In this paper, we propose a machine learning-based profiling attack on the prime multiplication operation of RSA's key generation algorithm. The proposed attack takes advantage of the fact that a prime word value, which is the data storage unit, is loaded in the process of the multiplication operation for generating a modulus. We selected a commonly used product-scanning method as a multiplication algorithm. Then we collected the power consumption traces and constructed a profile of the secret prime value based on machine learning. In addition, the success rate of the attack was measured within a single trace to perform a realistic attack during the key generation operation. The secret prime values were derived with a maximum success rate of 99.8% in a single trace. Based on this, this paper suggests that if the secret value is an operand of the multiplication operation, there may be vulnerability against side-channel attacks because of the characteristics of the multiplication algorithm.1
{"title":"Machine Learning-Based Profiling Attack Method in RSA Prime Multiplication","authors":"Han-Byeol Park, Bo-Yeon Sim, Dong‐Guk Han","doi":"10.1145/3440943.3444730","DOIUrl":"https://doi.org/10.1145/3440943.3444730","url":null,"abstract":"In this paper, we propose a machine learning-based profiling attack on the prime multiplication operation of RSA's key generation algorithm. The proposed attack takes advantage of the fact that a prime word value, which is the data storage unit, is loaded in the process of the multiplication operation for generating a modulus. We selected a commonly used product-scanning method as a multiplication algorithm. Then we collected the power consumption traces and constructed a profile of the secret prime value based on machine learning. In addition, the success rate of the attack was measured within a single trace to perform a realistic attack during the key generation operation. The secret prime values were derived with a maximum success rate of 99.8% in a single trace. Based on this, this paper suggests that if the secret value is an operand of the multiplication operation, there may be vulnerability against side-channel attacks because of the characteristics of the multiplication algorithm.1","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"328 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116307956","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}
1The system can reduce the calculating workload of the IoT development board, as well as lowering the power consumption and guard the pool against water pollution. The intelligent feeding system offered by this study can effectively ease the workforce of the aquaculture industry. In the future, cage culture can also implement such a method to increase the safety of the operators. According to the experimental result of this study, the approach is feasible.
{"title":"Developing Intelligent Feeding Systems based on Deep Learning","authors":"Wu-Chih Hu, Hsin-Te Wu, Jun-We Zhan, Ping-Hsin Hsieh","doi":"10.1145/3440943.3444343","DOIUrl":"https://doi.org/10.1145/3440943.3444343","url":null,"abstract":"1The system can reduce the calculating workload of the IoT development board, as well as lowering the power consumption and guard the pool against water pollution. The intelligent feeding system offered by this study can effectively ease the workforce of the aquaculture industry. In the future, cage culture can also implement such a method to increase the safety of the operators. According to the experimental result of this study, the approach is feasible.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130156138","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}
Yunsang Joo, Seungwon Lee, Hyoungju Kim, Pankoo Kim, Seong Oun Hwang, Chang Choi
Recently, research using medical big data to predict patients with high probability of disease are receiving a lot of attention. Due to the advancement of artificial intelligence, continuous research is essential in that diseases can be predicted only by computational numbers and can be prevented before they occur. Therefore, machine learning and deep learning research using medical big data for disease prediction are actively progressing. Due to the nature of medical data, diseases are rare, so there is a tendency to oversampling or under sampling that can lead to information distortion. Also, given that most machine learning-based research is based on certain predictive models, there is a risk that the predictions themselves will reflect the biases that exist. So, if you generalize the data your model will train on, or adjust the model's bias, you can get better predictions. In this white paper, we use diabetes, heart disease, and breast cancer data through several individual classifiers to get predicted values and use them as training data for one meta-model to get the final predictions. That is, by constructing a stacking ensemble model, the presence or absence of a disease is predicted, and its performance is analysed through experiments. This model trains multiple classifiers on the same data, so there is a possibility that the model will overfit the data. So, when training multiple classifiers, we compare the model with and without cross validation. In the experiment, the model using cross-validation for training showed an average of 1.4% higher performance than that of the individual single model. On the other hand, the meta-model without cross-validation shows lower performance than that of individual single models. In other words, when constructing a stacking ensemble model, high performance could be obtained only by essentially cross-validating individual single classifiers. Performing one final prediction on the predicted values of high-performance individual models will yield more stable and reliable predictions. The cross-learning-based cumulative ensemble model proposed in this paper predicts the presence or absence of a disease and can be used for medical service development and disease prevention.
{"title":"Efficient healthcare service based on Stacking Ensemble","authors":"Yunsang Joo, Seungwon Lee, Hyoungju Kim, Pankoo Kim, Seong Oun Hwang, Chang Choi","doi":"10.1145/3440943.3444727","DOIUrl":"https://doi.org/10.1145/3440943.3444727","url":null,"abstract":"Recently, research using medical big data to predict patients with high probability of disease are receiving a lot of attention. Due to the advancement of artificial intelligence, continuous research is essential in that diseases can be predicted only by computational numbers and can be prevented before they occur. Therefore, machine learning and deep learning research using medical big data for disease prediction are actively progressing. Due to the nature of medical data, diseases are rare, so there is a tendency to oversampling or under sampling that can lead to information distortion. Also, given that most machine learning-based research is based on certain predictive models, there is a risk that the predictions themselves will reflect the biases that exist. So, if you generalize the data your model will train on, or adjust the model's bias, you can get better predictions. In this white paper, we use diabetes, heart disease, and breast cancer data through several individual classifiers to get predicted values and use them as training data for one meta-model to get the final predictions. That is, by constructing a stacking ensemble model, the presence or absence of a disease is predicted, and its performance is analysed through experiments. This model trains multiple classifiers on the same data, so there is a possibility that the model will overfit the data. So, when training multiple classifiers, we compare the model with and without cross validation. In the experiment, the model using cross-validation for training showed an average of 1.4% higher performance than that of the individual single model. On the other hand, the meta-model without cross-validation shows lower performance than that of individual single models. In other words, when constructing a stacking ensemble model, high performance could be obtained only by essentially cross-validating individual single classifiers. Performing one final prediction on the predicted values of high-performance individual models will yield more stable and reliable predictions. The cross-learning-based cumulative ensemble model proposed in this paper predicts the presence or absence of a disease and can be used for medical service development and disease prevention.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133783573","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}
The application of the sensor node of the Internet of Things can help managers to grasp the abnormal information of the production equipment and achieve the goal of effective factory management. The integration of a safe control mechanism into the inspection system can reduce the cost of company. Therefore, this paper proposed an intelligent secure and reliable patrol system. It supports the efficiency patrol system and privacy of the information. It also ensures only legally authorized users have right to access the information. We built the intelligent secure and reliable patrol system by using IoT technology and designed a trusted authentication mechanism within a smart, safe and reliable patrol system. The benefits of the system are: Ensuring the security of the transmission. The system user cannot modify the inspection information arbitrarily. It can make the production maintenance mechanism sounder. It will also help companies gradually move towards the goal of Industry 4.0 smart factory to improve the production efficiency of enterprises and increase production capacity.
{"title":"An intelligent patrol system for Industry 4.0 Smart Factory","authors":"Hung-Jen Chen, Chin-Chia Hsu, Chia-Hui Liu","doi":"10.1145/3440943.3444339","DOIUrl":"https://doi.org/10.1145/3440943.3444339","url":null,"abstract":"The application of the sensor node of the Internet of Things can help managers to grasp the abnormal information of the production equipment and achieve the goal of effective factory management. The integration of a safe control mechanism into the inspection system can reduce the cost of company. Therefore, this paper proposed an intelligent secure and reliable patrol system. It supports the efficiency patrol system and privacy of the information. It also ensures only legally authorized users have right to access the information. We built the intelligent secure and reliable patrol system by using IoT technology and designed a trusted authentication mechanism within a smart, safe and reliable patrol system. The benefits of the system are: Ensuring the security of the transmission. The system user cannot modify the inspection information arbitrarily. It can make the production maintenance mechanism sounder. It will also help companies gradually move towards the goal of Industry 4.0 smart factory to improve the production efficiency of enterprises and increase production capacity.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132249819","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}
Taiwan is a maritime country. In recent years, due to the open pole of the ocean, outdoor marine leisure sports have been promoted, especially canoeing activities are currently the most popular marine sport in Taiwan. The canoe sport also has competition games: Especially the two-person competition canoe requires two people to coordinate with each other at the same time. Therefore, this article proposes to build a two-person canoe training analysis based on IoT. In this article, an IoT device is installed on the two-person arm. When two people are sliding a canoe, the speed of the G-sensor can be used to judge the problem of coordination between the two parties, and the information proposed in this article will be sent to the platform. The platform will record the rate of each canoe user's sliding. Therefore, the system proposed in this article can be analyzed through platform information. Whether the coordination between the users of both sides is gradually growing, or it needs to be further revised. The method proposed in this article helps to scientifically train players.
{"title":"Training Analysis of Double Canoe Based on IOT","authors":"Jo-Hung Yu, Meng-Tsung Lee, Jao-Chuan Lin, Chien-Hung Wu","doi":"10.1145/3440943.3444344","DOIUrl":"https://doi.org/10.1145/3440943.3444344","url":null,"abstract":"Taiwan is a maritime country. In recent years, due to the open pole of the ocean, outdoor marine leisure sports have been promoted, especially canoeing activities are currently the most popular marine sport in Taiwan. The canoe sport also has competition games: Especially the two-person competition canoe requires two people to coordinate with each other at the same time. Therefore, this article proposes to build a two-person canoe training analysis based on IoT. In this article, an IoT device is installed on the two-person arm. When two people are sliding a canoe, the speed of the G-sensor can be used to judge the problem of coordination between the two parties, and the information proposed in this article will be sent to the platform. The platform will record the rate of each canoe user's sliding. Therefore, the system proposed in this article can be analyzed through platform information. Whether the coordination between the users of both sides is gradually growing, or it needs to be further revised. The method proposed in this article helps to scientifically train players.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125148217","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}
Jiyoon Kim, Sangmin Lee, Daniel Gerbi Duguma, Bonam Kim, I. You
Implantable Medical Devices (IMDs) have evolved over the years to stretch their application areas to provide a range of services from health-care to public safety. In order to handle such information, the high strength security and the proper authentication are required. For this, Ellouze et al. have proposed an authentication protocol for IMDs in 2013. The security in IMD that they propose and mention is reasonable, but some aspects are expected to be vulnerable to attack. In addition, not only are such schemes need to be secured, but their security should also be formally verified against their security requirements. Thus, we confirm the security of the authentication protocol for IMDs that have not been objectively verified through formal verification tool such as BAN-logic. Consequently, in this paper, Ellouze et al. are turned out to be insecure.
{"title":"Comments on \"Securing implantable cardiac medical devices\": Use of radio frequency energy harvesting","authors":"Jiyoon Kim, Sangmin Lee, Daniel Gerbi Duguma, Bonam Kim, I. You","doi":"10.1145/3440943.3444733","DOIUrl":"https://doi.org/10.1145/3440943.3444733","url":null,"abstract":"Implantable Medical Devices (IMDs) have evolved over the years to stretch their application areas to provide a range of services from health-care to public safety. In order to handle such information, the high strength security and the proper authentication are required. For this, Ellouze et al. have proposed an authentication protocol for IMDs in 2013. The security in IMD that they propose and mention is reasonable, but some aspects are expected to be vulnerable to attack. In addition, not only are such schemes need to be secured, but their security should also be formally verified against their security requirements. Thus, we confirm the security of the authentication protocol for IMDs that have not been objectively verified through formal verification tool such as BAN-logic. Consequently, in this paper, Ellouze et al. are turned out to be insecure.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121109877","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}
An effective multi-objective search algorithm based on a new meta-heuristic algorithm, named search economic (SE), is presented in this study. The basic idea of SE is to first partition the solution space into a certain number of regions to keep the diversity. Then, it will determine the later search directions by the so-called expected value that is composed of the objective values of the best-so-far solution of each region, the searched solutions, and the number of searches invested on a region. More important, the proposed algorithm will invest limited computing resources on promising regions to find a better Pareto optimal set (POS). Different from other search economics-based algorithms, the proposed method uses two transition operators of differential evolution and adds a self adaptive mechanism to tune its parameters. Experimental results show that the proposed algorithm outperforms all the other metaheuristic algorithms compared in this study in most cases in the sense that it can get a more uniformly distributed POS and a smaller distance to the Pareto optimal front.
{"title":"An Effective Algorithm based on Search Economics for Multi-Objective Optimization","authors":"Tzu-Tsai Kao, Chun-Wei Tsai, Ming-Chao Chiang","doi":"10.1145/3440943.3444726","DOIUrl":"https://doi.org/10.1145/3440943.3444726","url":null,"abstract":"An effective multi-objective search algorithm based on a new meta-heuristic algorithm, named search economic (SE), is presented in this study. The basic idea of SE is to first partition the solution space into a certain number of regions to keep the diversity. Then, it will determine the later search directions by the so-called expected value that is composed of the objective values of the best-so-far solution of each region, the searched solutions, and the number of searches invested on a region. More important, the proposed algorithm will invest limited computing resources on promising regions to find a better Pareto optimal set (POS). Different from other search economics-based algorithms, the proposed method uses two transition operators of differential evolution and adds a self adaptive mechanism to tune its parameters. Experimental results show that the proposed algorithm outperforms all the other metaheuristic algorithms compared in this study in most cases in the sense that it can get a more uniformly distributed POS and a smaller distance to the Pareto optimal front.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126790573","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}
Joochan Lee, Hyunpyo Choi, Jiho Shin, Jung-Taek Seo
In recent years, 1 a large number of studies have been conducted on cybersecurity for Programmable Logic Controllers (PLCs) to cope with cyberattacks on Industrial Control Systems(ICS). However, few studies have been conducted on ensuring cybersafety for control logics running inside PLCs. In this study, a technique for detecting an attack on PLC control logic change was proposed by analyzing the network protocol data and project file structure. Based on the analysis results for the proposed technique, a tool was implemented to detect an manipulation attack on control logic, and whether such attack was detected or not was verified through experiments.
{"title":"Detection and Analysis Technique for Manipulation Attacks on PLC Control Logic","authors":"Joochan Lee, Hyunpyo Choi, Jiho Shin, Jung-Taek Seo","doi":"10.1145/3440943.3444742","DOIUrl":"https://doi.org/10.1145/3440943.3444742","url":null,"abstract":"In recent years, 1 a large number of studies have been conducted on cybersecurity for Programmable Logic Controllers (PLCs) to cope with cyberattacks on Industrial Control Systems(ICS). However, few studies have been conducted on ensuring cybersafety for control logics running inside PLCs. In this study, a technique for detecting an attack on PLC control logic change was proposed by analyzing the network protocol data and project file structure. Based on the analysis results for the proposed technique, a tool was implemented to detect an manipulation attack on control logic, and whether such attack was detected or not was verified through experiments.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126870014","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}
With the advancement of technology, modern people increasingly tend to communicate with other people through electronic products, and various relationships gradually become alienated, including the Parent-Child Relationship. Parent-child relationship can cultivate children's interaction and trust with other people in social relations, so education systems all over the world encourage the establishment of parent-child relationships to learn together. This research attempted to use children's picture storybooks as study tools to examine parents' and children's attitudes toward an English as a Foreign Language (EFL) parent-child co-learning program. Several parents, and G1 and G2 children, were invited as experimental subjects to participate in a ten-week co-learning program. Experimental results show that parents and children generally have a positive attitude towards the process of joint learning plans.
{"title":"Attitudes of Single Parents and Children for EFL Co-Learning Schedules of Digital Picture Storybooks","authors":"Y. Ou, Yueming Yu, Yu-Xi Chen, Zhen-Yu Wu","doi":"10.1145/3440943.3444338","DOIUrl":"https://doi.org/10.1145/3440943.3444338","url":null,"abstract":"With the advancement of technology, modern people increasingly tend to communicate with other people through electronic products, and various relationships gradually become alienated, including the Parent-Child Relationship. Parent-child relationship can cultivate children's interaction and trust with other people in social relations, so education systems all over the world encourage the establishment of parent-child relationships to learn together. This research attempted to use children's picture storybooks as study tools to examine parents' and children's attitudes toward an English as a Foreign Language (EFL) parent-child co-learning program. Several parents, and G1 and G2 children, were invited as experimental subjects to participate in a ten-week co-learning program. Experimental results show that parents and children generally have a positive attitude towards the process of joint learning plans.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125972158","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}
Typical label data detect anomaly due to the relationship between inputs and labels, but time-series data are more demanding in detecting anomalies because they detect anomaly based on time-varying values. To solve this problem, this paper proposed Stacked-Autoencoder based data detection technique with ICS dataset among time series data. The Loss value was calculated as CDF and determined to be a suspicious event if it was greater than the arbitrarily specified threshold value. The experiment was carried out by designating 0.5, 0.7, 0.9 and 0.98, and 0.98 showed the best result with an accuracy of about 96%.
{"title":"Anomaly detection in time-series data environment","authors":"Doyeon Kim, Taejin Lee","doi":"10.1145/3440943.3444353","DOIUrl":"https://doi.org/10.1145/3440943.3444353","url":null,"abstract":"Typical label data detect anomaly due to the relationship between inputs and labels, but time-series data are more demanding in detecting anomalies because they detect anomaly based on time-varying values. To solve this problem, this paper proposed Stacked-Autoencoder based data detection technique with ICS dataset among time series data. The Loss value was calculated as CDF and determined to be a suspicious event if it was greater than the arbitrarily specified threshold value. The experiment was carried out by designating 0.5, 0.7, 0.9 and 0.98, and 0.98 showed the best result with an accuracy of about 96%.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132296001","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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