2021 IEEE Global Communications Conference (GLOBECOM)最新文献_第8页

Architecture and Performance Comparison of Permissioned Blockchains Platforms for Smart Contracts 智能合约许可区块链平台的架构和性能比较

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685508

Guilherme A. Thomaz, G. Camilo, Lucas Airam C. de Souza, O. Duarte

引用次数: 2

BPFL: A Blockchain Based Privacy-Preserving Federated Learning Scheme BPFL:一种基于区块链的隐私保护联邦学习方案

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685821

Naiyu Wang, Wenti Yang, Zhitao Guan, Xiaojiang Du, M. Guizani

引用次数: 6

Instantaneous Feedback-based Opportunistic Symbol Length Adaptation for Reliable Communication 基于瞬时反馈的可靠通信机会符号长度自适应

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685257

Chin-Wei Hsu, A. Anastasopoulos, Hun-Seok Kim

引用次数: 3

Autonomous UAV Aided Vehicular Edge Computing for Service Offering 自主无人机辅助车辆边缘计算服务提供

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685525

Mohammed Laroui, Hatem Ibn-Khedher, Hassine Moungla, H. Afifi

引用次数: 3

Measuring Adoption of DNS Security Mechanisms with Cross-Sectional Approach 用横断面法测量DNS安全机制的采用情况

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685960

Masanori Yajima, Daiki Chiba, Yoshiro Yoneya, Tatsuya Mori

{"title":"Measuring Adoption of DNS Security Mechanisms with Cross-Sectional Approach","authors":"Masanori Yajima, Daiki Chiba, Yoshiro Yoneya, Tatsuya Mori","doi":"10.1109/GLOBECOM46510.2021.9685960","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685960","url":null,"abstract":"The threat of attacks targeting a DNS, such as DNS cache poisoning attacks and DNS amplification attacks, continues unabated. In addition, attacks that exploit the difficulty in deter-mining the authenticity of domain names, such as phishing sites and fraudulent emails, continue to be a significant threat. Various DNS security mechanisms have been proposed, standardized, and implemented as effective countermeasures against DNS-related attacks. However, it is not clear how widespread these security mechanisms are in the DNS ecosystem and how effectively they work in the wild. With this background, this study targets the major DNS security mechanisms deployed for the DNS name servers, DNSSEC, DNS Cookies, CAA, SPF, DMARC, MTA-STS, DANE, and TLSRPT, and a large-scale measurement analysis of their deployment is conducted. Our results quantitatively reveal that, as of 2021, the adoption rate of most DNS security mechanisms, except SPF, remains low, and the adoption rate is lower for mechanisms that are more difficult to configure. These findings suggest the importance of developing easy-to-deploy tools to promote the adoption of security mechanisms.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130727123","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

WiMate: Location-independent Material Identification Based on Commercial WiFi Devices WiMate:基于商用WiFi设备的位置无关材料识别

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685094

Yu Gu, Yanan Zhu, Jie Li, Yusheng Ji

{"title":"WiMate: Location-independent Material Identification Based on Commercial WiFi Devices","authors":"Yu Gu, Yanan Zhu, Jie Li, Yusheng Ji","doi":"10.1109/GLOBECOM46510.2021.9685094","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685094","url":null,"abstract":"Material identification is playing an increasingly important role in our daily lives such as public security checks. X-ray-based technologies are highly radioactive because they rely on specialized devices to transmit high-frequency signals. Ultrasound-based technologies are cumbersome due to their large size. RF-based approaches necessitate the use of RFID which is usually expensive to be used in home and office environments. To this end, WiFi-based material identification approach has emerged recently as a low-cost yet effective alternative. In this paper, we propose WiMate, a noncontact material identification system leveraging only off-the-shelf WiFi devices. The key enabler of WiMate is a novel theoretical model we build to characterize how the electromagnetic wave decays when penetrating different materials. Our model identifies a unique feature for each material that only depends on the material itself. Consequently, we can leverage this feature coupling with the machine learning techniques for robust and accurate material identification. We prototype WiMate using low-cost commodity WiFi devices and evaluate its performance in real-world. The empirical study shows that WiMate can identify six different materials, i.e., board, paperboard, nickel, wood chip, iron and titanium, with an average accuracy of 96.20%.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132930806","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

Physical Layer Security Optimization for MIMO Enabled Visible Light Communication Networks 支持MIMO的可见光通信网络物理层安全优化

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685063

Zheng Xu, Ming Chen, Mingzhe Chen, Zhaohui Yang, Yihan Cang, H. Poor

引用次数: 0

CFL-HC: A Coded Federated Learning Framework for Heterogeneous Computing Scenarios CFL-HC:异构计算场景下的编码联邦学习框架

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685962

Dong Wang, Baoqian Wang, Jinran Zhang, K. Lu, Junfei Xie, Yan Wan, Shengli Fu

{"title":"CFL-HC: A Coded Federated Learning Framework for Heterogeneous Computing Scenarios","authors":"Dong Wang, Baoqian Wang, Jinran Zhang, K. Lu, Junfei Xie, Yan Wan, Shengli Fu","doi":"10.1109/GLOBECOM46510.2021.9685962","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685962","url":null,"abstract":"Federated learning (FL) is a promising machine learning paradigm because it allows distributed edge devices to collaboratively train a model without sharing their raw data. In practice, a major challenge to FL is that edge devices are heterogeneous, so slow devices may compromise the convergence of model training. To address such a challenge, several recent studies have suggested different solutions, in which a promising scheme is to utilize coded computing to facilitate the training of linear models. Nevertheless, the existing coded FL (CFL) scheme is limited by a fixed coding redundancy parameter, and a weight matrix used in the existing design may introduce unnecessary errors. In this paper, we tackle these issues and propose a novel framework, namely CFL-HC, to facilitate CFL in heterogeneous computing scenarios. In our framework, we consider a computing system consisting of a central server and multiple computing devices with original or coded datasets. Then we specify an expected number of input-output pairs that are used in one round. Within such a framework, we formulate an optimization problem to find the best deadline of each training round and the optimal size of the computing task allocated to each computing device. We then design a two-step optimization scheme to obtain the optimal solution. To evaluate the proposed framework, we develop a real CFL system using the message passing interface platform. Based on this system, we conduct numerical experiments, which demonstrate the advantages of the proposed framework, in terms of both accuracy and convergence speed.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133074879","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

Kernel-Based Structural-Temporal Cascade Learning for Popularity Prediction 基于核的结构-时间级联学习的人气预测

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685636

Ce Li, Fan Zhou, Xucheng Luo, Goce Trajcevski

{"title":"Kernel-Based Structural-Temporal Cascade Learning for Popularity Prediction","authors":"Ce Li, Fan Zhou, Xucheng Luo, Goce Trajcevski","doi":"10.1109/GLOBECOM46510.2021.9685636","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685636","url":null,"abstract":"One of the main objectives of information cascade popularity prediction is to forecast the future size of a cascade given the observed propagation information. It is an enabling step for many practical applications (e.g., advertisement, academic writing, etc.). Recent advances in neural networks have spurred a few deep learning-based cascade models, which preserve the structural features of information cascades with node embedding and graph neural networks. However, efforts in cascade graph learning as well as its internal temporal dependency, existing methods mainly focus on node-level similarity learning, ignoring the structural equivalence among different sub-graphs that are more informative for information diffusion prediction. Towards this, we present a kernel-based structural-temporal cascade learning model, called CasKernel, to explicitly estimate and encode the structural similarity of cascades with the graph kernels. Moreover, we employ a non sequential process to address the temporal dependency, which can be used to facilitate information popularity prediction. Experiments conducted on both tweets propagation network and academic citation network demonstrate the effectiveness of our method.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"183 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133315676","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

Efficient Multiple Charging Base Stations Assignment for Far-Field Wireless-Charging in Green IoT 绿色物联网远场无线充电的高效多充电基站分配

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685825

Qiuyu Sha, Xilong Liu, Nirwan Ansari, Yongxing Jia

{"title":"Efficient Multiple Charging Base Stations Assignment for Far-Field Wireless-Charging in Green IoT","authors":"Qiuyu Sha, Xilong Liu, Nirwan Ansari, Yongxing Jia","doi":"10.1109/GLOBECOM46510.2021.9685825","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685825","url":null,"abstract":"Owing to the development of Internet of Things (IoT) and Artificial Intelligence (AI) technology, powering IoT devices has become a dire problem that mobile IoT devices need a more portable way to be charged. Based on our previous research on green IoT, the far-field Wireless Power Transfer (WPT) powered by green energy can alleviate this problem. Although many existing works on Multi-Base Station Joint Charging Schemes have gained remarkable results, the aggregation of multiple power waves cannot be explicitly described by the traditional 1-dimensional model suggested by Friis Formula. The 2-dimensional model called vector model can solve this problem by clearly indicating how the multiple power waves aggregate at an IoT device in the form of a 2-dimensional vector. In this work, an Adjusting Phase (AP) method based on the vector model is designed to enhance the value of aggregated power waves. In addition, we propose the Greedy chArging Grouping Algorithm (GAGA) to ensure that the charging mission will be completed on time and the risk of running out of power can be reduced. Finally, we validate the performance of the proposed algorithm in comparison with the state-of-the-art solutions through extensive simulations.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132087239","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