Pub Date : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340159
Fernanda Magalhães, J. Magalhães
Nowadays there are many Domain Name System (DNS) firewall solutions to prevent users to access malicious domains. These can provide real time protection and block illegitimate communications. Most of these solutions are based on known malicious domain names lists (blocklists) that are being constantly updated. However, this way, it is only possible to block malicious communications for known malicious domains, leaving out many others that are malicious but have not yet been updated in the blocklists. In this paper we present a study on the usefulness of adopting machine learning to detect malicious domain names. From a large set of domain names classified in-advance as malicious or benign an enriched dataset with multiple features was created and analyzed. The exploratory analysis and the data preparation tasks were carried out and the results achieved by different machine learning classification algorithms. Depending on the classification algorithm, the accuracy results varied between 75% and 92% and the classification time ranged between 2.77 seconds and 5320 seconds. These results are interesting in that they make it possible to classify a new domain as malicious or not in a short time and with good hit rate.
{"title":"Adopting Machine Learning to Support the Detection of Malicious Domain Names","authors":"Fernanda Magalhães, J. Magalhães","doi":"10.1109/IOTSMS52051.2020.9340159","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340159","url":null,"abstract":"Nowadays there are many Domain Name System (DNS) firewall solutions to prevent users to access malicious domains. These can provide real time protection and block illegitimate communications. Most of these solutions are based on known malicious domain names lists (blocklists) that are being constantly updated. However, this way, it is only possible to block malicious communications for known malicious domains, leaving out many others that are malicious but have not yet been updated in the blocklists. In this paper we present a study on the usefulness of adopting machine learning to detect malicious domain names. From a large set of domain names classified in-advance as malicious or benign an enriched dataset with multiple features was created and analyzed. The exploratory analysis and the data preparation tasks were carried out and the results achieved by different machine learning classification algorithms. Depending on the classification algorithm, the accuracy results varied between 75% and 92% and the classification time ranged between 2.77 seconds and 5320 seconds. These results are interesting in that they make it possible to classify a new domain as malicious or not in a short time and with good hit rate.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123952798","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340215
Sai Mounika Tadaka, L. Tawalbeh
A Blockchain is the collection of the blocks consisting of digital assets, and these blocks with digital information connect like a chain stored through a node in a database. This paper gives an overview of Blockchain and its keywords and Blockchain-based applications in different areas. Specifically includes how Blockchain helps in the healthcare industry, prevent healthcare frauds, storing and managing Electronic Health Records (EHR), Blockchain based solution in industry 4.0 applications, Blockchain in the cyber-physical systems, Blockchain-based medical cyber-physical systems and some general forms of Blockchain. Concluding with some of the challenges in the Blockchain technology and proposed solutions.
{"title":"Applications of Blockchain in Healthcare, Industry 4, and Cyber-Physical Systems","authors":"Sai Mounika Tadaka, L. Tawalbeh","doi":"10.1109/IOTSMS52051.2020.9340215","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340215","url":null,"abstract":"A Blockchain is the collection of the blocks consisting of digital assets, and these blocks with digital information connect like a chain stored through a node in a database. This paper gives an overview of Blockchain and its keywords and Blockchain-based applications in different areas. Specifically includes how Blockchain helps in the healthcare industry, prevent healthcare frauds, storing and managing Electronic Health Records (EHR), Blockchain based solution in industry 4.0 applications, Blockchain in the cyber-physical systems, Blockchain-based medical cyber-physical systems and some general forms of Blockchain. Concluding with some of the challenges in the Blockchain technology and proposed solutions.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"87 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120894218","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 : 2020-12-14DOI: 10.1109/iotsms52051.2020.9340220
{"title":"IOTSMS 2020 Message from the General Chairs","authors":"","doi":"10.1109/iotsms52051.2020.9340220","DOIUrl":"https://doi.org/10.1109/iotsms52051.2020.9340220","url":null,"abstract":"","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126753601","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340202
Vishakha Subhash Supekar, A. Ahmadinia
The changing environment plays a vital role in the health of humans as well as animals. Due to the grave impacts of pollution and increased temperature on human health, it is of utmost importance to monitor the environment parameters at every step. With the recent developments in the Internet of Things (IoT), monitoring these parameters in real-time has become possible and cost-effective. In this paper, we have designed and implemented a web application to demonstrate an intelligent temperature and humidity reporting system using IoT and cloud. This application aims to provide a visual map for the users to analyze the temperature and humidity in different areas to make an informed decision. The proposed system provides a new solution by utilizing the sensor activity on various applications using Amazon Web Services that can be used as a prototype in strengthening real-time localized temperature and humidity data monitoring in many applications such as Nest, activating farm sprinklers based on weather data, and helping patients sensitive to high temperature and high humidity to take prompt action upon real-time notification on change in temperature or humidity.
不断变化的环境对人类和动物的健康起着至关重要的作用。由于污染和温度升高对人类健康的严重影响，监测每一步的环境参数是至关重要的。随着物联网(IoT)的最新发展，实时监控这些参数已经成为可能，并且具有成本效益。在本文中，我们设计并实现了一个web应用程序来演示使用物联网和云的智能温湿度报告系统。该应用程序旨在为用户提供一个可视化的地图，以分析不同地区的温度和湿度，从而做出明智的决定。该系统提供了一种新的解决方案，通过使用Amazon Web Services的各种应用程序利用传感器活动，可以作为原型，在Nest等许多应用程序中加强实时局部温度和湿度数据监测，根据天气数据激活农场洒水装置，并帮助对高温高湿敏感的患者在实时通知温度或湿度变化时及时采取行动。
{"title":"Sensor Data Visualization on Google Maps using AWS, and IoT Discovery Board","authors":"Vishakha Subhash Supekar, A. Ahmadinia","doi":"10.1109/IOTSMS52051.2020.9340202","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340202","url":null,"abstract":"The changing environment plays a vital role in the health of humans as well as animals. Due to the grave impacts of pollution and increased temperature on human health, it is of utmost importance to monitor the environment parameters at every step. With the recent developments in the Internet of Things (IoT), monitoring these parameters in real-time has become possible and cost-effective. In this paper, we have designed and implemented a web application to demonstrate an intelligent temperature and humidity reporting system using IoT and cloud. This application aims to provide a visual map for the users to analyze the temperature and humidity in different areas to make an informed decision. The proposed system provides a new solution by utilizing the sensor activity on various applications using Amazon Web Services that can be used as a prototype in strengthening real-time localized temperature and humidity data monitoring in many applications such as Nest, activating farm sprinklers based on weather data, and helping patients sensitive to high temperature and high humidity to take prompt action upon real-time notification on change in temperature or humidity.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126759241","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 : 2020-12-14DOI: 10.1109/iotsms52051.2020.9340193
{"title":"IOTSMS 2020 Table of Contents","authors":"","doi":"10.1109/iotsms52051.2020.9340193","DOIUrl":"https://doi.org/10.1109/iotsms52051.2020.9340193","url":null,"abstract":"","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122056893","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340161
Raghad Al-Syouf, M. Shurman, A. Alma'aitah, Sharhabeel H. Alnabelsi
Energy conservation and high data rate requirements are considered as major challenges in wireless networks. In this work, we investigate the concept of three-layered networks, such that the proposed theory consists of smart grids, Mobile Ad-hoc Network (MANET), and satellite networks where all can be employed in different IoT platforms. We developed four performance metrics that applied in the MANET layer for multi-gateway selection. Also, we provided the MANET layer with a proper routing protocol which can reduce the amount of traffic pressure. The experimental results show the performance of our proposed approach in terms of quality, average delay, and the network load balance for different network’s conditions. Moreover, the numerical results prove that the proposed design for MANET can improve throughput performance, gateway lifetime, and packet transmission rate.
{"title":"A Novel Gateway Selection Protocol for Three-layers Integrated Wireless Networks","authors":"Raghad Al-Syouf, M. Shurman, A. Alma'aitah, Sharhabeel H. Alnabelsi","doi":"10.1109/IOTSMS52051.2020.9340161","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340161","url":null,"abstract":"Energy conservation and high data rate requirements are considered as major challenges in wireless networks. In this work, we investigate the concept of three-layered networks, such that the proposed theory consists of smart grids, Mobile Ad-hoc Network (MANET), and satellite networks where all can be employed in different IoT platforms. We developed four performance metrics that applied in the MANET layer for multi-gateway selection. Also, we provided the MANET layer with a proper routing protocol which can reduce the amount of traffic pressure. The experimental results show the performance of our proposed approach in terms of quality, average delay, and the network load balance for different network’s conditions. Moreover, the numerical results prove that the proposed design for MANET can improve throughput performance, gateway lifetime, and packet transmission rate.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126915097","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340200
Yassine Boufenneche, Rafik Zitouni, L. George, Nawel Gharbi
Time Slotted Channel Hopping (TSCH) is a new Medium Access Control (MAC) protocol proposed by the IEEE 802.15.4e standard. It is designed to meet the requirements of industrial networks, such as high Packet Delivery Ratio (PDR) and bounded delays, along with low energy consumption. TSCH is now the basis of a full stack for Industrial Internet of Things (IIoT) proposed by the International Engineering Task Force (IETF), known as 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e). Since 6TiSCH networks are expected to offer high performance and fast bootstrapping, the network formation time could be impacted by the network size and the rate of control packets. In this paper, we demonstrate that non cooperative nodes, which can be malicious, could also drastically increase the network joining time. First, we propose the attack model and its implementation on the 6TiSCH simulator. Then, we carry out a set of experiments for different network sizes. Finally, we show through simulation results the impact of the proposed attack on the joining time.
{"title":"Network Formation in 6TiSCH Industrial Internet of Things under Misbehaved Nodes","authors":"Yassine Boufenneche, Rafik Zitouni, L. George, Nawel Gharbi","doi":"10.1109/IOTSMS52051.2020.9340200","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340200","url":null,"abstract":"Time Slotted Channel Hopping (TSCH) is a new Medium Access Control (MAC) protocol proposed by the IEEE 802.15.4e standard. It is designed to meet the requirements of industrial networks, such as high Packet Delivery Ratio (PDR) and bounded delays, along with low energy consumption. TSCH is now the basis of a full stack for Industrial Internet of Things (IIoT) proposed by the International Engineering Task Force (IETF), known as 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e). Since 6TiSCH networks are expected to offer high performance and fast bootstrapping, the network formation time could be impacted by the network size and the rate of control packets. In this paper, we demonstrate that non cooperative nodes, which can be malicious, could also drastically increase the network joining time. First, we propose the attack model and its implementation on the 6TiSCH simulator. Then, we carry out a set of experiments for different network sizes. Finally, we show through simulation results the impact of the proposed attack on the joining time.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122299842","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340197
Safuriyawu Ahmed, Frédéric Le Mouël, N. Stouls
Pipeline networks dominate the oil and gas midstream sector, and although the safest means of transportation for oil and gas products, they are susceptible to failures. These failures are due to manufacturing defects, environmental effects, material degradation, or third party interference through sabotage and vandalism. Internet of Things (IoT)-based solutions are promising to address these by monitoring and predicting failures. However, some challenges remain in the deployment of industrial IoT-based solutions, as the reliability, the robustness, the maintainability, the scalability, the energy consumption, etc. This paper is therefore aimed at highlighting potential solutions for detection and mitigation of pipeline failures while addressing the robustness, the cost and scalability issues of such approach efficiently across the network infrastructure, data and service layers.
{"title":"Resilient IoT-based Monitoring System for Crude Oil Pipelines","authors":"Safuriyawu Ahmed, Frédéric Le Mouël, N. Stouls","doi":"10.1109/IOTSMS52051.2020.9340197","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340197","url":null,"abstract":"Pipeline networks dominate the oil and gas midstream sector, and although the safest means of transportation for oil and gas products, they are susceptible to failures. These failures are due to manufacturing defects, environmental effects, material degradation, or third party interference through sabotage and vandalism. Internet of Things (IoT)-based solutions are promising to address these by monitoring and predicting failures. However, some challenges remain in the deployment of industrial IoT-based solutions, as the reliability, the robustness, the maintainability, the scalability, the energy consumption, etc. This paper is therefore aimed at highlighting potential solutions for detection and mitigation of pipeline failures while addressing the robustness, the cost and scalability issues of such approach efficiently across the network infrastructure, data and service layers.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430903","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340212
Fahem Zerrouki, Samir Ouchani, Hafida Bouarfa
Physical Unclonable Function is an innovative hardware security primitives that exploit the physical characteristics of a physical object to generate a unique identifier, which play the role of the object’s fingerprint. Silicon PUF, a popular type of PUFs, exploits the variation in the manufacturing process of integrated circuits (ICs). It needs an input called challenge to generate the response as an output. In addition, of classical attacks, PUFs are vulnerable to physical and modeling attacks. The performance of the PUFs is measured by several metrics like reliability, uniqueness and uniformity. So as an evidence, the main goal is to provide a complete tool that checks the strength and quantifies the performance of a given physical unconscionable function. This paper provides a tool and develops a set of metrics that can achieve safely the proposed goal.
{"title":"Quantifying Security and Performance of Physical Unclonable Functions","authors":"Fahem Zerrouki, Samir Ouchani, Hafida Bouarfa","doi":"10.1109/IOTSMS52051.2020.9340212","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340212","url":null,"abstract":"Physical Unclonable Function is an innovative hardware security primitives that exploit the physical characteristics of a physical object to generate a unique identifier, which play the role of the object’s fingerprint. Silicon PUF, a popular type of PUFs, exploits the variation in the manufacturing process of integrated circuits (ICs). It needs an input called challenge to generate the response as an output. In addition, of classical attacks, PUFs are vulnerable to physical and modeling attacks. The performance of the PUFs is measured by several metrics like reliability, uniqueness and uniformity. So as an evidence, the main goal is to provide a complete tool that checks the strength and quantifies the performance of a given physical unconscionable function. This paper provides a tool and develops a set of metrics that can achieve safely the proposed goal.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127153631","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 : 2020-12-14DOI: 10.1109/IOTSMS52051.2020.9340229
Ali Safari Khatouni, M. Bauer, H. Lutfiyya
Building monitoring and management are some of the important components of smart cities. It provides valuable information to the city manager and power supplier to better optimize their resources. With a steady rise in electricity prices in recent years, the importance of efficient use of the Heating, Ventilating, and Air-Conditioning (HVAC) systems becomes vital since they contribute to more than 10% of building power consumption. Given the growth on the Internet of Things (IoT) more HVAC equipment is being deployed with sensors. These sensors can produce large amounts of data that can be transformed into knowledge about the operation of a building. In this paper, we examine a large amount of sensor data from a building with more than 200 rooms. We analyze the power consumption of the building and compare different algorithms to predict the power consumption of the building using indoor and outdoor temperatures. We compare 8 different Machine Learning (ML) algorithms in order to examine their effectiveness. We then cluster rooms based on the temperature settings. Our evaluation results illustrate reasonable prediction accuracy and pinpoint several clusters with an inefficient temperature setting. The results can help the university to better utilize its resources and reduce the power consumption costs.
{"title":"Indoor Temperature Characterization and its Implication on Power Consumption in a Campus Building","authors":"Ali Safari Khatouni, M. Bauer, H. Lutfiyya","doi":"10.1109/IOTSMS52051.2020.9340229","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340229","url":null,"abstract":"Building monitoring and management are some of the important components of smart cities. It provides valuable information to the city manager and power supplier to better optimize their resources. With a steady rise in electricity prices in recent years, the importance of efficient use of the Heating, Ventilating, and Air-Conditioning (HVAC) systems becomes vital since they contribute to more than 10% of building power consumption. Given the growth on the Internet of Things (IoT) more HVAC equipment is being deployed with sensors. These sensors can produce large amounts of data that can be transformed into knowledge about the operation of a building. In this paper, we examine a large amount of sensor data from a building with more than 200 rooms. We analyze the power consumption of the building and compare different algorithms to predict the power consumption of the building using indoor and outdoor temperatures. We compare 8 different Machine Learning (ML) algorithms in order to examine their effectiveness. We then cluster rooms based on the temperature settings. Our evaluation results illustrate reasonable prediction accuracy and pinpoint several clusters with an inefficient temperature setting. The results can help the university to better utilize its resources and reduce the power consumption costs.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131484093","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：