"title":"DDoS attack detection and defense in SDN based on machine learning","authors":"Tan-Khang Luong, Trung-Dung Tran, Giang-Thanh Le","doi":"10.1109/NICS51282.2020.9335867","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335867","url":null,"abstract":"Distributed Denial of Service (DDoS) attack is one of the most dangerous threats in computer networks. Hence, DDoS attack detection is one of the key defense mechanisms. In this paper, we propose a DDoS detection and defense approach in Software Defined Network (SDN) systems based on machine learning (ML) and deep neural network (DNN) models. The combination of ML and DNN classifiers with the centralized factors of SDN can efficiently mitigate the harmful effect of DDoS to the network system. Besides, we conducted two types of attack scenarios, one is from inside and one is from outside of the network system.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132648708","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
Mining and Creating a Software Repositories Dataset 挖掘和创建软件存储库数据集
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335894
Thai-Bao Do, Huu-Nghia H. Nguyen, Bao-Linh L. Mai, Vu Nguyen
{"title":"Mining and Creating a Software Repositories Dataset","authors":"Thai-Bao Do, Huu-Nghia H. Nguyen, Bao-Linh L. Mai, Vu Nguyen","doi":"10.1109/NICS51282.2020.9335894","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335894","url":null,"abstract":"Mining software repositories to extract meaningful information from them has become an important topic in software engineering. This paper presents our study to mine a very large dataset consisting of over three million software repositories across many version control systems and create derived data for future studies. Through this study, we propose a method for detecting forks and duplicates in repositories. We also preliminarily investigate the possible correlations between forking patterns, software health and risks, and success indicators.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122491209","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
Vietnamese Facebook Posts Classification using Fine-Tuning BERT 使用微调BERT对越南Facebook帖子进行分类
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335865
Dung Tran Tuan, Dang Van Thin, V. Pham, N. Nguyen
{"title":"Vietnamese Facebook Posts Classification using Fine-Tuning BERT","authors":"Dung Tran Tuan, Dang Van Thin, V. Pham, N. Nguyen","doi":"10.1109/NICS51282.2020.9335865","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335865","url":null,"abstract":"With the development of social networks in the age of information technology explosion, the classification of social news plays an important role in detecting the hot topics being discussed on social networks over a period of time. In this paper, we present a new model for effective Facebook's posts classification and a new dataset which is labeled for the corresponding subject. The dataset consists of 5191 Facebook user's public posts, which is divided into 3 subsets: training, validation and testing data sets. Then, we explore the effectiveness of fine-tuning BERT model with three truncation methods compared with other machine learning algorithms on our dataset. Experimental results show that the fine-tune BERT models outperform other approaches. The fine-tune BERT with “head + tail” truncation methods achieves the best scores with 84.31% of Precision, 84.12% of Recall and 84.15% of F1-score.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122613564","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
[Copyright notice] (版权)
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/nics51282.2020.9335900
{"title":"[Copyright notice]","authors":"","doi":"10.1109/nics51282.2020.9335900","DOIUrl":"https://doi.org/10.1109/nics51282.2020.9335900","url":null,"abstract":"","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127609722","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
A Study of Finger Movement Classification Based On 2-sEMG Channels 基于2-表面肌电信号通道的手指运动分类研究
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335895
T. L. Thi, Phuc Viet Ho, Tuan Van Huynh
{"title":"A Study of Finger Movement Classification Based On 2-sEMG Channels","authors":"T. L. Thi, Phuc Viet Ho, Tuan Van Huynh","doi":"10.1109/NICS51282.2020.9335895","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335895","url":null,"abstract":"Electromyography signals are highly valuable bioelectric signals in diagnosing abnormal nerve and muscle problems. Besides, in recent decades, processing and classification of EMG signals has become a core issue in prosthetic control applications. The focus of this study is an investigation into individual and combined fingers movement recognition using surface EMG signals. The dataset was used belongs to ten different classes collected from ten subjects. There are several sequential steps obtained to analysis EMG signals in this paper (i.e. preprocessing, feature extraction, feature reduction, pattern recognition). At first, EMG signals have been segmented by the windowing process. After that, various feature sets were extracted from these segments. Feature vectors were then reduced by applying two different reduction methods: Principal Component Analysis and Bhattacharyya Distance. Finally, they were fed to two classifiers: Artificial Neural Network and Fuzzy Logic. Overall average classification accuracies of these two systems were 96.08(±0.9)% and 90.56(±3)% respectively.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127420855","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
Facial Expression Recognition in the Wild: Efficiency of Modified-Category and Ensemble Learning Methods 野外面部表情识别:修改类别和集成学习方法的效率
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335879
Bao Bui-Xuan, Bao-Minh Nguyen-Hoang, Cong-Anh Truong, Quang-Duy Nguyen-Tran
{"title":"Facial Expression Recognition in the Wild: Efficiency of Modified-Category and Ensemble Learning Methods","authors":"Bao Bui-Xuan, Bao-Minh Nguyen-Hoang, Cong-Anh Truong, Quang-Duy Nguyen-Tran","doi":"10.1109/NICS51282.2020.9335879","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335879","url":null,"abstract":"Human facial expression plays a significant role in the medical field, the automotive industry, and so on. Recent research and achievements in recognizing the expressions by using CNNs have been published, conducted on old datasets, i.e. CKP, FER+, etc. However, those are unnatural and less challenging. We authors propose two methods to deal with a new and more realistic dataset called CAER-S first introduced in ICCV 2019. Instead of using the original images of CAER-S, we prepare our dataset by extracting the faces to focus mainly on facial expressions. The first method is to merge some categories sharing the most mispredictions mutually. Nonetheless, the results are indecisive to conclude this method's efficiency. The other is to use plenty of pre-trained models to find the best three of them for ensembles. The ensembles are weighted majority voting and soft voting. These are applied to fuse the three models' results to return the final one whose accuracy is higher than each's separately. This work contributes to advanced facial expression recognition research, especially with using the new dataset CAER-S.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126861056","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
Papers by title 论文标题
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/nics51282.2020.9335873
{"title":"Papers by title","authors":"","doi":"10.1109/nics51282.2020.9335873","DOIUrl":"https://doi.org/10.1109/nics51282.2020.9335873","url":null,"abstract":"","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129702876","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
Vehicle Detection at Night Time 夜间车辆探测
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335870
Ngoc Ho, Mai Pham, Nguyen D. Vo, Khang Nguyen
{"title":"Vehicle Detection at Night Time","authors":"Ngoc Ho, Mai Pham, Nguyen D. Vo, Khang Nguyen","doi":"10.1109/NICS51282.2020.9335870","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335870","url":null,"abstract":"Recent growth in deep learning has opened up many opportunities for the problem of vehicle detection. Detecting objects in poor visibility is catching scientists attention. In this study, we choose night as the challenge. We conducted training and evaluation of the YOLOv4 method in combination with image preprocessing methods: gamma, CycleGAN's night-day conversion model was retrained on DETRAC data. Night dataset (26,168 images) extracted from DETRAC were used. The results showed that the training on the primitive data is highly effective (64.51%mAP) compared to the image changed from night to day, particularly on the car class (92%AP), bus (91%AP). This is the premise for the next studies and the basis to develop intelligent traffic monitoring systems.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132340616","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: 5
Deep reinforcement learning based socially aware mobile robot navigation framework 基于深度强化学习的社交感知移动机器人导航框架
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335911
Nam Thang Do, T. Pham, Nguyen Huu Son, T. Ngo, Xuan-Tung Truong
{"title":"Deep reinforcement learning based socially aware mobile robot navigation framework","authors":"Nam Thang Do, T. Pham, Nguyen Huu Son, T. Ngo, Xuan-Tung Truong","doi":"10.1109/NICS51282.2020.9335911","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335911","url":null,"abstract":"In this study, we propose a socially aware navigation framework, which enables a mobile robot to avoid humans and social interactions in dynamic social environments, using deep reinforcement learning algorithm. The proposed framework is composed of two main stages. In the first stage, the socio-spatio-temporal characteristics of the humans including human states and social interactions are extracted and projected onto the 2D laser plane. In the second stage, these social dynamic features are then feed into a deep neural network, which is trained using the asynchronous advantage actor-critic (A3C) technique, safety rules and social constraints. The trained deep neural network is then used to generate the motion control command for the robot. To evaluate the proposed framework, we integrate it into a conventional robot navigation system, and verify it in a simulation environment. The simulation results illustrate that, the proposed socially aware navigation framework is able to drive the mobile robot to avoid humans and social interactions, and to generate socially acceptable behavior for the robot.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124591713","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
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