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

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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
Right protection mechanism based on optimal robust watermarking for shared EEG data 基于最优鲁棒水印的共享脑电数据保护机制
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140737
Nguyen Nhat Hai, Pham Duy Trung, Nguyen Thi Hong Ha
{"title":"Right protection mechanism based on optimal robust watermarking for shared EEG data","authors":"Nguyen Nhat Hai, Pham Duy Trung, Nguyen Thi Hong Ha","doi":"10.1109/RIVF48685.2020.9140737","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140737","url":null,"abstract":"Watermarking is proved as a right-protection mechanism that can provide detectable evidence for the legal ownership of a shared dataset like image, audio, video, text. However, watermarking schemes for shared biomedical data, such as EEG data have been studied in little research. This paper proposes a optimized watermarking scheme with Particle Swarm Optimization (PSO) technique to protect ownership for shared EEG data. The proposed watermarking optimizes quantization steps to find a suitable one to achieve the highest possible robustness without losing watermark transparency. Experimental results show that the proposed scheme provides good imperceptibility and more robust against various signal processing techniques and common attacks such as noise addition, low-pass filtering, and re-sampling.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"59 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":"116813718","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
Machine learning application development to predict blood glucose level based on real time patient data 开发机器学习应用程序，根据实时患者数据预测血糖水平
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140750
G. Eigner, Miklós Nagy, L. Kovács
{"title":"Machine learning application development to predict blood glucose level based on real time patient data","authors":"G. Eigner, Miklós Nagy, L. Kovács","doi":"10.1109/RIVF48685.2020.9140750","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140750","url":null,"abstract":"The given paper details the development of a decision support system application to help for people with type 1 diabetes mellitus. The developed solution is based on supervised machine learning and it focuses to predict the future blood glucose level to support decision making of patients with conservative therapy. We applied the Tensorflow and Keras framework during our work to make our solutions embedded system compatible. We applied the AIDA diabetes simulator to generate data for the proof-of-concept. We found that our result are promising and the performance of the developed solutions are able to satisfy the requirements related the proof-of-concept.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"1 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":"128822331","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
Automatic Keywords-based Classification of Vietnamese Texts 基于关键词的越南语文本自动分类
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140761
Hao Tuan Huynh, Nghia Duong-Trung, H. Son, Nga Quynh Thi Tang, H. Huynh, Q. Truong
{"title":"Automatic Keywords-based Classification of Vietnamese Texts","authors":"Hao Tuan Huynh, Nghia Duong-Trung, H. Son, Nga Quynh Thi Tang, H. Huynh, Q. Truong","doi":"10.1109/RIVF48685.2020.9140761","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140761","url":null,"abstract":"Text classification is a sophisticated field of research in natural language processing that deals with the problem of automatically classifying new documents into pre-defined classes. It is a complex procedure involving not only selecting the right training models, but also integrating numerous fine-tuned processes, e.g. pre-processing, transformation, and dimensionality reduction. Researchers either develop new classification models or improve the existing approaches by investigating new techniques. An ideal text classifier would mimic how humans assign text to topics. People usually categorize documents by scanning their important words rather than reading the whole text source. With this process in mind, the authors propose a framework to categorize documents and apply the idea of keyword-based classification. The authors have collected real text data from various websites and utilize the TextRank algorithm and Jaccard similarity coefficient. A wide range of experiments has been conducted to show that the proposed framework achieves good results.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"27 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":"121092287","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
Digit detection from digital devices in multiple environment conditions 数字设备在多种环境条件下的数字检测
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140775
Chau N. Truong, Nguyen Q. H. Ton, Huy P. Do, Son P. Nguyen
{"title":"Digit detection from digital devices in multiple environment conditions","authors":"Chau N. Truong, Nguyen Q. H. Ton, Huy P. Do, Son P. Nguyen","doi":"10.1109/RIVF48685.2020.9140775","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140775","url":null,"abstract":"This paper proposes two automatic segmentation and detection methods to recognize seven segments digits in images of temperature and humidity screen from multiple types of devices. Since there is a lack of methods working in seven segments recognition in comparison with hand-written digits, it is important to dive deep into this area. Reading digits from screen is a difficult computer vision problem that is important for a range of real world applications. This paper focuses on the problem of segmentation and recognition digits on multiple types of digital screen, many points of views, and noisy images. Since most cameras in recent years are becoming more and more popular, users can use them to take a picture or real time tracking the screen of the device. After frame taken, computer vision techniques can be used to recognize the digits on the picture and thus record the data. In this case, specific model trained with seven segments digits will definitely do better recognition rates than general existing recognition system. With overexposed condition and noisy frame from different points of view, our methods achieve high accuracy recognition rate. Our methods are applied for over 50,000 pictures; each has one or multiple digital screen display temperature and humid in Vietnamese factories. We have found that there is much room for improvement: computer performance lags well behind human performance on our dataset since the gap between human performance and state of the art feature representations is significant, therefore, it is still a long way to reach the robust solution.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"63 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":"130696634","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
B-Box - A Decentralized Storage System Using IPFS, Attributed-based Encryption, and Blockchain B-Box -一个使用IPFS、基于属性的加密和区块链的分散存储系统
2020 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2020-10-01 DOI: 10.1109/RIVF48685.2020.9140747
Van-Duy Pham, Canh Tran, Thang Nguyen, Tien-Thao Nguyen, Ba-Lam Do, Thanh-Chung Dao, B. Nguyen
{"title":"B-Box - A Decentralized Storage System Using IPFS, Attributed-based Encryption, and Blockchain","authors":"Van-Duy Pham, Canh Tran, Thang Nguyen, Tien-Thao Nguyen, Ba-Lam Do, Thanh-Chung Dao, B. Nguyen","doi":"10.1109/RIVF48685.2020.9140747","DOIUrl":"https://doi.org/10.1109/RIVF48685.2020.9140747","url":null,"abstract":"In recent years, centralized storage systems have been extensively adopted by many companies, organizations, and individuals for storing and sharing data. These systems, however, make concerns for users of a single point of failure and the involvement of a centralized entity or third party. Therefore, there is a need for developing decentralized storage systems to overcome the drawbacks of traditional approach. In order to enhance secure and transparent characteristics of decentralized storage systems, in this paper, we present a combination of IPFS (InterPlanetary File System), ABE (Attribute-based Encryption), Multi-Authority ABE (MA-ABE), and Ethereum blockchain. In particular, we facilitate the advantages of IPFS network to store user’s data in a distributed manner. Furthermore, we make the use of MA-ABE to encrypt a document, which an user needs to share it among multiple organizations. The hash returned by the IPFS network will be stored in the Ethereum blockchain network to provide trustworthy for all users participating in our system. To the best of our knowledge, it is the first storage system using IPFS, ABE, MA-ABE, and blockchain technologies together to ensure decentralized, secure, and transparent characteristics for storing and sharing data.","PeriodicalId":169999,"journal":{"name":"2020 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"4 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":"134619414","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: 13
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