A complex and changeable underwater archaeological environment leads to the lack of target features in the collected images, affecting the accuracy of target detection. Meanwhile, the difficulty in obtaining underwater archaeological images leads to less training data, resulting in poor generalization performance of the recognition algorithm. For these practical issues, we propose an underwater incomplete target recognition network via generating feature module (UITRNet). Specifically, for targets that lack features, features are generated by dual discriminators and generators to improve target detection accuracy. Then, multilayer features are fused to extract regions of interest. Finally, supervised contrastive learning is introduced into few-shot learning to improve the intraclass similarity and interclass distance of the target and enhance the generalization of the algorithm. The UIFI dataset is produced to verify the effectiveness of the algorithm in this paper. The experimental results show that the mean average precision (mAP) of our algorithm was improved by 0.86% and 1.29% under insufficient light and semiburied interference, respectively. The mAP for ship identification reached the highest level under all four sets of experiments.
{"title":"Underwater Incomplete Target Recognition Network via Generating Feature Module","authors":"Qi Shen, Jishen Jia, Lei Cai","doi":"10.1155/2023/5337454","DOIUrl":"https://doi.org/10.1155/2023/5337454","url":null,"abstract":"A complex and changeable underwater archaeological environment leads to the lack of target features in the collected images, affecting the accuracy of target detection. Meanwhile, the difficulty in obtaining underwater archaeological images leads to less training data, resulting in poor generalization performance of the recognition algorithm. For these practical issues, we propose an underwater incomplete target recognition network via generating feature module (UITRNet). Specifically, for targets that lack features, features are generated by dual discriminators and generators to improve target detection accuracy. Then, multilayer features are fused to extract regions of interest. Finally, supervised contrastive learning is introduced into few-shot learning to improve the intraclass similarity and interclass distance of the target and enhance the generalization of the algorithm. The UIFI dataset is produced to verify the effectiveness of the algorithm in this paper. The experimental results show that the mean average precision (mAP) of our algorithm was improved by 0.86% and 1.29% under insufficient light and semiburied interference, respectively. The mAP for ship identification reached the highest level under all four sets of experiments.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43092526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221135516
Yourui Huang, Gang Zhang, Min Kong, Fugui He
Aimed at the demands of wireless sensor networks for high energy-efficient time synchronization, the reduction of synchronization energy consumption is studied from the aspects of both accurate timestamps marking and synchronous information transmission mechanism. First, the network is divided into several parent–child groups periodically. The group-wise pair selection algorithm is used to select the network’s pairwise synchronization nodes, and chain-type network topology is thus generated. Second, the sequential multi-hop synchronization algorithm is introduced to realize the synchronization information exchange among pairwise synchronization nodes. The overhearing synchronization (OS) nodes obtain the synchronization information packet based on a one-way overhearing mechanism. Moreover, the accurate acquisition of the synchronization ack packet’s timestamp is carried out through the use of receiving-time-plus-fixed-delay mode. Third, the joint maximum likelihood method and the minimum variance unbiased estimation method are used to estimate the clock offsets of pairwise synchronization nodes and overhearing nodes to the parent nodes, respectively, based on which the child nodes adjust their local virtual clocks. Periodically, the pairwise synchronization nodes initiate the network’s time synchronization, estimate, and broadcast the relative offset to the gateway node, assisting the upper layer child nodes in synchronizing to the gateway node. Simulation results show that the proposed method not only achieves the millisecond level synchronization accuracy but also reduces the synchronization energy consumption and thus improves the network lifetime.
{"title":"New timestamp mark–based energy efficient time synchronization method for wireless sensor networks","authors":"Yourui Huang, Gang Zhang, Min Kong, Fugui He","doi":"10.1177/15501329221135516","DOIUrl":"https://doi.org/10.1177/15501329221135516","url":null,"abstract":"Aimed at the demands of wireless sensor networks for high energy-efficient time synchronization, the reduction of synchronization energy consumption is studied from the aspects of both accurate timestamps marking and synchronous information transmission mechanism. First, the network is divided into several parent–child groups periodically. The group-wise pair selection algorithm is used to select the network’s pairwise synchronization nodes, and chain-type network topology is thus generated. Second, the sequential multi-hop synchronization algorithm is introduced to realize the synchronization information exchange among pairwise synchronization nodes. The overhearing synchronization (OS) nodes obtain the synchronization information packet based on a one-way overhearing mechanism. Moreover, the accurate acquisition of the synchronization ack packet’s timestamp is carried out through the use of receiving-time-plus-fixed-delay mode. Third, the joint maximum likelihood method and the minimum variance unbiased estimation method are used to estimate the clock offsets of pairwise synchronization nodes and overhearing nodes to the parent nodes, respectively, based on which the child nodes adjust their local virtual clocks. Periodically, the pairwise synchronization nodes initiate the network’s time synchronization, estimate, and broadcast the relative offset to the gateway node, assisting the upper layer child nodes in synchronizing to the gateway node. Simulation results show that the proposed method not only achieves the millisecond level synchronization accuracy but also reduces the synchronization energy consumption and thus improves the network lifetime.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46249001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221136978
Yong Shen, Xiaokang Tang, X. Zhang, Yong-zhuang Zhou, H. Zou
As quantum computing techniques develop rapidly, the security of classical communication, which is usually based on public key encryption algorithm, is under great threat. Therefore, a key establishment method with physics base is demanding, especially for Internet of Things devices, where energy and computational power is quite limited. In this article, we present a flexible continuous-wave quantum cryptography scheme for Internet of Things systems. In this configuration, the IoT controller contains a narrow linewidth laser as a real local oscillator. Thus, it is capable of working as either a host or a client in quantum key distribution with remote servers, and efficiently generating quantum random numbers for quantum key distribution, as well as one time pad communication with deployed sensors. The security of the scheme is analyzed under the assumption of collective attacks in the asymptotic regime, and feasibility is theoretically verified with typical channel and commercial device parameters.
{"title":"A flexible continuous-wave quantum cryptography scheme with zero-trust security for Internet of Things","authors":"Yong Shen, Xiaokang Tang, X. Zhang, Yong-zhuang Zhou, H. Zou","doi":"10.1177/15501329221136978","DOIUrl":"https://doi.org/10.1177/15501329221136978","url":null,"abstract":"As quantum computing techniques develop rapidly, the security of classical communication, which is usually based on public key encryption algorithm, is under great threat. Therefore, a key establishment method with physics base is demanding, especially for Internet of Things devices, where energy and computational power is quite limited. In this article, we present a flexible continuous-wave quantum cryptography scheme for Internet of Things systems. In this configuration, the IoT controller contains a narrow linewidth laser as a real local oscillator. Thus, it is capable of working as either a host or a client in quantum key distribution with remote servers, and efficiently generating quantum random numbers for quantum key distribution, as well as one time pad communication with deployed sensors. The security of the scheme is analyzed under the assumption of collective attacks in the asymptotic regime, and feasibility is theoretically verified with typical channel and commercial device parameters.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46839446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221133291
David Miguel-Santiago, M. E. Rivero-Angeles, L. Garay-Jimenéz, I. Orea-Flores, B. Tovar-Corona
Crowdsensing systems are developed in order to use the computational and communication capabilities of registered users to monitor specific variables and phenomena in an opportunistic manner. As such, the Quality of Experience is not easily attained since these systems heavily rely on the user’s behavior and willingness to cooperate whenever an event with certain interest needs to be monitored. In this work, we analyze the data acquisition phase, where pedestrians opportunistically transmit to vehicles to further disseminate it in the city according to their trajectory. This highly dynamic environment (sensors and data sinks are mobile, and the number of users varies according to the region and time) poses many challenges for properly operating a crowdsensing system. We first study the statistical properties of vehicular traffic in different regions of Luxembourg City where pedestrians share their computational resources and send data to passing cars. Then we propose an Erlang distribution to model the vehicles’ dwelling times and develop a Markov chain accordingly. We model the system using two different queues: we use a single server queue to model the vehicle traffic, while we use an infinite server queue system to model the pedestrian traffic.
{"title":"Teletraffic analysis of a mobile crowdsensing system: The pedestrian-to-vehicle scenario","authors":"David Miguel-Santiago, M. E. Rivero-Angeles, L. Garay-Jimenéz, I. Orea-Flores, B. Tovar-Corona","doi":"10.1177/15501329221133291","DOIUrl":"https://doi.org/10.1177/15501329221133291","url":null,"abstract":"Crowdsensing systems are developed in order to use the computational and communication capabilities of registered users to monitor specific variables and phenomena in an opportunistic manner. As such, the Quality of Experience is not easily attained since these systems heavily rely on the user’s behavior and willingness to cooperate whenever an event with certain interest needs to be monitored. In this work, we analyze the data acquisition phase, where pedestrians opportunistically transmit to vehicles to further disseminate it in the city according to their trajectory. This highly dynamic environment (sensors and data sinks are mobile, and the number of users varies according to the region and time) poses many challenges for properly operating a crowdsensing system. We first study the statistical properties of vehicular traffic in different regions of Luxembourg City where pedestrians share their computational resources and send data to passing cars. Then we propose an Erlang distribution to model the vehicles’ dwelling times and develop a Markov chain accordingly. We model the system using two different queues: we use a single server queue to model the vehicle traffic, while we use an infinite server queue system to model the pedestrian traffic.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46173777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221134479
Xin Xia, Yunlong Ma, Ye Luo, Jianwei Lu
Traditional electronic medical record systems in hospitals rely on healthcare workers to manually enter patient information, resulting in healthcare workers having to spend a significant amount of time each day filling out electronic medical records. This inefficient interaction seriously affects the communication between doctors and patients and reduces the speed at which doctors can diagnose patients’ conditions. The rapid development of deep learning–based speech recognition technology promises to improve this situation. In this work, we build an online electronic medical record system based on speech interaction. The system integrates a medical linguistic knowledge base, a specialized language model, a personalized acoustic model, and a fault-tolerance mechanism. Hence, we propose and develop an advanced electronic medical record system approach with multi-accent adaptive technology for avoiding the mistakes caused by accents, and it improves the accuracy of speech recognition obviously. For testing the proposed speech recognition electronic medical record system, we construct medical speech recognition data sets using audio and electronic medical records from real medical environments. On the data sets from real clinical scenarios, our proposed algorithm significantly outperforms other machine learning algorithms. Furthermore, compared to traditional electronic medical record systems that rely on keyboard inputs, our system is much more efficient, and its accuracy rate increases with the increasing online time of the proposed system. Our results show that the proposed electronic medical record system is expected to revolutionize the traditional working approach of clinical departments, and it serves more efficient in clinics with low time consumption compared with traditional electronic medical record systems depending on keyboard inputs, which has less recording mistakes and lows down the time consumption in modification of medical recordings; due to the proposed speech recognition electronic medical record system is built on knowledge database of medical terms, so it has a good generalized application and adaption in the clinical scenarios for hospitals.
{"title":"An online intelligent electronic medical record system via speech recognition","authors":"Xin Xia, Yunlong Ma, Ye Luo, Jianwei Lu","doi":"10.1177/15501329221134479","DOIUrl":"https://doi.org/10.1177/15501329221134479","url":null,"abstract":"Traditional electronic medical record systems in hospitals rely on healthcare workers to manually enter patient information, resulting in healthcare workers having to spend a significant amount of time each day filling out electronic medical records. This inefficient interaction seriously affects the communication between doctors and patients and reduces the speed at which doctors can diagnose patients’ conditions. The rapid development of deep learning–based speech recognition technology promises to improve this situation. In this work, we build an online electronic medical record system based on speech interaction. The system integrates a medical linguistic knowledge base, a specialized language model, a personalized acoustic model, and a fault-tolerance mechanism. Hence, we propose and develop an advanced electronic medical record system approach with multi-accent adaptive technology for avoiding the mistakes caused by accents, and it improves the accuracy of speech recognition obviously. For testing the proposed speech recognition electronic medical record system, we construct medical speech recognition data sets using audio and electronic medical records from real medical environments. On the data sets from real clinical scenarios, our proposed algorithm significantly outperforms other machine learning algorithms. Furthermore, compared to traditional electronic medical record systems that rely on keyboard inputs, our system is much more efficient, and its accuracy rate increases with the increasing online time of the proposed system. Our results show that the proposed electronic medical record system is expected to revolutionize the traditional working approach of clinical departments, and it serves more efficient in clinics with low time consumption compared with traditional electronic medical record systems depending on keyboard inputs, which has less recording mistakes and lows down the time consumption in modification of medical recordings; due to the proposed speech recognition electronic medical record system is built on knowledge database of medical terms, so it has a good generalized application and adaption in the clinical scenarios for hospitals.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41599382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221135160
Jianrong Wang, P. Zhang, Wei Bai, Guoyuan Yang, Yunyun Yang
In the future, the Internet of things will reduce the cell radius and increase the number of low-power nodes to support thousands of times of traffic growth under 5G. As a virtual multiple input multiple output technology, cooperative communication technology can solve these problems effectively. According to the evolution characteristics of cooperative communication networks, a multi-domain cooperative communication network evolution model with preferential attachment and random attachment is constructed in this article. And then, the network properties and robustness are analyzed using the mean-field method and different attacks. Aiming at the resource constraints and resource allocation problems of communication nodes, a relay selection strategy based on the combination of maximum degree and minimum clustering coefficient is proposed. The simulation results show that the relay node selection strategy based on the combination of maximum degree and minimum clustering coefficient has significant advantages in selection steps and selection time, which greatly enhanced the performance of relay selection in multi-domain cooperative communication networks. Through real-time monitoring and updating of the performance and security indicators of the multi-domain cooperative communication networks, it provides a strong guarantee for the node deployment and security management of the Internet of things cooperative communication system.
{"title":"Evolutionary modeling and robustness analysis of multi-domain cooperative communication network under the environment of Internet of things","authors":"Jianrong Wang, P. Zhang, Wei Bai, Guoyuan Yang, Yunyun Yang","doi":"10.1177/15501329221135160","DOIUrl":"https://doi.org/10.1177/15501329221135160","url":null,"abstract":"In the future, the Internet of things will reduce the cell radius and increase the number of low-power nodes to support thousands of times of traffic growth under 5G. As a virtual multiple input multiple output technology, cooperative communication technology can solve these problems effectively. According to the evolution characteristics of cooperative communication networks, a multi-domain cooperative communication network evolution model with preferential attachment and random attachment is constructed in this article. And then, the network properties and robustness are analyzed using the mean-field method and different attacks. Aiming at the resource constraints and resource allocation problems of communication nodes, a relay selection strategy based on the combination of maximum degree and minimum clustering coefficient is proposed. The simulation results show that the relay node selection strategy based on the combination of maximum degree and minimum clustering coefficient has significant advantages in selection steps and selection time, which greatly enhanced the performance of relay selection in multi-domain cooperative communication networks. Through real-time monitoring and updating of the performance and security indicators of the multi-domain cooperative communication networks, it provides a strong guarantee for the node deployment and security management of the Internet of things cooperative communication system.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41601399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1177/15501329221135060
Mingcheng Gao, Ruiheng Wang, Lu Wang, Yang Xin, Hongliang Zhu
Cross-domain identity association of network entities is a significant research challenge and a vital issue of practical value in relationship discovery and service recommendation between things in the Internet of things, cyberspace resources surveying mapping, threat tracking, and intelligent recommendation. This task usually adds additional difficulty to the research in practical applications due to the need to link across multiple platforms. The existing entity identity association methods in cross-domain networks mainly use the attribute information, generated content, and network structure information of network user entities but do not fully use the inherent strong positioning characteristics of active nodes in the network. In this article, we analyzed the structural characteristics of existing relational networks. We found that the hub node has the role of identity association positioning, and the importance of identity association reflected by different nodes is different. Moreover, we creatively designed a network representation learning method. We proposed a supervised learning identity association model combined with a representation learning method. Experiments on the public data set show that using the identity association method proposed in this article, the ranking accuracy of user entity association similarity is about 30% and 25% higher than the existing two typical methods.
{"title":"Cross-domain entity identity association analysis and prediction based on representation learning","authors":"Mingcheng Gao, Ruiheng Wang, Lu Wang, Yang Xin, Hongliang Zhu","doi":"10.1177/15501329221135060","DOIUrl":"https://doi.org/10.1177/15501329221135060","url":null,"abstract":"Cross-domain identity association of network entities is a significant research challenge and a vital issue of practical value in relationship discovery and service recommendation between things in the Internet of things, cyberspace resources surveying mapping, threat tracking, and intelligent recommendation. This task usually adds additional difficulty to the research in practical applications due to the need to link across multiple platforms. The existing entity identity association methods in cross-domain networks mainly use the attribute information, generated content, and network structure information of network user entities but do not fully use the inherent strong positioning characteristics of active nodes in the network. In this article, we analyzed the structural characteristics of existing relational networks. We found that the hub node has the role of identity association positioning, and the importance of identity association reflected by different nodes is different. Moreover, we creatively designed a network representation learning method. We proposed a supervised learning identity association model combined with a representation learning method. Experiments on the public data set show that using the identity association method proposed in this article, the ranking accuracy of user entity association similarity is about 30% and 25% higher than the existing two typical methods.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47701323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1177/15501329221132496
B. Rehman, M. I. Babar, Arbab Waheed Ahmad, Mohammad Amir, Wasim Habib, Muhammad Farooq, Gamil Abdel Azim
Fifth-generation wireless communications provide several benefits, including high throughput, lower latency, massive connectivity, considerable improvement in the number of users, higher base station capacity, and achieved quality of service. Non-orthogonal multiple access, an effective approach for sharing the same radio resources, has been highlighted as a viable technology in the fifth-generation wireless networks to achieve the demands of available bandwidth, user connectivity, and application latency. Non-orthogonal multiple access and heterogeneous networks have recently emerged as promising network infrastructures for enhancing the spectrum capacity and accommodating more users by sharing the same resources with high throughput. This potential capability has made the non-orthogonal multiple access–enabled heterogeneous networks a new research topic in the modern era. In this survey, the concept of non-orthogonal multiple access and its significance in different emerging technologies has been well explored. Furthermore, this survey covers a systematic overview of the state-of the-art techniques based on non-orthogonal multiple access–enabled heterogeneous networks and devising taxonomy for uplink non-orthogonal multiple access–enabled heterogeneous networks. In addition, this survey provides critical insights and identifies several open research challenges considering the uplink non-orthogonal multiple access–enabled heterogeneous networks.
{"title":"Uplink non-orthogonal multiple access in heterogeneous networks: A review of recent advances and open research challenges","authors":"B. Rehman, M. I. Babar, Arbab Waheed Ahmad, Mohammad Amir, Wasim Habib, Muhammad Farooq, Gamil Abdel Azim","doi":"10.1177/15501329221132496","DOIUrl":"https://doi.org/10.1177/15501329221132496","url":null,"abstract":"Fifth-generation wireless communications provide several benefits, including high throughput, lower latency, massive connectivity, considerable improvement in the number of users, higher base station capacity, and achieved quality of service. Non-orthogonal multiple access, an effective approach for sharing the same radio resources, has been highlighted as a viable technology in the fifth-generation wireless networks to achieve the demands of available bandwidth, user connectivity, and application latency. Non-orthogonal multiple access and heterogeneous networks have recently emerged as promising network infrastructures for enhancing the spectrum capacity and accommodating more users by sharing the same resources with high throughput. This potential capability has made the non-orthogonal multiple access–enabled heterogeneous networks a new research topic in the modern era. In this survey, the concept of non-orthogonal multiple access and its significance in different emerging technologies has been well explored. Furthermore, this survey covers a systematic overview of the state-of the-art techniques based on non-orthogonal multiple access–enabled heterogeneous networks and devising taxonomy for uplink non-orthogonal multiple access–enabled heterogeneous networks. In addition, this survey provides critical insights and identifies several open research challenges considering the uplink non-orthogonal multiple access–enabled heterogeneous networks.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65535455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1177/15501329221133765
Shangbin Han, Qianhong Wu, Yang Yang
With the popularization of Internet of things, its network security has aroused widespread concern. Anomaly detection is one of the important technologies to protect network security. To meet the needs of automatic and intelligent detection, supervised machine learning is widely used in anomaly detection. However, the existing schemes ignore the problem of data quality, which leads to the unsatisfactory detection effect in practice. Therefore, practitioners may not know which algorithm to choose due to the lack of review and evaluation of anomaly detection methods under low-quality data. To address this problem, we give a detailed review and evaluation of six supervised anomaly detection methods, as well as release the core code of feature extractor for pcap format traffic traces and anomaly detection methods for reuse. We evaluate the methods on two public datasets (one is a simulated network dataset and the other is a real Internet of things dataset). We believe that our work and insights will help practitioners quickly understand and develop anomaly detection schemes for Internet of things and can provide reference for future research.
{"title":"Machine learning for Internet of things anomaly detection under low-quality data","authors":"Shangbin Han, Qianhong Wu, Yang Yang","doi":"10.1177/15501329221133765","DOIUrl":"https://doi.org/10.1177/15501329221133765","url":null,"abstract":"With the popularization of Internet of things, its network security has aroused widespread concern. Anomaly detection is one of the important technologies to protect network security. To meet the needs of automatic and intelligent detection, supervised machine learning is widely used in anomaly detection. However, the existing schemes ignore the problem of data quality, which leads to the unsatisfactory detection effect in practice. Therefore, practitioners may not know which algorithm to choose due to the lack of review and evaluation of anomaly detection methods under low-quality data. To address this problem, we give a detailed review and evaluation of six supervised anomaly detection methods, as well as release the core code of feature extractor for pcap format traffic traces and anomaly detection methods for reuse. We evaluate the methods on two public datasets (one is a simulated network dataset and the other is a real Internet of things dataset). We believe that our work and insights will help practitioners quickly understand and develop anomaly detection schemes for Internet of things and can provide reference for future research.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41793024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1177/15501329221126609
Yahya M. Tashtoush, Dirar A. Darweesh, Ola Karajeh, Omar M. Darwish, Majdi Maabreh, Safa Swedat, Rawan Koraysh, O. Almousa, Nasser Alsaedi
The emergence of fifth generation networks opens the doors for Internet of Things environment to spread widely. The number of connected devices to fifth generation networks is expected to increase to more than 1.7 billion users by 2025. Each year, millions of modern devices go online at the beginning of the school year and after the holidays, and you can even notice the publicity of Internet of Things devices swinging with the seasons. Nowadays, these devices are considered to be very important to our daily life. That is because they provide power to our homes, organize our work operations and let communications more suitable. As a result of the increasing number of connected devices to fifth generation networks, the necessity to protect these Internet of Things devices against different types of cyber-attacks is also increased. For this reason, many researchers proposed different protocols and schemes to achieve the security of the Internet of Things devices. In this article, we introduce a survey of some protocols proposed by researchers in different domains and make a comparative study between them in terms of their category, authentication process, evaluation methodology, advantages, target, development year and applications within Internet of Things environment. The objective of this survey is to provide researchers with rich information about these protocols and their uses within Internet of Things systems, whether they can be used for cloud radio access networks, Internet of Things general purposes, telecommunications systems, e-healthcare systems or drone delivery service systems. It can also assist them in choosing the proper protocol to be used according to the type of their Internet of Things system.
{"title":"Survey on authentication and security protocols and schemes over 5G networks","authors":"Yahya M. Tashtoush, Dirar A. Darweesh, Ola Karajeh, Omar M. Darwish, Majdi Maabreh, Safa Swedat, Rawan Koraysh, O. Almousa, Nasser Alsaedi","doi":"10.1177/15501329221126609","DOIUrl":"https://doi.org/10.1177/15501329221126609","url":null,"abstract":"The emergence of fifth generation networks opens the doors for Internet of Things environment to spread widely. The number of connected devices to fifth generation networks is expected to increase to more than 1.7 billion users by 2025. Each year, millions of modern devices go online at the beginning of the school year and after the holidays, and you can even notice the publicity of Internet of Things devices swinging with the seasons. Nowadays, these devices are considered to be very important to our daily life. That is because they provide power to our homes, organize our work operations and let communications more suitable. As a result of the increasing number of connected devices to fifth generation networks, the necessity to protect these Internet of Things devices against different types of cyber-attacks is also increased. For this reason, many researchers proposed different protocols and schemes to achieve the security of the Internet of Things devices. In this article, we introduce a survey of some protocols proposed by researchers in different domains and make a comparative study between them in terms of their category, authentication process, evaluation methodology, advantages, target, development year and applications within Internet of Things environment. The objective of this survey is to provide researchers with rich information about these protocols and their uses within Internet of Things systems, whether they can be used for cloud radio access networks, Internet of Things general purposes, telecommunications systems, e-healthcare systems or drone delivery service systems. It can also assist them in choosing the proper protocol to be used according to the type of their Internet of Things system.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47705245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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