The paper addresses unmanned aerial vehicles (UAVs - aka drones) designed to be undetected by humans, i.e. stealth drones, or more generally, to have a minimal impact on living beings and environment, i.e. 'blue' drones, in the sense of preserving unaltered the blue color of the sky. Being 'blue' might be highly desirable in the future when drones will proliferate in large numbers, stealth is a special case, desirable to covert military and security operations. The paper explores general characteristics of blue drones and alternatives of making them, offering both system and component level solutions.
{"title":"UAVs You Can't See or Hear - A Survey of Key Technologies","authors":"A. Stoica, E. Dente, Y. Iwashita, A. Chiolerio","doi":"10.1109/EST.2015.21","DOIUrl":"https://doi.org/10.1109/EST.2015.21","url":null,"abstract":"The paper addresses unmanned aerial vehicles (UAVs - aka drones) designed to be undetected by humans, i.e. stealth drones, or more generally, to have a minimal impact on living beings and environment, i.e. 'blue' drones, in the sense of preserving unaltered the blue color of the sky. Being 'blue' might be highly desirable in the future when drones will proliferate in large numbers, stealth is a special case, desirable to covert military and security operations. The paper explores general characteristics of blue drones and alternatives of making them, offering both system and component level solutions.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131923317","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. Xavier, M. Pereira, G. Giraldi, S. Gibson, C. Solomon, D. Rueckert, D. Gillies, C. Thomaz
This work describes a photo-realistic generator that creates semi-automatically face images of unseen subjects. Unlike previously described methods for generating face imagery, the approach described herein incorporates texture and shape information in a single computational framework based on high dimensional encoding of variance and discriminant information from sample groups. The method produces realistic, frontal pose, images with minimum manual intervention. We believe that the work presented describes a useful tool for face perception applications where privacy-preserving analysis might be an issue and the goal is not the recognition of the face itself, but rather its characteristics like gender, age or race, commonly explored in social and forensic contexts.
{"title":"A Photo-Realistic Generator of Most Expressive and Discriminant Changes in 2D Face Images","authors":"I. Xavier, M. Pereira, G. Giraldi, S. Gibson, C. Solomon, D. Rueckert, D. Gillies, C. Thomaz","doi":"10.1109/EST.2015.17","DOIUrl":"https://doi.org/10.1109/EST.2015.17","url":null,"abstract":"This work describes a photo-realistic generator that creates semi-automatically face images of unseen subjects. Unlike previously described methods for generating face imagery, the approach described herein incorporates texture and shape information in a single computational framework based on high dimensional encoding of variance and discriminant information from sample groups. The method produces realistic, frontal pose, images with minimum manual intervention. We believe that the work presented describes a useful tool for face perception applications where privacy-preserving analysis might be an issue and the goal is not the recognition of the face itself, but rather its characteristics like gender, age or race, commonly explored in social and forensic contexts.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131309359","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}
S. Yanushkevich, Shawn C. Eastwood, S. Samoil, V. Shmerko, Travis Manderson, M. Drahanský
Impersonation is a phenomenon of biometric-enabled authentication machines. The focus of this paper is authentication machines for border crossing applications (e-borders). A novel taxonomy of impersonation and seven impersonation strategies for border crossing control applications are proposed. We identify conditions for impersonation and reinforced factors for various scenarios of e-border crossing automation. A demonstrative experiment using a Dempster-Shafer approach to the detection of impersonation phenomena is introduced. This lays a foundation for the study of the vulnerabilities of e-borders to the specified impersonation strategies.
{"title":"Taxonomy and Modeling of Impersonation in e-Border Authentication","authors":"S. Yanushkevich, Shawn C. Eastwood, S. Samoil, V. Shmerko, Travis Manderson, M. Drahanský","doi":"10.1109/EST.2015.18","DOIUrl":"https://doi.org/10.1109/EST.2015.18","url":null,"abstract":"Impersonation is a phenomenon of biometric-enabled authentication machines. The focus of this paper is authentication machines for border crossing applications (e-borders). A novel taxonomy of impersonation and seven impersonation strategies for border crossing control applications are proposed. We identify conditions for impersonation and reinforced factors for various scenarios of e-border crossing automation. A demonstrative experiment using a Dempster-Shafer approach to the detection of impersonation phenomena is introduced. This lays a foundation for the study of the vulnerabilities of e-borders to the specified impersonation strategies.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127128019","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}
Robust and stringent fault detection and correction techniques in executing Advanced Encryption Standard (AES) are still interesting issues for many critical applications. The purpose of fault detection and correction techniques is not only to ensure the reliability of a cryptosystem, but also protect the system against side channel attacks. Such errors could result due to a fault injection attack, production faults, noise or radiation effects in deep space. Devising a proper error control mechanisms for AES cipher during execution would improve both system reliability and security. In this work a novel fault detection and correction algorithm is proposed. The proposed mechanism is making use of the linear mappings of AES round structure to detect errors in the ShiftRow (SR) and MixColumn (MC) transformations. The error correction is achieved by creating temporary redundant check words through the combined SR and MC mapping to create in case of errors an error syndrome leading to error correction with relatively minor additional complexity. The proposed technique is making use of an error detecting and correcting capability in the combined mapping of SR and MC rather than detecting and/or correcting errors in each transformation separately. The proposed technique is making use especially of the MC mapping exhibiting efficient ECC properties, which can be deployed to simplify the design of a fault-tolerance technique. The performance of the algorithm proposed is evaluated by a simulated system model in FPGA technology. The simulation results demonstrate the ability to reach relatively high fault coverage with error correction up to four bytes of execution errors in the merged transformation SR-MC. The overall gate complexity overhead of the resulting system is estimated for proposed technique in FPGA technology.
{"title":"Fault Detection and Correction in Processing AES Encryption Algorithm","authors":"M. Basil, W. Adi","doi":"10.1109/EST.2015.13","DOIUrl":"https://doi.org/10.1109/EST.2015.13","url":null,"abstract":"Robust and stringent fault detection and correction techniques in executing Advanced Encryption Standard (AES) are still interesting issues for many critical applications. The purpose of fault detection and correction techniques is not only to ensure the reliability of a cryptosystem, but also protect the system against side channel attacks. Such errors could result due to a fault injection attack, production faults, noise or radiation effects in deep space. Devising a proper error control mechanisms for AES cipher during execution would improve both system reliability and security. In this work a novel fault detection and correction algorithm is proposed. The proposed mechanism is making use of the linear mappings of AES round structure to detect errors in the ShiftRow (SR) and MixColumn (MC) transformations. The error correction is achieved by creating temporary redundant check words through the combined SR and MC mapping to create in case of errors an error syndrome leading to error correction with relatively minor additional complexity. The proposed technique is making use of an error detecting and correcting capability in the combined mapping of SR and MC rather than detecting and/or correcting errors in each transformation separately. The proposed technique is making use especially of the MC mapping exhibiting efficient ECC properties, which can be deployed to simplify the design of a fault-tolerance technique. The performance of the algorithm proposed is evaluated by a simulated system model in FPGA technology. The simulation results demonstrate the ability to reach relatively high fault coverage with error correction up to four bytes of execution errors in the merged transformation SR-MC. The overall gate complexity overhead of the resulting system is estimated for proposed technique in FPGA technology.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114800848","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}
We propose a novel method for stabilizing videos taken by a low altitude aerial vehicle, for the purpose of monitoring activities on the ground. A popular choice for aerial video stabilization is the use of homography-based methods, which assume that the scene consists mostly of planar regions. When videos are recorded in low altitude flight, the regions with buildings, trees and hills are non-planar areas (with relatively big changes in height), and making the planar assumption would decrease the accuracy of stabilization with respect to the ground. The idea presented in this paper is to stabilize aerial images, where height changes exist, by explicitly estimating a planar area in the scene. For the estimation of planar region, a relative pose between two images is estimated by taking advantages of the homography-based method and the essential matrix-based method. Positions in the 3D space are reconstructed from feature points on the images, which are used for the pose estimation, and points on the plane are estimated based on RANSAC. The points on the flat area are used for stabilization of images with high accuracy. The experimental results with simulated aerial images illustrate the proposed method can estimate relative pose with higher accuracy compared with previous approaches, even when noise is present. The proposed method is also applied to real aerial images, in people tracking. Experimental results show that tracking using the proposed method has better performance than tracking using the homography-based method.
{"title":"Stable Image Registration for People Tracking from the Sky","authors":"Y. Iwashita, R. Kurazume","doi":"10.1109/EST.2015.14","DOIUrl":"https://doi.org/10.1109/EST.2015.14","url":null,"abstract":"We propose a novel method for stabilizing videos taken by a low altitude aerial vehicle, for the purpose of monitoring activities on the ground. A popular choice for aerial video stabilization is the use of homography-based methods, which assume that the scene consists mostly of planar regions. When videos are recorded in low altitude flight, the regions with buildings, trees and hills are non-planar areas (with relatively big changes in height), and making the planar assumption would decrease the accuracy of stabilization with respect to the ground. The idea presented in this paper is to stabilize aerial images, where height changes exist, by explicitly estimating a planar area in the scene. For the estimation of planar region, a relative pose between two images is estimated by taking advantages of the homography-based method and the essential matrix-based method. Positions in the 3D space are reconstructed from feature points on the images, which are used for the pose estimation, and points on the plane are estimated based on RANSAC. The points on the flat area are used for stabilization of images with high accuracy. The experimental results with simulated aerial images illustrate the proposed method can estimate relative pose with higher accuracy compared with previous approaches, even when noise is present. The proposed method is also applied to real aerial images, in people tracking. Experimental results show that tracking using the proposed method has better performance than tracking using the homography-based method.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126690232","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}
Security schemes are rendered impractical if their cryptographic keys are compromised. ICMetric technology is an innovation in the field of cryptography that generates a device identification based on the inherent features of a device. Devices in the internet of things (IoT) are cyber physical systems with varying purpose and platforms. Since these devices are deeply entwined with the physical world, the chances of a security failure are higher. In this paper we suggest coupling the ICMetric technology and IoT. We prove that device identification can be generated by using the accelerometer found in many pervasive devices. Our experiments are based on a set of health sensors equipped with a MEMS accelerometer. Periodic readings are obtained from the sensor and analysed mathematically and statistically to generate a stable ICMetric number.
{"title":"Securing MEMS Based Sensor Nodes in the Internet of Things","authors":"Hasan Tahir, Ruhma Tahir, K. Mcdonald-Maier","doi":"10.1109/EST.2015.8","DOIUrl":"https://doi.org/10.1109/EST.2015.8","url":null,"abstract":"Security schemes are rendered impractical if their cryptographic keys are compromised. ICMetric technology is an innovation in the field of cryptography that generates a device identification based on the inherent features of a device. Devices in the internet of things (IoT) are cyber physical systems with varying purpose and platforms. Since these devices are deeply entwined with the physical world, the chances of a security failure are higher. In this paper we suggest coupling the ICMetric technology and IoT. We prove that device identification can be generated by using the accelerometer found in many pervasive devices. Our experiments are based on a set of health sensors equipped with a MEMS accelerometer. Periodic readings are obtained from the sensor and analysed mathematically and statistically to generate a stable ICMetric number.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426352","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}
C. Frowd, S. Underwood, P. Athwal, J. Lampinen, W. B. Erickson, G. Mahony, J. Marsh
It is well established that we carry stereotypes that impact on human perception and behaviour (e.g. G.W. Allport, "The nature of prejudice". Reading, MA: Addison-Wesley, 1954). Here, we investigate the possibility that we hold a stereotype for a face indicating that its owner may have a mental illness. A three-stage face-perception experiment suggested the presence of such a stereotype. Participants first rated 200 synthetic male faces from the EvoFIT facial-composite system for perceived mental illness (PMI). These faces were used to create a computer-based rating scale that was used by a second sample of participants to make a set of faces appear mentally ill. There was evidence to suggest that the faces that participants identified using the PMI scale differed along this dimension (although not entirely as expected). In the final stage of the study, another set of synthetic faces were created by artificially increasing and decreasing levels along the scale. Participants were asked to rate these items for PMI and for six criminal types. It was found that participants assigned higher PMI ratings (cf. veridical) for items with inflated PMI (although there was no reliable difference in ratings between veridical faces and faces with decreased PMI). Implications of the findings are discussed.
{"title":"Facial Stereotypes and Perceived Mental Illness","authors":"C. Frowd, S. Underwood, P. Athwal, J. Lampinen, W. B. Erickson, G. Mahony, J. Marsh","doi":"10.1109/EST.2015.25","DOIUrl":"https://doi.org/10.1109/EST.2015.25","url":null,"abstract":"It is well established that we carry stereotypes that impact on human perception and behaviour (e.g. G.W. Allport, \"The nature of prejudice\". Reading, MA: Addison-Wesley, 1954). Here, we investigate the possibility that we hold a stereotype for a face indicating that its owner may have a mental illness. A three-stage face-perception experiment suggested the presence of such a stereotype. Participants first rated 200 synthetic male faces from the EvoFIT facial-composite system for perceived mental illness (PMI). These faces were used to create a computer-based rating scale that was used by a second sample of participants to make a set of faces appear mentally ill. There was evidence to suggest that the faces that participants identified using the PMI scale differed along this dimension (although not entirely as expected). In the final stage of the study, another set of synthetic faces were created by artificially increasing and decreasing levels along the scale. Participants were asked to rate these items for PMI and for six criminal types. It was found that participants assigned higher PMI ratings (cf. veridical) for items with inflated PMI (although there was no reliable difference in ratings between veridical faces and faces with decreased PMI). Implications of the findings are discussed.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127242656","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}
This paper evaluates the feasibility of using the fusion of multispectral data from a Kinect v2 sensor as a way to extract the palm region of hand in an unconstrained environment. The depth data was used to both track the hand and extract palm regions. This extracted palm region was then used to extract the palm region in the RGB and Near Infrared data. One of the underlying goals was to maintain real time performance and as such relatively simple techniques such as using a sliding window were used. The lower boundary of the usable frames extracted was 50%, while in the case when the user is positioned directly in front of the sensor with hands extended outward from the body, the percentage of usable frames reached 75%.
{"title":"Depth Assisted Palm Region Extraction Using the Kinect v2 Sensor","authors":"S. Samoil, S. Yanushkevich","doi":"10.1109/EST.2015.11","DOIUrl":"https://doi.org/10.1109/EST.2015.11","url":null,"abstract":"This paper evaluates the feasibility of using the fusion of multispectral data from a Kinect v2 sensor as a way to extract the palm region of hand in an unconstrained environment. The depth data was used to both track the hand and extract palm regions. This extracted palm region was then used to extract the palm region in the RGB and Near Infrared data. One of the underlying goals was to maintain real time performance and as such relatively simple techniques such as using a sliding window were used. The lower boundary of the usable frames extracted was 50%, while in the case when the user is positioned directly in front of the sensor with hands extended outward from the body, the percentage of usable frames reached 75%.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"230 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124222339","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}
Encryption techniques used by popular messaging services such as Skype, Viber and WhatsApp make traces of illegal activities by criminal groups almost undetectable. This paper reports challenges involved to examine data of the WhatsApp application on popular mobile platforms (iOS, Android and Windows Phone) using latest forensic software such as EnCase, UFED and Oxygen Forensic Suite. The operating systems used were Windows phone 8.1, Android 5.0.1 (Lollipop) and iOS 8.3. Results show that due to strong security features built into the Windows 8.1 system forensic examiners may not be able to access data with standard forensic suite and they must decide whether to perform a live forensic acquisition. This paper provides forensics examiners with practical techniques for recovering evidences of WhatsApp data from Windows 8.1 mobile operating systems that would otherwise be inaccessible.
{"title":"Forensic Acquisitions of WhatsApp Data on Popular Mobile Platforms","authors":"Adam Shortall, M. Azhar","doi":"10.1109/EST.2015.16","DOIUrl":"https://doi.org/10.1109/EST.2015.16","url":null,"abstract":"Encryption techniques used by popular messaging services such as Skype, Viber and WhatsApp make traces of illegal activities by criminal groups almost undetectable. This paper reports challenges involved to examine data of the WhatsApp application on popular mobile platforms (iOS, Android and Windows Phone) using latest forensic software such as EnCase, UFED and Oxygen Forensic Suite. The operating systems used were Windows phone 8.1, Android 5.0.1 (Lollipop) and iOS 8.3. Results show that due to strong security features built into the Windows 8.1 system forensic examiners may not be able to access data with standard forensic suite and they must decide whether to perform a live forensic acquisition. This paper provides forensics examiners with practical techniques for recovering evidences of WhatsApp data from Windows 8.1 mobile operating systems that would otherwise be inaccessible.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128495357","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 problem of combining multi-modal features which extract from characteristics of given Cloud Computing Servers in the pattern recognition system is well known difficult. This paper addresses a novel efficient technique for normalizing sets of features which are highly multi-modal in nature, so as to allow them to be incorporated from a multi-dimensional feature distribution space. The intend system identify the modes of each distribution and for removing any possible correlation between the feature data to allow to be used in an encryption key generation system.
{"title":"Integrating Multi-modal Cloud Features within a Multi-dimensional Encryption Space","authors":"Bin Ye, G. Howells","doi":"10.1109/EST.2015.12","DOIUrl":"https://doi.org/10.1109/EST.2015.12","url":null,"abstract":"The problem of combining multi-modal features which extract from characteristics of given Cloud Computing Servers in the pattern recognition system is well known difficult. This paper addresses a novel efficient technique for normalizing sets of features which are highly multi-modal in nature, so as to allow them to be incorporated from a multi-dimensional feature distribution space. The intend system identify the modes of each distribution and for removing any possible correlation between the feature data to allow to be used in an encryption key generation system.","PeriodicalId":402244,"journal":{"name":"2015 Sixth International Conference on Emerging Security Technologies (EST)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127597517","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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