2023 International Conference on Information Networking (ICOIN)最新文献_第6页

Towards Decentralized Autonomous Digital Signatures Using Smart Contracts 使用智能合约实现去中心化自治数字签名

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049041

Kazumasa Omote

{"title":"Towards Decentralized Autonomous Digital Signatures Using Smart Contracts","authors":"Kazumasa Omote","doi":"10.1109/ICOIN56518.2023.10049041","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049041","url":null,"abstract":"Owing to the spread of COVID-19, the digitalization of various services is rapidly being promoted. In particular, online services such as obtaining a digital certificate (e.g., digital signature) from an authority are becoming increasingly important. Therefore, systems that can autonomously generate digital signatures are urgently required. However, the autonomous generation of signatures is difficult because the secret key for signatures must be strictly managed. Moreover, a decentralized autonomous systems should be publicly verifiable. Thus, schemes that preclude strict control of the secret key are desirable. In this study, we propose a new decentralized scheme that autonomously generates a digital signature without a secret key, using blockchain-based smart contracts. The fundamental concept behind our scheme is to eliminate secret keys by leveraging the closed nature of the processing operations of smart contracts within the blockchain; thus, the process of generating signatures and their output values satisfies the condition of immutability. Finally, we perform a security evaluation and feasibility study of our proposed scheme and show that it works securely on the Ethereum blockchain.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127642270","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

Privacy Enhanced Federated Learning Utilizing Differential Privacy and Interplanetary File System 利用差分隐私和星际文件系统的隐私增强联邦学习

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049019

Hyowon Kim, Inshil Doh

{"title":"Privacy Enhanced Federated Learning Utilizing Differential Privacy and Interplanetary File System","authors":"Hyowon Kim, Inshil Doh","doi":"10.1109/ICOIN56518.2023.10049019","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049019","url":null,"abstract":"As the Internet of Things (IoT) grows exponentially, it is becoming deeply embedded in our daily lives. As the quantity and quality of data produced by devices have also gradually increased, there have been increasing attempts to use these useful IoT big data for various applications and to combine IoT with machine learning and deep learning to process a large amount of useful data. However, in the centralized deep learning method, privacy issues have been raised because the server can use personal data collected from the user’s IoT. Due to this reason, Federated Learning (FL) method that can protect users' personal data while doing machine learning has been studied. However, current FL also has the possibility of data poisoning attacks and other problems. Therefore, this work, by suggesting distributed FL framework combined with Interplanetary File System and Differential Privacy, proposes a method that allows users to participate in FL safely and efficiently. Through this method, participants share some parts of data, and these data are collected by specific nodes. These data are combined to make a new dataset of FL network for defending against data poisoning attack and vouch for training’s accuracy. Also, an aggregation mechanism is proposed to suppress the effect of a malicious node poisoning attack. Finally, this framework is tested in python environment. With this method, one can freely open a project and anyone can join in with distributed condition, even when he or she has no enough dataset for learning but computing capability, vice versa. If a malicious node tries to interrupt the learning with poisoned dataset, aggregation mechanism and combined validation set from the network’s nodes will suppress the bad effect. We have tested through python and open-source code to verify the efficiency and privacy.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127688497","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

An Evaluation of Time-Series Anomaly Detection in Computer Networks 计算机网络中时间序列异常检测的评价

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049051

Hong Nguyen, Arash Hajisafi, Alireza Abdoli, S. H. Kim, C. Shahabi

{"title":"An Evaluation of Time-Series Anomaly Detection in Computer Networks","authors":"Hong Nguyen, Arash Hajisafi, Alireza Abdoli, S. H. Kim, C. Shahabi","doi":"10.1109/ICOIN56518.2023.10049051","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049051","url":null,"abstract":"One critical issue in any network systems is failure detection. Failures not only impact the source network but also propagate through other communicating networks due to the butterfly effect, making root causing of failures even more challenging. Therefore, the necessity to detect failures and anomalies in computer networks is fundamental. Given the nature of computer networks, data is received in a time-series format where each time-point has temporal dependencies on others. As a result, time-series analysis stands out as a potential approach to deal with the task of network anomaly detection. In this paper, we conduct studies on multivariate time series anomaly detection, varying from traditional machine learning techniques to deep learning models. We show that the choice of models is not as important as the choice of pre-processing techniques. Interestingly, non-linear normalization can boost the performance of deep detectors by around 20% in terms of F1 score and balance the preference of deep detectors for specific types of anomalies. We also study the bias of anomaly types to deep detectors, time-performance trade-offs, shortage of data, and effects of weakly labeled data on both synthetic and realworld datasets to fill out the missing insights in the literature.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128455032","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

Controlling and simulation system for hydraulic valve testing based on Qt 基于Qt的液压阀试验控制与仿真系统

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049037

Xuefeng Liu, Chen Zhang

引用次数: 0

Abnormal Client Detection Federated Learning Using Image Vectors 基于图像向量的异常客户端检测联合学习

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048907

Jinseon Park, Ki Tae Kim, Seong-Bae Park, C. Hong

引用次数: 0

A Review on Satellite-Terrestrial Integrated Wireless Networks: Challenges and Open Research Issues 星-地集成无线网络研究进展:挑战与有待解决的问题

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049009

D. Lakew, Anh-Tien Tran, Arooj Masood, Nhu-Ngoc Dao, Sungrae Cho

引用次数: 1

Scalable Channel Allocation in Downlink NOMA Using Parallel Array of Laser Chaos Decision-Maker 基于激光混沌决策者并行阵列的下行NOMA可扩展信道分配

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048909

Masaki Sugiyama, Aohan Li, M. Naruse, M. Hasegawa

{"title":"Scalable Channel Allocation in Downlink NOMA Using Parallel Array of Laser Chaos Decision-Maker","authors":"Masaki Sugiyama, Aohan Li, M. Naruse, M. Hasegawa","doi":"10.1109/ICOIN56518.2023.10048909","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048909","url":null,"abstract":"Non-orthogonal multiple access (NOMA) is a technology that multiplexes multiple users on the same channel at transmitters through appropriate channel allocation, and the signal detection of multiple users at receivers is conducted based on successive interference cancellation. Real-time processing requires an ultra-fast channel allocation scheme. Previous studies have demonstrated that a laser chaos decision-maker is ultra-fast and effective in solving the decision-making problem. This study demonstrates a scalable channel allocation using a laser chaos decision-maker. The possible approaches to channel allocation increase abruptly with the number of users, which is difficult to handle with the previously proposed NOMA principle using a single laser chaos decision-maker in which its decision corresponds to the channel allocation for all users. Here, the proposed principle adopts an array of laser chaos decision-makers, each of which decides a channel for a particular user. Using this architecture, the proposed scheme can handle an increasing number of users or realize a scalable and ultrafast channel allocation in NOMA. The obtained numerical results indicate that the proposed approach obtains a higher throughput than conventional-NOMA and uniformed channel gain difference-NOMA in several wireless communication environments with differences in density and distance decay.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125440936","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

Edge-assisted Attention-based Federated Learning for Multi-Step EVSE-enabled Prosumer Energy Demand Prediction 边缘辅助的基于注意力的联邦学习，用于支持多步evse的生产消费者能源需求预测

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048987

Luyao Zou, Chu Myaet Thwal, Seong-Bae Park, C. Hong

{"title":"Edge-assisted Attention-based Federated Learning for Multi-Step EVSE-enabled Prosumer Energy Demand Prediction","authors":"Luyao Zou, Chu Myaet Thwal, Seong-Bae Park, C. Hong","doi":"10.1109/ICOIN56518.2023.10048987","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048987","url":null,"abstract":"Energy demand prediction for the prosumer building, which is capable of playing the role of an electric vehicle (EV) charging station (EVCS) with installed EV supply equipment (EVSE), is currently of paramount importance for ameliorating energy efficiency and mitigating energy wastage. However, the time-dependency characteristics between successive energy demand data, the stochasticity of the number of EVs, and the randomness of the energy demand data of EVs and prosumers cause challenges in accurately predicting energy demand. Therefore, it is urgent to do energy demand prediction for prosumers. Nevertheless, energy demand prediction through centralized training is an extravagant process. This is because transferring energy data to a centralized machine for prediction will not only cause network bandwidth and energy consumption, but also cause communication delay. Thus, in this paper, an edge-assisted attention-based federated learning (FL) algorithm is proposed for multi-step energy demand prediction of prosumers, where the goal is to minimize the average forecasting loss. Specifically, since the attention mechanism has the advantage of detecting important features from inputs, to capture the temporal features and improve the prediction accuracy, the long short-term memory-utilized sequence to sequence model with the attention mechanism (LSTM-Seq2Seq-att) in FL setting is employed in each local edge server to train the global model collaboratively. The evaluation results clarify the effectiveness of the proposed method.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127614299","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 Review on Recent Approaches in mmWave UAV-aided Communication Networks and Open Issues 毫米波无人机辅助通信网络研究进展及有待解决的问题

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049043

Quang Tuan Do, D. Lakew, Anh-Tien Tran, D. Hua, Sungrae Cho

{"title":"A Review on Recent Approaches in mmWave UAV-aided Communication Networks and Open Issues","authors":"Quang Tuan Do, D. Lakew, Anh-Tien Tran, D. Hua, Sungrae Cho","doi":"10.1109/ICOIN56518.2023.10049043","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049043","url":null,"abstract":"Recently, the use of unmanned aerial vehicles (UAVs) is spreading to many fields, especially for wireless communication-related tasks. However, such communication is facing many challenges, as the sub-6 GHz frequency band is now heavily occupied. As a result, millimeter-wave (mmWave) frequency band communication is now a promising technology to tackle that issue. By equipping multiple antennas to the UAV to perform 3D beamforming, as well as making good use of the flexible mobility of the UAV, we can greatly improve the communication link in mmWave communication systems. On the other hand, the trend of using intelligent-based learning methods, specifically reinforcement learning greatly increases recently, due to their ability to capture the dynamic of complex systems. In this study, we review recent approaches in mmWave UAV-aided communication networks. We first introduce the main characteristics of mmWave UAV networks, then we provide some insight into the recent trend of applying intelligent learning-based methods for solving this type of system. After that, some open issues and potential research directions for the mmWave UAV communication systems are provided.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127485278","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

Scene identification using visual semantic segmentation and supplementary classifier for resource-constrained edge systems 基于视觉语义分割和辅助分类器的资源约束边缘系统场景识别

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/icoin56518.2023.10048947

Chungjae Choe, Sungwook Jung, Nak-Myoung Sung, Sukjun Lee

{"title":"Scene identification using visual semantic segmentation and supplementary classifier for resource-constrained edge systems","authors":"Chungjae Choe, Sungwook Jung, Nak-Myoung Sung, Sukjun Lee","doi":"10.1109/icoin56518.2023.10048947","DOIUrl":"https://doi.org/10.1109/icoin56518.2023.10048947","url":null,"abstract":"This paper presents a scene identification method employing semantic segmentation where the method provides real-time computation in resource-constrained edge devices. Scene identification could be crucial for intelligent systems (e.g., service robots, drone-based inspection, and visual surveillance) regarding a proper decision making of those systems. Existing methods focus on adopting a deep learning-based image classification for the identification. However, those approaches may provide wrong identification due to an overlap of spatial features when training dataset is limited.In this paper, we propose an accurate scene identification with a novel approach. Our method includes two-steps: 1) measurement of object class frequency with visual semantic segmentation; 2) scene classification using class frequencies. For fast computation, we build a lightweight backbone network for the segmentation model in addition to TensorRT-based optimization. From the experiments, we validate that our method improves the identification accuracy by 12% compared to conventional visual classification-based method. In terms of computation, we observe that the method enables real-time inference on resource- constrained devices (i.e., NVIDIA Jetsons).","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126261567","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