Pub Date : 2018-02-01DOI: 10.1109/NTMS.2018.8328732
J. Ellul, Gordon J. Pace
Blockchain technology and the application of smart contracts allow for automation of verifiable digital processes between any number of parties. The Internet of Things (IoT) has seen great potential in the past decade to revolutionise our day-to-day lives with the aim of automating physical processes by incorporating Internet-connected devices into commodities. By integrating the IoT with blockchain systems and smart contracts it is possible to provide verifiable automation of physical processes involving different parties. The challenge lies in that due to resource constraints, many of the computational devices used within the IoT are not capable of directly interacting with blockchain implementations. In this paper, we describe and give a reference design and implementation of a split-virtual machine, AlkylVM, which allows for resource constrained IoT devices to interact with blockchain systems.
{"title":"AlkylVM: A Virtual Machine for Smart Contract Blockchain Connected Internet of Things","authors":"J. Ellul, Gordon J. Pace","doi":"10.1109/NTMS.2018.8328732","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328732","url":null,"abstract":"Blockchain technology and the application of smart contracts allow for automation of verifiable digital processes between any number of parties. The Internet of Things (IoT) has seen great potential in the past decade to revolutionise our day-to-day lives with the aim of automating physical processes by incorporating Internet-connected devices into commodities. By integrating the IoT with blockchain systems and smart contracts it is possible to provide verifiable automation of physical processes involving different parties. The challenge lies in that due to resource constraints, many of the computational devices used within the IoT are not capable of directly interacting with blockchain implementations. In this paper, we describe and give a reference design and implementation of a split-virtual machine, AlkylVM, which allows for resource constrained IoT devices to interact with blockchain systems.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131342150","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328696
Mathew Nicho, Adelaiye Oluwasegun, F. Kamoun
This research aims to identify some vulnerabilities of advanced persistent threat (APT) attacks using multiple simulated attacks in a virtualized environment. Our experimental study shows that while updating the antivirus software and the operating system with the latest patches may help in mitigating APTs, APT threat vectors could still infiltrate the strongest defenses. Accordingly, we highlight some critical areas of security concern that need to be addressed.
{"title":"Identifying Vulnerabilities in APT Attacks: A Simulated Approach","authors":"Mathew Nicho, Adelaiye Oluwasegun, F. Kamoun","doi":"10.1109/NTMS.2018.8328696","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328696","url":null,"abstract":"This research aims to identify some vulnerabilities of advanced persistent threat (APT) attacks using multiple simulated attacks in a virtualized environment. Our experimental study shows that while updating the antivirus software and the operating system with the latest patches may help in mitigating APTs, APT threat vectors could still infiltrate the strongest defenses. Accordingly, we highlight some critical areas of security concern that need to be addressed.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126151660","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328697
Manuel-Jesús Espinosa-Gavira, A. Jimenez-Pro, J. D. L. Rosa, A. A. Pérez, O. Florencias-Oliveros, J. C. P. Salas, José María Sierra Fernández
This paper presents a Wireless Sensor Network (WSN) design, using the Application Programming Interface (API) mode for accessing to the communication modules built-in functions. In these conditions, the use of an external microcontroller can be avoided with the subsequent reduction in the global network cost, but also increasing the reliability and the flexibility while maintaining the essential features of typical WSN. To show the system performance, two variables have been monitored: light and temperature.
{"title":"Improving Flexibility in Wireless Sensor Networks via API. An Application in Environmental Monitoring","authors":"Manuel-Jesús Espinosa-Gavira, A. Jimenez-Pro, J. D. L. Rosa, A. A. Pérez, O. Florencias-Oliveros, J. C. P. Salas, José María Sierra Fernández","doi":"10.1109/NTMS.2018.8328697","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328697","url":null,"abstract":"This paper presents a Wireless Sensor Network (WSN) design, using the Application Programming Interface (API) mode for accessing to the communication modules built-in functions. In these conditions, the use of an external microcontroller can be avoided with the subsequent reduction in the global network cost, but also increasing the reliability and the flexibility while maintaining the essential features of typical WSN. To show the system performance, two variables have been monitored: light and temperature.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121710678","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328747
H. Bouafif, F. Kamoun, Farkhund Iqbal, A. Marrington
Powerful information acquisition and processing capabilities, coupled with intelligent surveillance and reconnaissance features, have contributed to increased popularity of Unmanned Aerial Vehicles (UAVs), also known as drones. In addition to the numerous beneficial uses, UAVs have been misused to launch illegal and sometimes criminal activities that pose direct threats to individuals, organizations, public safety and national security. Despite its increased importance, "drone forensics" remains a relatively unexplored research topic. This paper presents important results of a forensic investigation analysis performed on a test Parrot AR drone 2.0. We present new insights into drone forensics in terms of accessing the digital containers of an intercepted drone and retrieving all the information that can help digital forensic investigators establish ownership, recover flight data and acquire content of media files.
{"title":"Drone Forensics: Challenges and New Insights","authors":"H. Bouafif, F. Kamoun, Farkhund Iqbal, A. Marrington","doi":"10.1109/NTMS.2018.8328747","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328747","url":null,"abstract":"Powerful information acquisition and processing capabilities, coupled with intelligent surveillance and reconnaissance features, have contributed to increased popularity of Unmanned Aerial Vehicles (UAVs), also known as drones. In addition to the numerous beneficial uses, UAVs have been misused to launch illegal and sometimes criminal activities that pose direct threats to individuals, organizations, public safety and national security. Despite its increased importance, \"drone forensics\" remains a relatively unexplored research topic. This paper presents important results of a forensic investigation analysis performed on a test Parrot AR drone 2.0. We present new insights into drone forensics in terms of accessing the digital containers of an intercepted drone and retrieving all the information that can help digital forensic investigators establish ownership, recover flight data and acquire content of media files.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131110016","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328718
Zeeshan Afzal, Johan Garcia, S. Lindskog, A. Brunström
Levenshtein distance is well known for its use in comparing two strings for similarity. However, the set of considered edit operations used when comparing can be reduced in a number of situations. In such cases, the application of the generic Levenshtein distance can result in degraded detection and computational performance. Other metrics in the literature enable limiting the considered edit operations to a smaller subset. However, the possibility where a difference can only result from deleted bytes is not yet explored. To this end, we propose an insert-only variation of the Levenshtein distance to enable comparison of two strings for the case in which differences occur only because of missing bytes. The proposed distance metric is named slice distance and is formally presented and its computational complexity is discussed. We also provide a discussion of the potential security applications of the slice distance.
{"title":"Slice Distance: An Insert-Only Levenshtein Distance with a Focus on Security Applications","authors":"Zeeshan Afzal, Johan Garcia, S. Lindskog, A. Brunström","doi":"10.1109/NTMS.2018.8328718","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328718","url":null,"abstract":"Levenshtein distance is well known for its use in comparing two strings for similarity. However, the set of considered edit operations used when comparing can be reduced in a number of situations. In such cases, the application of the generic Levenshtein distance can result in degraded detection and computational performance. Other metrics in the literature enable limiting the considered edit operations to a smaller subset. However, the possibility where a difference can only result from deleted bytes is not yet explored. To this end, we propose an insert-only variation of the Levenshtein distance to enable comparison of two strings for the case in which differences occur only because of missing bytes. The proposed distance metric is named slice distance and is formally presented and its computational complexity is discussed. We also provide a discussion of the potential security applications of the slice distance.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134248630","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328749
Mahmoud Kalash, Mrigank Rochan, N. Mohammed, Neil D. B. Bruce, Yang Wang, Farkhund Iqbal
In this paper, we propose a deep learning framework for malware classification. There has been a huge increase in the volume of malware in recent years which poses a serious security threat to financial institutions, businesses and individuals. In order to combat the proliferation of malware, new strategies are essential to quickly identify and classify malware samples so that their behavior can be analyzed. Machine learning approaches are becoming popular for classifying malware, however, most of the existing machine learning methods for malware classification use shallow learning algorithms (e.g. SVM). Recently, Convolutional Neural Networks (CNN), a deep learning approach, have shown superior performance compared to traditional learning algorithms, especially in tasks such as image classification. Motivated by this success, we propose a CNN-based architecture to classify malware samples. We convert malware binaries to grayscale images and subsequently train a CNN for classification. Experiments on two challenging malware classification datasets, Malimg and Microsoft malware, demonstrate that our method achieves better than the state-of-the-art performance. The proposed method achieves 98.52% and 99.97% accuracy on the Malimg and Microsoft datasets respectively.
{"title":"Malware Classification with Deep Convolutional Neural Networks","authors":"Mahmoud Kalash, Mrigank Rochan, N. Mohammed, Neil D. B. Bruce, Yang Wang, Farkhund Iqbal","doi":"10.1109/NTMS.2018.8328749","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328749","url":null,"abstract":"In this paper, we propose a deep learning framework for malware classification. There has been a huge increase in the volume of malware in recent years which poses a serious security threat to financial institutions, businesses and individuals. In order to combat the proliferation of malware, new strategies are essential to quickly identify and classify malware samples so that their behavior can be analyzed. Machine learning approaches are becoming popular for classifying malware, however, most of the existing machine learning methods for malware classification use shallow learning algorithms (e.g. SVM). Recently, Convolutional Neural Networks (CNN), a deep learning approach, have shown superior performance compared to traditional learning algorithms, especially in tasks such as image classification. Motivated by this success, we propose a CNN-based architecture to classify malware samples. We convert malware binaries to grayscale images and subsequently train a CNN for classification. Experiments on two challenging malware classification datasets, Malimg and Microsoft malware, demonstrate that our method achieves better than the state-of-the-art performance. The proposed method achieves 98.52% and 99.97% accuracy on the Malimg and Microsoft datasets respectively.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130974882","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328713
Louis Tajan, Moritz Kaumanns, D. Westhoff
In a Semi-autonomic cloud auditing architecture we weaved in privacy enhancing mechanisms [15] by applying the public key version of the Somewhat homomorphic encryption (SHE) scheme from [4]. It turns out that the performance of the SHE can be significantly improved by carefully deriving relevant crypto parameters from the concrete cloud auditing use cases for which the scheme serves as a privacy enhancing approach. We provide a generic algorithm for finding good SHE parameters with respect to a given use case scenario by analyzing and taking into consideration security, correctness and performance of the scheme. Also, to show the relevance of our proposed algorithms we apply it to two predominant cloud auditing use cases.
{"title":"Pre-Computing Appropriate Parameters: How to Accelerate Somewhat Homomorphic Encryption for Cloud Auditing","authors":"Louis Tajan, Moritz Kaumanns, D. Westhoff","doi":"10.1109/NTMS.2018.8328713","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328713","url":null,"abstract":"In a Semi-autonomic cloud auditing architecture we weaved in privacy enhancing mechanisms [15] by applying the public key version of the Somewhat homomorphic encryption (SHE) scheme from [4]. It turns out that the performance of the SHE can be significantly improved by carefully deriving relevant crypto parameters from the concrete cloud auditing use cases for which the scheme serves as a privacy enhancing approach. We provide a generic algorithm for finding good SHE parameters with respect to a given use case scenario by analyzing and taking into consideration security, correctness and performance of the scheme. Also, to show the relevance of our proposed algorithms we apply it to two predominant cloud auditing use cases.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126599171","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328705
Canek Portillo, J. Martínez-Bauset, V. Pla
Wireless Sensor Networks (WSN) have experienced an important resurgence, especially through applications designed for the Internet of Things. In that sense, a WSN can be constituted of different classes of nodes, having different characteristics. On the other hand, S-MAC was the first Medium Access Control (MAC) protocol for WSN to implement the Duty Cycling (DC). DC is a popular technique for energy conservation in WSN, that allows nodes to wake up and sleep periodically. In this work, a performance evaluation study of S-MAC is performed considering heterogeneous scenarios and diverse medium access priorities. To accomplish that, an analytical model with a pair of two-dimensional Discrete-Time Markov Chains (DTMC) is developed. Scenarios with two classes of nodes forming the network were studied. Performance parameters such as packet average delay, throughput and consumed energy, are obtained and validated by simulation, showing accurate results.
{"title":"Modelling of S-MAC for Heterogeneous WSN","authors":"Canek Portillo, J. Martínez-Bauset, V. Pla","doi":"10.1109/NTMS.2018.8328705","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328705","url":null,"abstract":"Wireless Sensor Networks (WSN) have experienced an important resurgence, especially through applications designed for the Internet of Things. In that sense, a WSN can be constituted of different classes of nodes, having different characteristics. On the other hand, S-MAC was the first Medium Access Control (MAC) protocol for WSN to implement the Duty Cycling (DC). DC is a popular technique for energy conservation in WSN, that allows nodes to wake up and sleep periodically. In this work, a performance evaluation study of S-MAC is performed considering heterogeneous scenarios and diverse medium access priorities. To accomplish that, an analytical model with a pair of two-dimensional Discrete-Time Markov Chains (DTMC) is developed. Scenarios with two classes of nodes forming the network were studied. Performance parameters such as packet average delay, throughput and consumed energy, are obtained and validated by simulation, showing accurate results.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126946887","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328739
A. Unterweger, F. Knirsch, Christoph Leixnering, D. Engel
Real-world smart contracts which preserve the privacy of both, their users and their data, have barely been proposed theoretically, let alone been implemented practically. In this paper, we are the first to implement a privacy-preserving protocol from the energy domain as a smart contract in Ethereum. We elaborate on and present our implementation as well as our practical findings, including more or less subtle traps and pitfalls. Despite major optimizations to our implementation, we find that while it is currently possible, it is not feasible to implement a privacy-preserving protocol of modest complexity in the Ethereum blockchain due to the high cost of operation and the lack of privacy by design.
{"title":"Lessons Learned from Implementing a Privacy-Preserving Smart Contract in Ethereum","authors":"A. Unterweger, F. Knirsch, Christoph Leixnering, D. Engel","doi":"10.1109/NTMS.2018.8328739","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328739","url":null,"abstract":"Real-world smart contracts which preserve the privacy of both, their users and their data, have barely been proposed theoretically, let alone been implemented practically. In this paper, we are the first to implement a privacy-preserving protocol from the energy domain as a smart contract in Ethereum. We elaborate on and present our implementation as well as our practical findings, including more or less subtle traps and pitfalls. Despite major optimizations to our implementation, we find that while it is currently possible, it is not feasible to implement a privacy-preserving protocol of modest complexity in the Ethereum blockchain due to the high cost of operation and the lack of privacy by design.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115178943","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 : 2018-02-01DOI: 10.1109/NTMS.2018.8328746
Johan Garcia
Monitoring networks for the presence of some particular set of files can, for example, be important in order to avoid exfiltration of sensitive data, or combat the spread of Child Sexual Abuse (CSA) material. This work presents a scalable system for large-scale file detection in high-speed networks. A multi-level approach using packet sampling with rolling and block hashing is introduced. We show that such approach together with a well tuned implementation can perform detection of a large number of files on the network at 10 Gbps using standard hardware. The use of packet sampling enables easy distribution of the monitoring processing functionality, and allows for flexible scaling in a cloud environment. Performance experiments on the most run-time critical hashing parts shows a single-thread performance consistent with 10Gbps line rate monitoring. The file detectability is examined for three data sets over a range of packet sampling rates. A conservative sampling rate of 0.1 is demonstrated to perform well for all tested data sets. It is also shown that knowledge of the file size distribution can be exploited to allow lower sampling rates to be configured for two of the data sets, which in turn results in lower resource usage.
{"title":"A Fragment Hashing Approach for Scalable and Cloud-Aware Network File Detection","authors":"Johan Garcia","doi":"10.1109/NTMS.2018.8328746","DOIUrl":"https://doi.org/10.1109/NTMS.2018.8328746","url":null,"abstract":"Monitoring networks for the presence of some particular set of files can, for example, be important in order to avoid exfiltration of sensitive data, or combat the spread of Child Sexual Abuse (CSA) material. This work presents a scalable system for large-scale file detection in high-speed networks. A multi-level approach using packet sampling with rolling and block hashing is introduced. We show that such approach together with a well tuned implementation can perform detection of a large number of files on the network at 10 Gbps using standard hardware. The use of packet sampling enables easy distribution of the monitoring processing functionality, and allows for flexible scaling in a cloud environment. Performance experiments on the most run-time critical hashing parts shows a single-thread performance consistent with 10Gbps line rate monitoring. The file detectability is examined for three data sets over a range of packet sampling rates. A conservative sampling rate of 0.1 is demonstrated to perform well for all tested data sets. It is also shown that knowledge of the file size distribution can be exploited to allow lower sampling rates to be configured for two of the data sets, which in turn results in lower resource usage.","PeriodicalId":140704,"journal":{"name":"2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124416982","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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