Pub Date : 2015-06-08DOI: 10.1109/CYBERSA.2015.7166137
M. Nasir, Shizra Sultan, S. Nefti-Meziani, U. Manzoor
The energy sector has been actively looking into cyber risk assessment at a global level, as it has a ripple effect; risk taken at one step in supply chain has an impact on all the other nodes. Cyber-attacks not only hinder functional operations in an organization but also waves damaging effects to the reputation and confidence among shareholders resulting in financial losses. Organizations that are open to the idea of protecting their assets and information flow and are equipped; enough to respond quickly to any cyber incident are the ones who prevail longer in global market. As a contribution we put forward a modular plan to mitigate or reduce cyber risks in global supply chain by identifying potential cyber threats at each step and identifying their immediate counterm easures.
{"title":"Potential cyber-attacks against global oil supply chain","authors":"M. Nasir, Shizra Sultan, S. Nefti-Meziani, U. Manzoor","doi":"10.1109/CYBERSA.2015.7166137","DOIUrl":"https://doi.org/10.1109/CYBERSA.2015.7166137","url":null,"abstract":"The energy sector has been actively looking into cyber risk assessment at a global level, as it has a ripple effect; risk taken at one step in supply chain has an impact on all the other nodes. Cyber-attacks not only hinder functional operations in an organization but also waves damaging effects to the reputation and confidence among shareholders resulting in financial losses. Organizations that are open to the idea of protecting their assets and information flow and are equipped; enough to respond quickly to any cyber incident are the ones who prevail longer in global market. As a contribution we put forward a modular plan to mitigate or reduce cyber risks in global supply chain by identifying potential cyber threats at each step and identifying their immediate counterm easures.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131572270","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166132
Maria Evangelopoulou, C. W. Johnson
This paper presents an empirical framework for implementing Situation Awareness Measurement Techniques in a Network Defense environment. Bearing in mind the rise of Cyber-crime and the importance of Cyber security, the role of the security analyst (or as this paper will refer to them, defenders) is critical. In this paper the role of Situation Awareness Measurement Techniques will be presented and explained briefly. Input from previous studies will be given and an empirical framework of how to measure Situation Awareness in a computing network environment will be offered in two main parts. The first one will include the networking infrastructure of the system. The second part will be focused on specifying which Situation Awareness Techniques are going to be used and which Situation Awareness critical questions need to be asked to improve future decision making in cyber-security. Finally, a discussion will take place concerning the proposed approach, the chosen methodology and further validation.
{"title":"Empirical framework for situation awareness measurement techniques in network defense","authors":"Maria Evangelopoulou, C. W. Johnson","doi":"10.1109/CyberSA.2015.7166132","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166132","url":null,"abstract":"This paper presents an empirical framework for implementing Situation Awareness Measurement Techniques in a Network Defense environment. Bearing in mind the rise of Cyber-crime and the importance of Cyber security, the role of the security analyst (or as this paper will refer to them, defenders) is critical. In this paper the role of Situation Awareness Measurement Techniques will be presented and explained briefly. Input from previous studies will be given and an empirical framework of how to measure Situation Awareness in a computing network environment will be offered in two main parts. The first one will include the networking infrastructure of the system. The second part will be focused on specifying which Situation Awareness Techniques are going to be used and which Situation Awareness critical questions need to be asked to improve future decision making in cyber-security. Finally, a discussion will take place concerning the proposed approach, the chosen methodology and further validation.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134383818","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166127
Palvi Aggarwal, Antra Grover, Saumya Singh, Zahid Maqbool, V. Pammi, Varun Dutt
The rate at which cyber-attacks are increasing globally portrays a terrifying picture upfront. The main dynamics of such attacks could be studied in terms of the actions of attackers and defenders in a cyber-security game. However currently little research has taken place to study such interactions. In this paper we use behavioral game theory and try to investigate the role of certain actions taken by attackers and defenders in a simulated cyber-attack scenario of defacing a website. We choose a Reinforcement Learning (RL) model to represent a simulated attacker and a defender in a 2×4 cyber-security game where each of the 2 players could take up to 4 actions. A pair of model participants were computationally simulated across 1000 simulations where each pair played at most 30 rounds in the game. The goal of the attacker was to deface the website and the goal of the defender was to prevent the attacker from doing so. Our results show that the actions taken by both the attackers and defenders are a function of attention paid by these roles to their recently obtained outcomes. It was observed that if attacker pays more attention to recent outcomes then he is more likely to perform attack actions. We discuss the implication of our results on the evolution of dynamics between attackers and defenders in cyber-security games.
{"title":"Cyber security: A game-theoretic analysis of defender and attacker strategies in defacing-website games","authors":"Palvi Aggarwal, Antra Grover, Saumya Singh, Zahid Maqbool, V. Pammi, Varun Dutt","doi":"10.1109/CyberSA.2015.7166127","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166127","url":null,"abstract":"The rate at which cyber-attacks are increasing globally portrays a terrifying picture upfront. The main dynamics of such attacks could be studied in terms of the actions of attackers and defenders in a cyber-security game. However currently little research has taken place to study such interactions. In this paper we use behavioral game theory and try to investigate the role of certain actions taken by attackers and defenders in a simulated cyber-attack scenario of defacing a website. We choose a Reinforcement Learning (RL) model to represent a simulated attacker and a defender in a 2×4 cyber-security game where each of the 2 players could take up to 4 actions. A pair of model participants were computationally simulated across 1000 simulations where each pair played at most 30 rounds in the game. The goal of the attacker was to deface the website and the goal of the defender was to prevent the attacker from doing so. Our results show that the actions taken by both the attackers and defenders are a function of attention paid by these roles to their recently obtained outcomes. It was observed that if attacker pays more attention to recent outcomes then he is more likely to perform attack actions. We discuss the implication of our results on the evolution of dynamics between attackers and defenders in cyber-security games.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122198673","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166110
M. Hall, Devon David Hansen, K. Jones
Enhancing situational awareness is a major goal for organisations spanning many sectors, working across many domains. An increased awareness of the state of environments enables improved decision-making. Endsley's model of situational awareness has improved the understanding for the design of decision-support systems. This paper presents and discusses a theoretical model to extend this to cross-domain working to influence the design of future collaborative systems. A use-case is discussed within a military context of the use of this model for cross-domain working between an operational-domain and cyber security-domain.
{"title":"Cross-domain situational awareness and collaborative working for cyber security","authors":"M. Hall, Devon David Hansen, K. Jones","doi":"10.1109/CyberSA.2015.7166110","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166110","url":null,"abstract":"Enhancing situational awareness is a major goal for organisations spanning many sectors, working across many domains. An increased awareness of the state of environments enables improved decision-making. Endsley's model of situational awareness has improved the understanding for the design of decision-support systems. This paper presents and discusses a theoretical model to extend this to cross-domain working to influence the design of future collaborative systems. A use-case is discussed within a military context of the use of this model for cross-domain working between an operational-domain and cyber security-domain.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117187884","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166130
M. Nassar, A. A. Orabi, Marwan Doha, Bechara al Bouna
Data anonymization is an important preprocessing step for data sharing and the delegation of data storage to the cloud. In this paper, we propose an SQL-like query language and a tool to help the data provider ensuring the quality and the privacy of the data being outsourced. The tool supports a set of recent and well-known anonymization techniques in an SQL query style. We present our framework and the language capabilities. We report on experimental evaluation and results.
{"title":"An SQL-like query tool for data anonymization and outsourcing","authors":"M. Nassar, A. A. Orabi, Marwan Doha, Bechara al Bouna","doi":"10.1109/CyberSA.2015.7166130","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166130","url":null,"abstract":"Data anonymization is an important preprocessing step for data sharing and the delegation of data storage to the cloud. In this paper, we propose an SQL-like query language and a tool to help the data provider ensuring the quality and the privacy of the data being outsourced. The tool supports a set of recent and well-known anonymization techniques in an SQL query style. We present our framework and the language capabilities. We report on experimental evaluation and results.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116942236","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166112
S. Neogy
This paper aims to describe the characteristics of Wireless Sensor Networks (WSNs), challenges in designing a resource-constrained and vulnerable network and address security management as the main issue. The work begins with discussion on the attacks on WSNs. As part of protection against the attacks faced by WSNs, key management, the primary requirement of any security practice, is detailed out. This paper also deals with the existing security schemes covering various routing protocols. The paper also touches security issues concerning heterogeneous networks.
{"title":"Security management in Wireless Sensor Networks","authors":"S. Neogy","doi":"10.1109/CyberSA.2015.7166112","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166112","url":null,"abstract":"This paper aims to describe the characteristics of Wireless Sensor Networks (WSNs), challenges in designing a resource-constrained and vulnerable network and address security management as the main issue. The work begins with discussion on the attacks on WSNs. As part of protection against the attacks faced by WSNs, key management, the primary requirement of any security practice, is detailed out. This paper also deals with the existing security schemes covering various routing protocols. The paper also touches security issues concerning heterogeneous networks.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124012037","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166123
S. Neogy, Sayantani Saha
Cloud computing offers and allows users to use infrastructure, platforms, and software as services. With the advent of mobile computing, and cloud computing supporting mobile services, a merger of both these computing has opened a new domain of mobile cloud computing. Predictably, this has given way to a large number of issues coming forward, first and foremost among them, being, security. This paper develops a protocol suite that takes care of an entire mobile cloud computing (MCC) system with respect to a specific application area. Patient monitoring and providing subsequent medical care in remote areas is a problem. The proposal presented here considers the application of remote patient monitoring. The protocol considers remote user authentication and subsequently develop secure access to data retained using cloud infrastructure. A cloud service provider is considered that manages users and their requests.
{"title":"Developing a secure remote patient monitoring system","authors":"S. Neogy, Sayantani Saha","doi":"10.1109/CyberSA.2015.7166123","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166123","url":null,"abstract":"Cloud computing offers and allows users to use infrastructure, platforms, and software as services. With the advent of mobile computing, and cloud computing supporting mobile services, a merger of both these computing has opened a new domain of mobile cloud computing. Predictably, this has given way to a large number of issues coming forward, first and foremost among them, being, security. This paper develops a protocol suite that takes care of an entire mobile cloud computing (MCC) system with respect to a specific application area. Patient monitoring and providing subsequent medical care in remote areas is a problem. The proposal presented here considers the application of remote patient monitoring. The protocol considers remote user authentication and subsequently develop secure access to data retained using cloud infrastructure. A cloud service provider is considered that manages users and their requests.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452339","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166119
Moyinoluwa Abidemi Bode, S. Oluwadare, B. K. Alese, A. Thompson
The unpredictable cyber attackers and threats have to be detected in order to determine the outcome of risk in a network environment. This work develops a Bayesian network classifier to analyse the network traffic in a cyber situation. It is a tool that aids reasoning under uncertainty to determine certainty. It further analyze the level of risk using a modified risk matrix criteria. The classifier developed was experimented with various records extracted from the KDD Cup'99 dataset with 490,021 records. The evaluations showed that the Bayesian Network classifier is a suitable model which resulted in same performance level for classifying the Denial of Service (DoS) attacks with Association Rule Mining while as well as Genetic Algorithm, the Bayesian Network classifier performed better in classifying probe and User to Root (U2R) attacks and classified DoS equally. The result of the classification showed that Bayesian network classifier is a classification model that thrives well in network security. Also, the level of risk analysed from the adapted risk matrix showed that DoS attack has the most frequent occurrence and falls in the generally unacceptable risk zone.
{"title":"Risk analysis in cyber situation awareness using Bayesian approach","authors":"Moyinoluwa Abidemi Bode, S. Oluwadare, B. K. Alese, A. Thompson","doi":"10.1109/CyberSA.2015.7166119","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166119","url":null,"abstract":"The unpredictable cyber attackers and threats have to be detected in order to determine the outcome of risk in a network environment. This work develops a Bayesian network classifier to analyse the network traffic in a cyber situation. It is a tool that aids reasoning under uncertainty to determine certainty. It further analyze the level of risk using a modified risk matrix criteria. The classifier developed was experimented with various records extracted from the KDD Cup'99 dataset with 490,021 records. The evaluations showed that the Bayesian Network classifier is a suitable model which resulted in same performance level for classifying the Denial of Service (DoS) attacks with Association Rule Mining while as well as Genetic Algorithm, the Bayesian Network classifier performed better in classifying probe and User to Root (U2R) attacks and classified DoS equally. The result of the classification showed that Bayesian network classifier is a classification model that thrives well in network security. Also, the level of risk analysed from the adapted risk matrix showed that DoS attack has the most frequent occurrence and falls in the generally unacceptable risk zone.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133763615","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 : 2015-06-08DOI: 10.1109/CyberSA.2015.7166116
A. Enache, Mihai-Gabriel Ionita, V. Sgârciu
Information Security Assurance implies ensuring the integrity, confidentiality and availability of critical assets for an organization. The large amount of events to monitor in a fluid system in terms of topology and variety of new hardware or software, overwhelms monitoring controls. Furthermore, the multi-facets of cyber threats today makes it difficult even for security experts to handle and keep up-to-date. Hence, automatic "intelligent" tools are needed to address these issues. In this paper, we describe a `work in progress' contribution on intelligent based approach to mitigating security threats. The main contribution of this work is an anomaly based IDS model with active response that combines artificial immune systems and swarm intelligence with the SVM classifier. Test results for the NSL-KDD dataset prove the proposed approach can outperform the standard classifier in terms of attack detection rate and false alarm rate, while reducing the number of features in the dataset.
{"title":"An immune intelligent approach for security assurance","authors":"A. Enache, Mihai-Gabriel Ionita, V. Sgârciu","doi":"10.1109/CyberSA.2015.7166116","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166116","url":null,"abstract":"Information Security Assurance implies ensuring the integrity, confidentiality and availability of critical assets for an organization. The large amount of events to monitor in a fluid system in terms of topology and variety of new hardware or software, overwhelms monitoring controls. Furthermore, the multi-facets of cyber threats today makes it difficult even for security experts to handle and keep up-to-date. Hence, automatic \"intelligent\" tools are needed to address these issues. In this paper, we describe a `work in progress' contribution on intelligent based approach to mitigating security threats. The main contribution of this work is an anomaly based IDS model with active response that combines artificial immune systems and swarm intelligence with the SVM classifier. Test results for the NSL-KDD dataset prove the proposed approach can outperform the standard classifier in terms of attack detection rate and false alarm rate, while reducing the number of features in the dataset.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132819764","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 : 1900-01-01DOI: 10.1109/CyberSA.2015.7166128
Radu S. Pirscoveanu, Steven S. Hansen, Thor M. T. Larsen, Matija Stevanovic, J. Pedersen, A. Czech
Malicious software has become a major threat to modern society, not only due to the increased complexity of the malware itself but also due to the exponential increase of new malware each day. This study tackles the problem of analyzing and classifying a high amount of malware in a scalable and automatized manner. We have developed a distributed malware testing environment by extending Cuckoo Sandbox that was used to test an extensive number of malware samples and trace their behavioral data. The extracted data was used for the development of a novel type classification approach based on supervised machine learning. The proposed classification approach employs a novel combination of features that achieves a high classification rate with a weighted average AUC value of 0.98 using Random Forests classifier. The approach has been extensively tested on a total of 42,000 malware samples. Based on the above results it is believed that the developed system can be used to pre-filter novel from known malware in a future malware analysis system.
{"title":"Analysis of malware behavior: Type classification using machine learning","authors":"Radu S. Pirscoveanu, Steven S. Hansen, Thor M. T. Larsen, Matija Stevanovic, J. Pedersen, A. Czech","doi":"10.1109/CyberSA.2015.7166128","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166128","url":null,"abstract":"Malicious software has become a major threat to modern society, not only due to the increased complexity of the malware itself but also due to the exponential increase of new malware each day. This study tackles the problem of analyzing and classifying a high amount of malware in a scalable and automatized manner. We have developed a distributed malware testing environment by extending Cuckoo Sandbox that was used to test an extensive number of malware samples and trace their behavioral data. The extracted data was used for the development of a novel type classification approach based on supervised machine learning. The proposed classification approach employs a novel combination of features that achieves a high classification rate with a weighted average AUC value of 0.98 using Random Forests classifier. The approach has been extensively tested on a total of 42,000 malware samples. Based on the above results it is believed that the developed system can be used to pre-filter novel from known malware in a future malware analysis system.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"47 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125718997","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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