Pub Date : 2023-01-01DOI: 10.1109/ICOIN56518.2023.10049016
Bo-Ram Lee, Won-Bin Oh, Hak-Hyoung Kim, Yeongdo Jeong, Jae Seung Yoon, Ill-Soo Kim
{"title":"A Study on the Cluster-wise Regression Model for Bead Width in the Automatic GMA Welding","authors":"Bo-Ram Lee, Won-Bin Oh, Hak-Hyoung Kim, Yeongdo Jeong, Jae Seung Yoon, Ill-Soo Kim","doi":"10.1109/ICOIN56518.2023.10049016","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049016","url":null,"abstract":"","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"114 1","pages":"686-691"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79224971","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}
Pub Date : 2023-01-01DOI: 10.1109/ICOIN56518.2023.10048926
J. Yoon, Sun Moo Kang, Seong-Bae Park, C. Hong
{"title":"GDFed: Dynamic Federated Learning for Heterogenous Device Using Graph Neural Network","authors":"J. Yoon, Sun Moo Kang, Seong-Bae Park, C. Hong","doi":"10.1109/ICOIN56518.2023.10048926","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048926","url":null,"abstract":"","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"148 1","pages":"683-685"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80082482","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333968
Rubina Akter, Jae-Min Lee, Dong-Seong Kim
Due to the advancements of electricity dependent machinery, the excessive growth of power consumption has increased exponentially. Therefore, analysis and prediction of the energy consumption system will offer the future demand for electricity consumption and improve the power distribution system. On account of several challenges of existing energy consumption prediction models that are limiting to predict the actual energy consumption properly. Thus, to conquer the energy prediction method, this paper analyzes fourteen years of energy consumption data collected on an hourly basis, an open source dataset from kaggle. Moreover, the paper initiates a Long Short Term Memory (LSTM) based approach to predict the energy consumption based on the actual dataset. The empirical results demonstrate that the proposed LSTM architecture can efficiently enhance the prediction accuracy of energy consumption.
{"title":"Analysis and Prediction of Hourly Energy Consumption Based on Long Short-Term Memory Neural Network","authors":"Rubina Akter, Jae-Min Lee, Dong-Seong Kim","doi":"10.1109/ICOIN50884.2021.9333968","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333968","url":null,"abstract":"Due to the advancements of electricity dependent machinery, the excessive growth of power consumption has increased exponentially. Therefore, analysis and prediction of the energy consumption system will offer the future demand for electricity consumption and improve the power distribution system. On account of several challenges of existing energy consumption prediction models that are limiting to predict the actual energy consumption properly. Thus, to conquer the energy prediction method, this paper analyzes fourteen years of energy consumption data collected on an hourly basis, an open source dataset from kaggle. Moreover, the paper initiates a Long Short Term Memory (LSTM) based approach to predict the energy consumption based on the actual dataset. The empirical results demonstrate that the proposed LSTM architecture can efficiently enhance the prediction accuracy of energy consumption.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"136 1","pages":"732-734"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78193389","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333928
Daichi Ozaki, Hiroshi Yamamoto, E. Utsunomiya, K. Yoshihara
In recent years, there have been several incidents of crop damage and injury caused by harmful animals in various areas of Japan each year, amounting to about 15.8 billion yen in 2018. In order to reduce the damage, a number of existing studies have been conducted on camera-based systems. However, this existing system requires that the sensing devices should always be running, which makes it inappropriate for installation in mountainous areas where electronic power is difficult to be supplied to the system. Therefore, in this research, we propose a new harmful animals detection system that can detect not only the approaching of animals to the traps and the fences but also their species and postures by combining various sensing technologies (i.e., beacon sensing, laser radar, and depth camera). The beacon sensing attempts to detect the passage of moving objects by analyzing changes in received signal strength caused by reflection, diffraction, and absorption of radio wave beacons by the object. After detecting the passage of the moving object, a small computer is activated to measure one-dimensional distance to the target object using a laser radar. The time-series data of the measured distance is analyzed by the machine learning technology to estimate the type of the moving object (e.g., human, animal). If the moving object is judged as a harmful animal, the small computer activates the depth camera to acquire two-dimensional distance data of the target animal. The acquired distance data is analyzed by the machine learning technology to estimate the posture of the harmful animal. As explained above, by gradually activating the sensors with higher power consumption, the proposed system achieves power-saving.
{"title":"Harmful Animals Detection System Utilizing Cooperative Actuation of Multiple Sensing Devices","authors":"Daichi Ozaki, Hiroshi Yamamoto, E. Utsunomiya, K. Yoshihara","doi":"10.1109/ICOIN50884.2021.9333928","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333928","url":null,"abstract":"In recent years, there have been several incidents of crop damage and injury caused by harmful animals in various areas of Japan each year, amounting to about 15.8 billion yen in 2018. In order to reduce the damage, a number of existing studies have been conducted on camera-based systems. However, this existing system requires that the sensing devices should always be running, which makes it inappropriate for installation in mountainous areas where electronic power is difficult to be supplied to the system. Therefore, in this research, we propose a new harmful animals detection system that can detect not only the approaching of animals to the traps and the fences but also their species and postures by combining various sensing technologies (i.e., beacon sensing, laser radar, and depth camera). The beacon sensing attempts to detect the passage of moving objects by analyzing changes in received signal strength caused by reflection, diffraction, and absorption of radio wave beacons by the object. After detecting the passage of the moving object, a small computer is activated to measure one-dimensional distance to the target object using a laser radar. The time-series data of the measured distance is analyzed by the machine learning technology to estimate the type of the moving object (e.g., human, animal). If the moving object is judged as a harmful animal, the small computer activates the depth camera to acquire two-dimensional distance data of the target animal. The acquired distance data is analyzed by the machine learning technology to estimate the posture of the harmful animal. As explained above, by gradually activating the sensors with higher power consumption, the proposed system achieves power-saving.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"13 1","pages":"808-813"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75045679","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333990
Yuta Kuwahara, Naoki Aihara, S. Yamazaki, K. Ohuchi, H. Mizuno
With the progress of internet of things (IoT), devices with a wireless ad-hoc function are being increasingly used. For future wireless communication systems, the use of millimeter waves, which are strongly affected by shadowing, is considered. We focus on energy-efficiency [bits/J] that combines throughput and energy consumption, which is expected to be important in future wireless communication systems, to realize smart IoT in a shadowing environment. In this paper, we compare the effects of two parameters, including shadowing deviation values, on energy-efficiency in three dimensions for both AODV and OLSR protocols in a shadowing environment using network simulator, ns3.
{"title":"Energy-Efficiency Comparison of Ad-hoc Routings in a Shadowing Environment for Smart IoT","authors":"Yuta Kuwahara, Naoki Aihara, S. Yamazaki, K. Ohuchi, H. Mizuno","doi":"10.1109/ICOIN50884.2021.9333990","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333990","url":null,"abstract":"With the progress of internet of things (IoT), devices with a wireless ad-hoc function are being increasingly used. For future wireless communication systems, the use of millimeter waves, which are strongly affected by shadowing, is considered. We focus on energy-efficiency [bits/J] that combines throughput and energy consumption, which is expected to be important in future wireless communication systems, to realize smart IoT in a shadowing environment. In this paper, we compare the effects of two parameters, including shadowing deviation values, on energy-efficiency in three dimensions for both AODV and OLSR protocols in a shadowing environment using network simulator, ns3.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"11 1","pages":"801-804"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81904163","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333907
Seshariana Rahma Melati, L. V. Yovita, Ratna Mayasari
Named Data Networking, a future internet network architecture design that can change the network’s perspective from previously host-centric to data-centric. It can reduce the network load, especially on the server part, and can provide advantages in multicast cases or re-sending of content data to users due to transmission errors. In NDN, interest messages are sent to the router, and if they are not immediately found, they will continue to be forwarded, resulting in a large load. NDNS or a DNS-Like Name Service for NDN is needed to know exactly where the content is to improve system performance. NDNS is a database that provides information about the zone location of the data contained in the network. In this study, a simulation was conducted to test the NDNS mechanism on the NDN network to support caching on the NDN network by testing various topologies with changes in the size of the content store and the number of nodes used. NDNS is outperform compared to NDN without NDNS for cache hit ratio and load parameters.
{"title":"Caching Performance of Named Data Networking with NDNS","authors":"Seshariana Rahma Melati, L. V. Yovita, Ratna Mayasari","doi":"10.1109/ICOIN50884.2021.9333907","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333907","url":null,"abstract":"Named Data Networking, a future internet network architecture design that can change the network’s perspective from previously host-centric to data-centric. It can reduce the network load, especially on the server part, and can provide advantages in multicast cases or re-sending of content data to users due to transmission errors. In NDN, interest messages are sent to the router, and if they are not immediately found, they will continue to be forwarded, resulting in a large load. NDNS or a DNS-Like Name Service for NDN is needed to know exactly where the content is to improve system performance. NDNS is a database that provides information about the zone location of the data contained in the network. In this study, a simulation was conducted to test the NDNS mechanism on the NDN network to support caching on the NDN network by testing various topologies with changes in the size of the content store and the number of nodes used. NDNS is outperform compared to NDN without NDNS for cache hit ratio and load parameters.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"10 1","pages":"261-266"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84334976","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333850
Min Jun Lee, Jungmin So
Few-shot learning task, which aims to recognize a new class with insufficient data, is an inevitable issue to be solved in image classification. Among recent work, Metalearning is commonly used to Figure out few-shot learning task. Here we tackle a recent method that uses the nearest-neighbor algorithm when recognizing few-shot images and to this end, propose a metric-based approach for nearest-neighbor few-shot classification. We train a convolutional neural network with miniImageNet applying three types of loss, triplet loss, crossentropy loss, and combination of triplet loss and cross-entropy loss. In evaluation, three configurations exist according to feature transformation technique which are unnormalized features, L2-normalized features, and centered L2-norma1ized features. For 1-shot 5-way task, the triplet loss model attains the uppermost accuracy among all three configurations and for 5-shot 5-way task, the identical model reaches the foremost accuracy in unnormalized features configuration.
{"title":"Metric-Based Learning for Nearest-Neighbor Few-Shot Image Classification","authors":"Min Jun Lee, Jungmin So","doi":"10.1109/ICOIN50884.2021.9333850","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333850","url":null,"abstract":"Few-shot learning task, which aims to recognize a new class with insufficient data, is an inevitable issue to be solved in image classification. Among recent work, Metalearning is commonly used to Figure out few-shot learning task. Here we tackle a recent method that uses the nearest-neighbor algorithm when recognizing few-shot images and to this end, propose a metric-based approach for nearest-neighbor few-shot classification. We train a convolutional neural network with miniImageNet applying three types of loss, triplet loss, crossentropy loss, and combination of triplet loss and cross-entropy loss. In evaluation, three configurations exist according to feature transformation technique which are unnormalized features, L2-normalized features, and centered L2-norma1ized features. For 1-shot 5-way task, the triplet loss model attains the uppermost accuracy among all three configurations and for 5-shot 5-way task, the identical model reaches the foremost accuracy in unnormalized features configuration.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"20 1","pages":"460-464"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81246750","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9334014
Heemang Song, Youngkeun Yoo, Hyun-Chool Shin
In this paper, we suggest features for passenger detection inside the vehicle using frequency modulated continuous wave (FMCW) radar. In radar time-frequency spectrum, the magnitude variation of a person is caused by the physiological movements such as breathing and heartbeat. To quantify the physiological movements, the power of respiratory frequency band (0.1–0.4 Hz) and heartbeat frequency band (0.8–1.7 Hz) is used. We experimentally compare the proposed features under presence and absence of a person using FMCW radar signal acquired inside the vehicle.
{"title":"In-Vehicle Passenger Detection Using FMCW Radar","authors":"Heemang Song, Youngkeun Yoo, Hyun-Chool Shin","doi":"10.1109/ICOIN50884.2021.9334014","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9334014","url":null,"abstract":"In this paper, we suggest features for passenger detection inside the vehicle using frequency modulated continuous wave (FMCW) radar. In radar time-frequency spectrum, the magnitude variation of a person is caused by the physiological movements such as breathing and heartbeat. To quantify the physiological movements, the power of respiratory frequency band (0.1–0.4 Hz) and heartbeat frequency band (0.8–1.7 Hz) is used. We experimentally compare the proposed features under presence and absence of a person using FMCW radar signal acquired inside the vehicle.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"11 1","pages":"644-647"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84602184","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333943
Kota Tohno, Ryo Nakamura, N. Kamiyama
In recent years, Information-Centric Networking (ICN) which mainly focuses on the transferred data rather than the sending and receiving hosts has attracted attention. To realize ICN as a future Internet architecture, it is required that ICN is robust against network failures such as a disaster and errors of network equipments. In our previous work, we proposed a caching strategy called CDO (Caching based on Distance to Originals), which achieves the high content availability at network failure in ICN. In the CDO, a router caches a content only when the hop distance between the origin of the content and itself is greater than or equal to a given caching threshold. However, in our previous work, we focused on only maximizing the AMDC (Average Maximum hop Distance to Caching copies) which leads to the content availability at the network failure, and did not sufficiently consider the cache hit ratio, i.e., the probability that the requested content is returned from one of routers. Therefore, in this paper, we study how to design the caching threshold of the CDO, which aimed at achieving the high AMDC and the high cache hit ratio using the CDO. Especially, we consider the optimal design method of caching threshold using a weighted sum and the design method of caching threshold for each content. As a result of investigating the effectiveness of the two types of the design methods through experiments, we show that the cache hit ratio can be significantly improved while maintaining the high AMDC by appropriately designing the caching threshold of the CDO.
近年来，信息中心网络(Information-Centric Networking, ICN)引起了人们的关注，它主要关注传输的数据而不是发送和接收主机。为了使ICN成为未来的互联网架构，要求ICN对网络故障(如网络设备的灾难和错误)具有鲁棒性。在我们之前的工作中，我们提出了一种名为CDO (caching based on Distance to Originals)的缓存策略，实现了ICN在网络故障时的高内容可用性。在CDO中，只有当内容源与路由器之间的跳距大于或等于给定的缓存阈值时，路由器才会缓存内容。然而，在我们之前的工作中，我们只关注最大化导致网络故障时内容可用性的AMDC(到缓存副本的平均最大跳距离)，而没有充分考虑缓存命中率，即请求的内容从其中一个路由器返回的概率。因此，本文研究了如何设计CDO的缓存阈值，旨在利用CDO实现高AMDC和高缓存命中率。特别地，我们考虑了基于加权和的缓存阈值优化设计方法和针对每个内容的缓存阈值设计方法。通过实验考察了两种设计方法的有效性，结果表明，通过合理设计CDO的缓存阈值，可以在保持较高AMDC的同时显著提高缓存命中率。
{"title":"On Design of Caching Threshold of Caching Strategy CDO for ICN","authors":"Kota Tohno, Ryo Nakamura, N. Kamiyama","doi":"10.1109/ICOIN50884.2021.9333943","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333943","url":null,"abstract":"In recent years, Information-Centric Networking (ICN) which mainly focuses on the transferred data rather than the sending and receiving hosts has attracted attention. To realize ICN as a future Internet architecture, it is required that ICN is robust against network failures such as a disaster and errors of network equipments. In our previous work, we proposed a caching strategy called CDO (Caching based on Distance to Originals), which achieves the high content availability at network failure in ICN. In the CDO, a router caches a content only when the hop distance between the origin of the content and itself is greater than or equal to a given caching threshold. However, in our previous work, we focused on only maximizing the AMDC (Average Maximum hop Distance to Caching copies) which leads to the content availability at the network failure, and did not sufficiently consider the cache hit ratio, i.e., the probability that the requested content is returned from one of routers. Therefore, in this paper, we study how to design the caching threshold of the CDO, which aimed at achieving the high AMDC and the high cache hit ratio using the CDO. Especially, we consider the optimal design method of caching threshold using a weighted sum and the design method of caching threshold for each content. As a result of investigating the effectiveness of the two types of the design methods through experiments, we show that the cache hit ratio can be significantly improved while maintaining the high AMDC by appropriately designing the caching threshold of the CDO.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"110 1","pages":"615-620"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87746261","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}
Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333910
N. Vithanage, Sangeeth S. Hetti Thanthrige, Malsha C. K. Paththini Kapuge, Tharindu H. Malwenna, C. Liyanapathirana, J. Wijekoon
The world is now shifting from Industry 4.0 to Industry 5.0 enabling the automation of the human livelihood by using Internet of Things (IoT). IoT can be attributed as a network that connects many sensor devices to collect data to provide automated smart environments. However, with a huge number of connected devices already deployed worldwide and organizations resorting to IoT development services more frequently because IoT security issues remain a matter of concern. One of the main identified reasons is IoT devices possess limited memory capacity, energy, processing which cause difficulties to run complex security algorithms, hindering the security services such as privacy and authentication, although those are crucial factors of IoT services. Hence, the adoption of adequate security and authentication techniques are necessary for a broad IoT deployment. To this end, this study proposes an authentication platform to improve the security and efficiency of data transmission between the IoT devices using LDAP and MQTT technologies. The implementation complies with IEEE 1451 standardization to uplift the MQTT with the help of LDAP features and GZip compression.
{"title":"A Secure Corroboration Protocol for Internet of Things (IoT) Devices Using MQTT Version 5 and LDAP","authors":"N. Vithanage, Sangeeth S. Hetti Thanthrige, Malsha C. K. Paththini Kapuge, Tharindu H. Malwenna, C. Liyanapathirana, J. Wijekoon","doi":"10.1109/ICOIN50884.2021.9333910","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333910","url":null,"abstract":"The world is now shifting from Industry 4.0 to Industry 5.0 enabling the automation of the human livelihood by using Internet of Things (IoT). IoT can be attributed as a network that connects many sensor devices to collect data to provide automated smart environments. However, with a huge number of connected devices already deployed worldwide and organizations resorting to IoT development services more frequently because IoT security issues remain a matter of concern. One of the main identified reasons is IoT devices possess limited memory capacity, energy, processing which cause difficulties to run complex security algorithms, hindering the security services such as privacy and authentication, although those are crucial factors of IoT services. Hence, the adoption of adequate security and authentication techniques are necessary for a broad IoT deployment. To this end, this study proposes an authentication platform to improve the security and efficiency of data transmission between the IoT devices using LDAP and MQTT technologies. The implementation complies with IEEE 1451 standardization to uplift the MQTT with the help of LDAP features and GZip compression.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"13 1","pages":"837-841"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88426442","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}
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