Matt Gorbett, Caspian Siebert, Hossein Shirazi, Indrakshi Ray
Modern network infrastructures are in a constant state of transformation, in large part due to the exponential growth of Internet of Things (IoT) devices. The unique properties of IoT-connected networks, such as heterogeneity and non-standardized protocol, have created critical security holes and network mismanagement. In this paper we propose a new measurement tool, Intrinsic Dimensionality (ID), to aid in analyzing and classifying network traffic. A proxy for dataset complexity, ID can be used to understand the network as a whole, aiding in tasks such as network management and provisioning. We use ID to evaluate several modern network datasets empirically. Showing that, for network and device-level data, generated using IoT methodologies, the ID of the data fits into a low dimensional representation. Additionally we explore network data complexity at the sample level using Local Intrinsic Dimensionality (LID) and propose a novel unsupervised intrusion detection technique, the Weighted Hamming LID Estimator. We show that the algortihm performs better on IoT network datasets than the Autoencoder, KNN, and Isolation Forests. Finally, we propose the use of synthetic data as an additional tool for both network data measurement as well as intrusion detection. Synthetically generated data can aid in building a more robust network dataset, while also helping in downstream tasks such as machine learning based intrusion detection models. We explore the effects of synthetic data on ID measurements, as well as its role in intrusion detection systems.
{"title":"The intrinsic dimensionality of network datasets and its applications1","authors":"Matt Gorbett, Caspian Siebert, Hossein Shirazi, Indrakshi Ray","doi":"10.3233/jcs-220131","DOIUrl":"https://doi.org/10.3233/jcs-220131","url":null,"abstract":"Modern network infrastructures are in a constant state of transformation, in large part due to the exponential growth of Internet of Things (IoT) devices. The unique properties of IoT-connected networks, such as heterogeneity and non-standardized protocol, have created critical security holes and network mismanagement. In this paper we propose a new measurement tool, Intrinsic Dimensionality (ID), to aid in analyzing and classifying network traffic. A proxy for dataset complexity, ID can be used to understand the network as a whole, aiding in tasks such as network management and provisioning. We use ID to evaluate several modern network datasets empirically. Showing that, for network and device-level data, generated using IoT methodologies, the ID of the data fits into a low dimensional representation. Additionally we explore network data complexity at the sample level using Local Intrinsic Dimensionality (LID) and propose a novel unsupervised intrusion detection technique, the Weighted Hamming LID Estimator. We show that the algortihm performs better on IoT network datasets than the Autoencoder, KNN, and Isolation Forests. Finally, we propose the use of synthetic data as an additional tool for both network data measurement as well as intrusion detection. Synthetically generated data can aid in building a more robust network dataset, while also helping in downstream tasks such as machine learning based intrusion detection models. We explore the effects of synthetic data on ID measurements, as well as its role in intrusion detection systems.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"78 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135087347","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}
Availability is crucial to the security of distributed systems, but guaranteeing availability is hard, especially when participants in the system may act maliciously. Quorum replication protocols provide both integrity and availability: data and computation is replicated at multiple independent hosts, and a quorum of these hosts must agree on the output of all operations applied to the data. Unfortunately, these protocols have high overhead and can be difficult to calibrate for a specific application’s needs. Ideally, developers could use high-level abstractions for consensus and replication to write fault-tolerant code that is secure by construction. This paper presents Flow-Limited Authorization for Quorum Replication (FLAQR), a core calculus for building distributed applications with heterogeneous quorum replication protocols while enforcing end-to-end information security. Our type system ensures that well-typed FLAQR programs cannot fail (experience an unrecoverable error) in ways that violate their type-level specifications. We present noninterference theorems that characterize FLAQR’s confidentiality, integrity, and availability in the presence of consensus, replication, and failures, as well as a liveness theorem for the class of majority quorum protocols under a bounded number of faults. Additionally, we present an extension to FLAQR that supports secret sharing as a form of declassification and prove it preserves integrity and availability security properties.
{"title":"Flow-limited authorization for consensus, replication, and secret sharing1","authors":"Priyanka Mondal, Maximilian Algehed, Owen Arden","doi":"10.3233/jcs-230048","DOIUrl":"https://doi.org/10.3233/jcs-230048","url":null,"abstract":"Availability is crucial to the security of distributed systems, but guaranteeing availability is hard, especially when participants in the system may act maliciously. Quorum replication protocols provide both integrity and availability: data and computation is replicated at multiple independent hosts, and a quorum of these hosts must agree on the output of all operations applied to the data. Unfortunately, these protocols have high overhead and can be difficult to calibrate for a specific application’s needs. Ideally, developers could use high-level abstractions for consensus and replication to write fault-tolerant code that is secure by construction. This paper presents Flow-Limited Authorization for Quorum Replication (FLAQR), a core calculus for building distributed applications with heterogeneous quorum replication protocols while enforcing end-to-end information security. Our type system ensures that well-typed FLAQR programs cannot fail (experience an unrecoverable error) in ways that violate their type-level specifications. We present noninterference theorems that characterize FLAQR’s confidentiality, integrity, and availability in the presence of consensus, replication, and failures, as well as a liveness theorem for the class of majority quorum protocols under a bounded number of faults. Additionally, we present an extension to FLAQR that supports secret sharing as a form of declassification and prove it preserves integrity and availability security properties.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804565","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}
Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
We study the privacy-utility trade-off in the context of metric differential privacy. Ghosh et al. introduced the idea of universal optimality to characterise the “best” mechanism for a certain query that simultaneously satisfies (a fixed) ε-differential privacy constraint whilst at the same time providing better utility compared to any other ε-differentially private mechanism for the same query. They showed that the Geometric mechanism is universally optimal for the class of counting queries. On the other hand, Brenner and Nissim showed that outside the space of counting queries, and for the Bayes risk loss function, no such universally optimal mechanisms exist. Except for the universal optimality of the Laplace mechanism, there have been no generalisations of these universally optimal results to other classes of differentially-private mechanisms. In this paper, we use metric differential privacy and quantitative information flow as the fundamental principle for studying universal optimality. Metric differential privacy is a generalisation of both standard (i.e., central) differential privacy and local differential privacy, and it is increasingly being used in various application domains, for instance in location privacy and in privacy-preserving machine learning. Similar to the approaches adopted by Ghosh et al. and Brenner and Nissim, we measure utility in terms of loss functions, and we interpret the notion of a privacy mechanism as an information-theoretic channel satisfying constraints defined by ε-differential privacy and a metric meaningful to the underlying state space. Using this framework we are able to clarify Nissim and Brenner’s negative results by (a) that in fact all privacy types contain optimal mechanisms relative to certain kinds of non-trivial loss functions, and (b) extending and generalising their negative results beyond Bayes risk specifically to a wide class of non-trivial loss functions. Our exploration suggests that universally optimal mechanisms are indeed rare within privacy types. We therefore propose weaker universal benchmarks of utility called privacy type capacities. We show that such capacities always exist and can be computed using a convex optimisation algorithm. Further, we illustrate these ideas on a selection of examples with several different underlying metrics.
{"title":"Universal optimality and robust utility bounds for metric differential privacy1","authors":"Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding","doi":"10.3233/jcs-230036","DOIUrl":"https://doi.org/10.3233/jcs-230036","url":null,"abstract":"We study the privacy-utility trade-off in the context of metric differential privacy. Ghosh et al. introduced the idea of universal optimality to characterise the “best” mechanism for a certain query that simultaneously satisfies (a fixed) ε-differential privacy constraint whilst at the same time providing better utility compared to any other ε-differentially private mechanism for the same query. They showed that the Geometric mechanism is universally optimal for the class of counting queries. On the other hand, Brenner and Nissim showed that outside the space of counting queries, and for the Bayes risk loss function, no such universally optimal mechanisms exist. Except for the universal optimality of the Laplace mechanism, there have been no generalisations of these universally optimal results to other classes of differentially-private mechanisms. In this paper, we use metric differential privacy and quantitative information flow as the fundamental principle for studying universal optimality. Metric differential privacy is a generalisation of both standard (i.e., central) differential privacy and local differential privacy, and it is increasingly being used in various application domains, for instance in location privacy and in privacy-preserving machine learning. Similar to the approaches adopted by Ghosh et al. and Brenner and Nissim, we measure utility in terms of loss functions, and we interpret the notion of a privacy mechanism as an information-theoretic channel satisfying constraints defined by ε-differential privacy and a metric meaningful to the underlying state space. Using this framework we are able to clarify Nissim and Brenner’s negative results by (a) that in fact all privacy types contain optimal mechanisms relative to certain kinds of non-trivial loss functions, and (b) extending and generalising their negative results beyond Bayes risk specifically to a wide class of non-trivial loss functions. Our exploration suggests that universally optimal mechanisms are indeed rare within privacy types. We therefore propose weaker universal benchmarks of utility called privacy type capacities. We show that such capacities always exist and can be computed using a convex optimisation algorithm. Further, we illustrate these ideas on a selection of examples with several different underlying metrics.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804881","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}
Constantin Cătălin Drăgan, François Dupressoir, Ehsan Estaji, Kristian Gjøsteen, Thomas Haines, Peter Y.A. Ryan, Peter B. Rønne, Morten Rotvold Solberg
Privacy is a notoriously difficult property to achieve in complicated systems and especially in electronic voting schemes. Moreover, electronic voting schemes is a class of systems that require very high assurance. The literature contains a number of ballot privacy definitions along with security proofs for common systems. Some machine-checked security proofs have also appeared. We define a new ballot privacy notion that captures a larger class of voting schemes. This notion improves on the state of the art by taking into account that verification in many schemes will happen or must happen after the tally has been published, not before as in previous definitions. As a case study we give a machine-checked proof of privacy for Selene, which is a remote electronic voting scheme which offers an attractive mix of security properties and usability. Prior to our work, the computational privacy of Selene has never been formally verified. Finally, we also prove that MiniVoting and Belenios satisfies our definition.
{"title":"Machine-checked proofs of privacy against malicious boards for Selene & Co1","authors":"Constantin Cătălin Drăgan, François Dupressoir, Ehsan Estaji, Kristian Gjøsteen, Thomas Haines, Peter Y.A. Ryan, Peter B. Rønne, Morten Rotvold Solberg","doi":"10.3233/jcs-230045","DOIUrl":"https://doi.org/10.3233/jcs-230045","url":null,"abstract":"Privacy is a notoriously difficult property to achieve in complicated systems and especially in electronic voting schemes. Moreover, electronic voting schemes is a class of systems that require very high assurance. The literature contains a number of ballot privacy definitions along with security proofs for common systems. Some machine-checked security proofs have also appeared. We define a new ballot privacy notion that captures a larger class of voting schemes. This notion improves on the state of the art by taking into account that verification in many schemes will happen or must happen after the tally has been published, not before as in previous definitions. As a case study we give a machine-checked proof of privacy for Selene, which is a remote electronic voting scheme which offers an attractive mix of security properties and usability. Prior to our work, the computational privacy of Selene has never been formally verified. Finally, we also prove that MiniVoting and Belenios satisfies our definition.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135805039","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}
Replay attacks are among the most well-known attacks against vote privacy. Many e-voting systems have been proven vulnerable to replay attacks, including systems like Helios that are used in real practical elections. Despite their popularity, it is commonly believed that replay attacks are inefficient but the actual threat that they pose to vote privacy has never been studied formally. Therefore, in this paper, we precisely analyze for the first time how efficient replay attacks really are. We study this question from commonly used and complementary perspectives on vote privacy, showing as an independent contribution that a simple extension of a popular game-based privacy definition corresponds to a strong entropy-based notion. Our results demonstrate that replay attacks can be devastating for a voter’s privacy even when an adversary’s resources are very limited. We illustrate our formal findings by applying them to a number of real-world elections, showing that a modest number of replays can result in significant privacy loss. Overall, our work reveals that, contrary to a common belief, replay attacks can be very efficient and must therefore be considered a serious threat.
{"title":"How efficient are replay attacks against vote privacy? A formal quantitative analysis1","authors":"David Mestel, Johannes Müller, Pascal Reisert","doi":"10.3233/jcs-230047","DOIUrl":"https://doi.org/10.3233/jcs-230047","url":null,"abstract":"Replay attacks are among the most well-known attacks against vote privacy. Many e-voting systems have been proven vulnerable to replay attacks, including systems like Helios that are used in real practical elections. Despite their popularity, it is commonly believed that replay attacks are inefficient but the actual threat that they pose to vote privacy has never been studied formally. Therefore, in this paper, we precisely analyze for the first time how efficient replay attacks really are. We study this question from commonly used and complementary perspectives on vote privacy, showing as an independent contribution that a simple extension of a popular game-based privacy definition corresponds to a strong entropy-based notion. Our results demonstrate that replay attacks can be devastating for a voter’s privacy even when an adversary’s resources are very limited. We illustrate our formal findings by applying them to a number of real-world elections, showing that a modest number of replays can result in significant privacy loss. Overall, our work reveals that, contrary to a common belief, replay attacks can be very efficient and must therefore be considered a serious threat.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804882","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}
Liyi Li, Yiyun Liu, Deena Postol, Leonidas Lampropoulos, David Van Horn, Michael Hicks
We present a formal model of Checked C, a dialect of C that aims to enforce spatial memory safety. Our model pays particular attention to the semantics of dynamically sized, potentially null-terminated arrays. We formalize this model in Coq, and prove that any spatial memory safety errors can be blamed on portions of the program labeled unchecked; this is a Checked C feature that supports incremental porting and backward compatibility. While our model’s operational semantics uses annotated (“fat”) pointers to enforce spatial safety, we show that such annotations can be safely erased. Using PLT Redex we formalize an executable version of our model and a compilation procedure to an untyped C-like language, as well as use randomized testing to validate that generated code faithfully simulates the original. Finally, we develop a custom random generator for well-typed and almost-well-typed terms in our Redex model, and use it to search for inconsistencies between our model and the Clang Checked C implementation. We find these steps to be a useful way to co-develop a language (Checked C is still in development) and a core model of it.
{"title":"A formal model of Checked C1","authors":"Liyi Li, Yiyun Liu, Deena Postol, Leonidas Lampropoulos, David Van Horn, Michael Hicks","doi":"10.3233/jcs-230040","DOIUrl":"https://doi.org/10.3233/jcs-230040","url":null,"abstract":"We present a formal model of Checked C, a dialect of C that aims to enforce spatial memory safety. Our model pays particular attention to the semantics of dynamically sized, potentially null-terminated arrays. We formalize this model in Coq, and prove that any spatial memory safety errors can be blamed on portions of the program labeled unchecked; this is a Checked C feature that supports incremental porting and backward compatibility. While our model’s operational semantics uses annotated (“fat”) pointers to enforce spatial safety, we show that such annotations can be safely erased. Using PLT Redex we formalize an executable version of our model and a compilation procedure to an untyped C-like language, as well as use randomized testing to validate that generated code faithfully simulates the original. Finally, we develop a custom random generator for well-typed and almost-well-typed terms in our Redex model, and use it to search for inconsistencies between our model and the Clang Checked C implementation. We find these steps to be a useful way to co-develop a language (Checked C is still in development) and a core model of it.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804883","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}
Symbolic protocol verification generally abstracts probabilities away, considering computations that succeed only with negligible probability, such as guessing random numbers or breaking an encryption scheme, as impossible. This abstraction, sometimes referred to as the perfect cryptography assumption, has shown very useful as it simplifies automation of the analysis. However, probabilities may also appear in the control flow where they are generally not negligible. In this paper we consider a framework for symbolic protocol analysis with a probabilistic choice operator: the probabilistic applied π-calculus. We define and explore the relationships between several behavioral equivalences. In particular we show the need for randomized schedulers and exhibit a counter-example to a result in a previous work that relied on non-randomized ones. As in other frameworks that mix both non-deterministic and probabilistic choices, schedulers may sometimes be unrealistically powerful. We therefore consider two subclasses of processes that avoid this problem. In particular, when considering purely non-deterministic protocols, as is done in classical symbolic verification, we show that a probabilistic adversary has – maybe surprisingly – a strictly superior distinguishing power for may testing, which, when the number of sessions is bounded, we show to coincide with purely possibilistic similarity.
{"title":"Symbolic protocol verification with dice1","authors":"Vincent Cheval, Raphaëlle Crubillé, Steve Kremer","doi":"10.3233/jcs-230037","DOIUrl":"https://doi.org/10.3233/jcs-230037","url":null,"abstract":"Symbolic protocol verification generally abstracts probabilities away, considering computations that succeed only with negligible probability, such as guessing random numbers or breaking an encryption scheme, as impossible. This abstraction, sometimes referred to as the perfect cryptography assumption, has shown very useful as it simplifies automation of the analysis. However, probabilities may also appear in the control flow where they are generally not negligible. In this paper we consider a framework for symbolic protocol analysis with a probabilistic choice operator: the probabilistic applied π-calculus. We define and explore the relationships between several behavioral equivalences. In particular we show the need for randomized schedulers and exhibit a counter-example to a result in a previous work that relied on non-randomized ones. As in other frameworks that mix both non-deterministic and probabilistic choices, schedulers may sometimes be unrealistically powerful. We therefore consider two subclasses of processes that avoid this problem. In particular, when considering purely non-deterministic protocols, as is done in classical symbolic verification, we show that a probabilistic adversary has – maybe surprisingly – a strictly superior distinguishing power for may testing, which, when the number of sessions is bounded, we show to coincide with purely possibilistic similarity.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135805040","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}
I. Obiri, Abigail Akosua Addobea, Eric Affum, Jacob Ankamah, Albert Kofi Kwansah Ansah
Precision agriculture (PA) involves collecting, processing, and analyzing datasets in agriculture for an informed decision. Due to the high data storage and application maintenance costs, farmers usually outsource their agricultural data obtained from PA to cloud service providers to leverage cloud services. Nonetheless, serious security concerns arise from using cloud services for farmers. For instance, an attacker can intercept agricultural data and run comprehensive statistical analyses to adjudicate farmers’ financial status, extort money, commit identity theft, etc. As a result, compelling data security schemes have become crucial for secure precision farming, where only legitimate users are required to access the agricultural data outsourced to the cloud. This article presents a certificateless signcryption scheme with proxy re-encryption (CLS-PRE) for secure access control in PA. An in-depth security analysis proves that the CLS-PRE scheme is secure in the Random Oracle Model. Detailed performance evaluation also shows that the scheme can reduce the time required to signcrypt and unsigncrypt messages and lower communication overhead.
{"title":"A certificateless signcryption with proxy-encryption for securing agricultural data in the cloud","authors":"I. Obiri, Abigail Akosua Addobea, Eric Affum, Jacob Ankamah, Albert Kofi Kwansah Ansah","doi":"10.3233/jcs-220107","DOIUrl":"https://doi.org/10.3233/jcs-220107","url":null,"abstract":"Precision agriculture (PA) involves collecting, processing, and analyzing datasets in agriculture for an informed decision. Due to the high data storage and application maintenance costs, farmers usually outsource their agricultural data obtained from PA to cloud service providers to leverage cloud services. Nonetheless, serious security concerns arise from using cloud services for farmers. For instance, an attacker can intercept agricultural data and run comprehensive statistical analyses to adjudicate farmers’ financial status, extort money, commit identity theft, etc. As a result, compelling data security schemes have become crucial for secure precision farming, where only legitimate users are required to access the agricultural data outsourced to the cloud. This article presents a certificateless signcryption scheme with proxy re-encryption (CLS-PRE) for secure access control in PA. An in-depth security analysis proves that the CLS-PRE scheme is secure in the Random Oracle Model. Detailed performance evaluation also shows that the scheme can reduce the time required to signcrypt and unsigncrypt messages and lower communication overhead.","PeriodicalId":46074,"journal":{"name":"Journal of Computer Security","volume":"69 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74504717","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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