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2021 International Conference on Advanced Technologies for Communications (ATC)最新文献

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Adaptive Collision Avoidance Scheduling based on Traffic and Priority for IoT Sensor Networks 基于流量和优先级的物联网传感器网络自适应避碰调度
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598243
Linh-Trung Nguyen, Thu-Hang T. Nguyen, Hai-Chau Le, Thanh Vinh Vu, Chien Trinh Nguyen
{"title":"Adaptive Collision Avoidance Scheduling based on Traffic and Priority for IoT Sensor Networks","authors":"Linh-Trung Nguyen, Thu-Hang T. Nguyen, Hai-Chau Le, Thanh Vinh Vu, Chien Trinh Nguyen","doi":"10.1109/atc52653.2021.9598243","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598243","url":null,"abstract":"Recently, the proliferation of Internet of Things (IoT) and industrial networks poses new challenges and issues on the QoS requirements such as adaptation, real time, reliability, and energy efficiency. It is expected that important or urgent data need to be delivered in real time with higher reliability than ordinary data. To cope with that, we propose an Adaptive Collision Avoidance Scheduling based on Traffic and Priority (ACASTP) for IoT sensor networks. Our proposed solution employs data prioritizing and traffic adaptive scheme at MAC layer to ensure that higher-priority packets have more privileged access to shared channels. We have also evaluated the developed solution performance using numerical experiments on OMNeT++. The obtained results imply that, comparing to conventional approach, i.e., Timeout Multi-priority-based MAC (TMPQ MAC) protocol, the proposed scheduling scheme improves the network performance significantly.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123054733","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 dual circularly polarized metasurface-based antenna for synthetic aperture radars 合成孔径雷达双圆极化超表面天线
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598195
Thi Ngoc Hien Doan, Gia Thang Bui
{"title":"A dual circularly polarized metasurface-based antenna for synthetic aperture radars","authors":"Thi Ngoc Hien Doan, Gia Thang Bui","doi":"10.1109/atc52653.2021.9598195","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598195","url":null,"abstract":"This paper presents a dual circularly polarized metasurface-based antenna for synthetic aperture radars with a simulated high isolation of -30.6 dB and a simulated gain of 9.3 dB, within the bandwidth of 6.6%. This single element antenna achieves high isolation by using the ground with unbalanced # shaped-slot. A radiation metasurface with 4 × 4 periodic corner-truncated metallic plates changes the antenna from linear polarization (LP) to circular polarization (CP). A simple feeding network, consisting of two orthogonal ports is used in the design to excite RHCP or LHCP mode in the proposed antenna. So it is possible to employ only one antenna rather than two (RHCP and LHCP) when using the proposed structure.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"562 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127685773","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
Efficient Incremental Instance-based Learning Algorithms for Open World Malware Classification 开放世界恶意软件分类的高效增量实例学习算法
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598272
Kien Hoang Dang, Dai Tho Nguyen, Thu Hien Nguyen Thi
{"title":"Efficient Incremental Instance-based Learning Algorithms for Open World Malware Classification","authors":"Kien Hoang Dang, Dai Tho Nguyen, Thu Hien Nguyen Thi","doi":"10.1109/atc52653.2021.9598272","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598272","url":null,"abstract":"Malware is growing rapidly in number and become more and more sophisticated. To prevent them we need to collect samples continuously and update them to the classifier. In this paper, we will propose a method to update new labeled samples of malware to the classifier easily without re-training everything. The classifier can be updated by both labeled malware samples of an existing class or a new class. Our method also has the ability to detect samples of unknown families. Experiments are performed over the traditional computer malware dataset and the IoT malware dataset. The results have shown that our method can reach the macro F1-score almost the same re-train everything but take significantly less time.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126958227","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 Lightweight Multi-factor Authentication Scheme based on Digital Watermarking Technique 基于数字水印技术的轻量级多因素认证方案
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598266
Trong-Minh Hoang, Van-Hau Bui, Ngoc-Tan Nguyen
{"title":"A Lightweight Multi-factor Authentication Scheme based on Digital Watermarking Technique","authors":"Trong-Minh Hoang, Van-Hau Bui, Ngoc-Tan Nguyen","doi":"10.1109/atc52653.2021.9598266","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598266","url":null,"abstract":"Security in today’s IoT applications becomes extremely important because it is strongly related to social and human life. User authentication is the most important problem and the first step in establishing reliable communication sessions. Biometric authentication solutions including network face recognition have many advantages such as being fast, accurate, and user-friendly. Traditional authentication solutions using only device identification have always to deal with increasingly sophisticated forms of spoofing or sabotage attacks, especially for environments with low-complexity hardware devices. Thus, this paper proposes a novel multi-factor authentication solution exploiting face recognition and user’s device characteristics to increase the trustworthiness of the authentication process. Moreover, combined with the watermarking technique, the proposed scheme is lightweight and suitable for resource-constrained computing devices. By using BAN logic, the security of the proposed scheme has been analyzed to prove the reliability and security of the algorithms.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122436821","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
Comparison of Data Dimension Reduction Methods in The Problem of Detecting Attacks 攻击检测问题中的数据降维方法比较
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598247
Linh Le Thi Trang, Van-Truong Nguyen, Quang-Huy Dinh, Trong-Minh Hoang
{"title":"Comparison of Data Dimension Reduction Methods in The Problem of Detecting Attacks","authors":"Linh Le Thi Trang, Van-Truong Nguyen, Quang-Huy Dinh, Trong-Minh Hoang","doi":"10.1109/atc52653.2021.9598247","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598247","url":null,"abstract":"Data dimension reduction issue is an important problem in the data pre-processing stage of data intelligent computing systems. The performance of data dimension reduction methods not only ensure compatibility with machine learning techniques, but also improve data processing efficiency. However, the performance of a dimensional reduction processing method in a data set is always an open challenging issue since it is closely tied to the data features. This paper presents the results of comparing the performance of several approaches in two common approaches on the UNSW-NB 15 data set for attack detection. Our experimental results show that RF-MLP method is very effective for deploying IDSs against DOS attacks.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130799238","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
Development of Lightweight and Accurate Intrusion Detection on Programmable Data Plane 基于可编程数据平面的轻量、精确入侵检测方法的研究
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598239
Thi-Nga Dao, Van‐Phuc Hoang, C. Ta, V. Vu
{"title":"Development of Lightweight and Accurate Intrusion Detection on Programmable Data Plane","authors":"Thi-Nga Dao, Van‐Phuc Hoang, C. Ta, V. Vu","doi":"10.1109/atc52653.2021.9598239","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598239","url":null,"abstract":"With the aim of developing a lightweight yet accurate network security method for Internet of Things, this paper presents the neural-network-based intrusion detection model that incorporates a parameter trimming method. The intrusion detection and classification function is implemented on programmable data plane, thus significantly reducing the detection time. Moreover, by using the neuron pruning approach, the proposed architecture requires a much lower delay for traffic classification with a slight reduction in classification accuracy. We conduct experiments using a P4 programming language and the collected results show that the pruned intrusion detection model with low model complexity is more feasible for edge devices with constrained computing and memory resources than the fully-connected model.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133213343","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
Text classification problems via BERT embedding method and graph convolutional neural network 基于BERT嵌入法和图卷积神经网络的文本分类问题
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598337
L. Tran, Tuan-Kiet Tran, An Mai
{"title":"Text classification problems via BERT embedding method and graph convolutional neural network","authors":"L. Tran, Tuan-Kiet Tran, An Mai","doi":"10.1109/atc52653.2021.9598337","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598337","url":null,"abstract":"This paper presents a hybrid technique of combining the BERT embedding method and the graph convolutional neural network. This combination is then employed to solve the text classification problem. Initially, we apply the BERT embedding method to the whole corpus in order to transform all the texts into numerical vectors. Then, the graph convolutional neural network will be applied to these numerical vectors to classify these texts into their appropriate classes. Especially, in our approach, we need only a few labeled texts for the model training. For the illustration, in this paper, we use the BBC news and the IMDB movie reviews datasets to perform our experiments, showing that the performance of the graph convolutional neural network model is better than the performances of the combination of the BERT embedding method with other classical machine learning models.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132184227","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
Adaptive Sampling for Saving Energy: A Case Study on The Libelium-based Environment Monitoring Systems 基于自适应采样的节能技术——以锂基环境监测系统为例
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598270
Phat Phan-Trung, Thuat Nguyen-Khanh, Quan Le-Trung
{"title":"Adaptive Sampling for Saving Energy: A Case Study on The Libelium-based Environment Monitoring Systems","authors":"Phat Phan-Trung, Thuat Nguyen-Khanh, Quan Le-Trung","doi":"10.1109/atc52653.2021.9598270","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598270","url":null,"abstract":"In the plethora of energy saving techniques developed in Internet of Things, adaptive sampling is one of the common methods to reduce the energy consumption of IoT nodes, at the cost of reducing the data accuracy. Additionally, the user cannot define the amount of energy to be saved when performing the adaptive sampling technique. This paper shows a case study applied our developed UDASA – The User-Driven Adaptive Sampling Algorithm for Massive Internet of Things on the Libelium-based environment monitoring systems. The aim of this work is to support users to trade-off between energy consumption on IoT devices versus the data precision. The results show that once applied UDASA in 4 days, the collected data only takes about 10% compared to that of without UDASA, while the system saves 9% of energy, and the data accuracy is about 84% after interpolation.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127754139","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 Spectral Analysis Based Channel Estimation Method for Time Diversity Combining in Helicopter Satellite Communications 基于频谱分析的直升机卫星通信时分集信道估计方法
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598324
T. Kojima, Seiya Yako
{"title":"A Spectral Analysis Based Channel Estimation Method for Time Diversity Combining in Helicopter Satellite Communications","authors":"T. Kojima, Seiya Yako","doi":"10.1109/atc52653.2021.9598324","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598324","url":null,"abstract":"Helicopter satellite communications have to overcome the periodic blockage of the signal caused by rotor blades. To solve this problem, time diversity with maximal ratio combining (MRC) is promising. Although the conventional channel estimation method to perform MRC is accurate, its computational complexity is relatively high because of fast Fourier transform (FFT) and inverse FFT (IFFT). This paper proposes a novel spectral analysis based channel estimation method. The proposed method estimates the channel gain without IFFT. The computer simulation results confirmed that the proposed method reduces the FFT size by 75% without degrading the BER performance compared with the conventional method using IFFT.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"91 36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128812787","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
Physical Layer Security of Massive MIMO Spatially-uncorrelated Rician Channels 海量MIMO空间不相关信道的物理层安全
2021 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2021-10-14 DOI: 10.1109/atc52653.2021.9598293
Giang Quynh Le Vu, Thang Le Nhat, K. Truong
{"title":"Physical Layer Security of Massive MIMO Spatially-uncorrelated Rician Channels","authors":"Giang Quynh Le Vu, Thang Le Nhat, K. Truong","doi":"10.1109/atc52653.2021.9598293","DOIUrl":"https://doi.org/10.1109/atc52653.2021.9598293","url":null,"abstract":"Pilot contamination jamming not only reduces the secrecy capacity but also is difficult to detect. In this paper, we proposed a technique, in which we employ random NPSK to detect passive eavesdropper throw pilot contamination in Massive MIMO Uncorrelated Rician Fading Channels. The technique only needs two training times slot and without channel knowledge.","PeriodicalId":196900,"journal":{"name":"2021 International Conference on Advanced Technologies for Communications (ATC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128838501","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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