Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited n...Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited number of signature samples are available to train these models in a real-world scenario.Several researchers have proposed models to augment new signature images by applying various transformations.Others,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature samples.Hence,augmenting a sufficient number of signatures with variations is still a challenging task.This study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature verification.The proposed model is capable of augmenting better quality signatures with diversity from a single signature image only.It is empirically evaluated on widely used public datasets;GPDSsyntheticSignature.The quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIM),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy rate.Experiment results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation methods.The improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.展开更多
Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection.It is also a popular biometric authentication technology in forensic and com...Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection.It is also a popular biometric authentication technology in forensic and commercial transactions due to its various advantages,including noninvasiveness,user-friendliness,and social and legal acceptability.According to the literature,extensive research has been conducted on signature verification systems in a variety of languages,including English,Hindi,Bangla,and Chinese.However,the Arabic Offline Signature Verification(OSV)system is still a challenging issue that has not been investigated as much by researchers due to the Arabic script being distinguished by changing letter shapes,diacritics,ligatures,and overlapping,making verification more difficult.Recently,signature verification systems have shown promising results for recognizing signatures that are genuine or forgeries;however,performance on skilled forgery detection is still unsatisfactory.Most existing methods require many learning samples to improve verification accuracy,which is a major drawback because the number of available signature samples is often limited in the practical application of signature verification systems.This study addresses these issues by presenting an OSV system based on multifeature fusion and discriminant feature selection using a genetic algorithm(GA).In contrast to existing methods,which use multiclass learning approaches,this study uses a oneclass learning strategy to address imbalanced signature data in the practical application of a signature verification system.The proposed approach is tested on three signature databases(SID)-Arabic handwriting signatures,CEDAR(Center of Excellence for Document Analysis and Recognition),and UTSIG(University of Tehran Persian Signature),and experimental results show that the proposed system outperforms existing systems in terms of reducing the False Acceptance Rate(FAR),False Rejection Rate(FRR),and Equal Error Rate(ERR).The proposed system achieved 5%improvement.展开更多
Understanding the sensitivity of tidal flats to environmental changes is challenging.Currently,most studies rely on process-based models to systematically explain the morphodynamic evolution of tidal flats.In this stu...Understanding the sensitivity of tidal flats to environmental changes is challenging.Currently,most studies rely on process-based models to systematically explain the morphodynamic evolution of tidal flats.In this study,we proposed an alternative empirical approach to explore tidal flat dynamics using statistical indices based on long-term time series of daily surface elevation development.Surface elevation dynamic(SED)indices focus on the magnitude and period of surface elevation changes,while morphodynamic signature(MDS)indices relate sediment dynamics to environmental drivers.The statistical analyses were applied to an intervention site in the Netherlands to determine the effect of recently constructed groynes on the tidal flat.Using these analyses,we were able to(1)detect a reduction in the daily SED and(2)determine that the changes in the daily SED were predominantly caused by the reduction in wave impact between the groynes rather than the reduction in tidal currents.Overall,the presented results showed that the combination of novel statistical indices provides new insights into the trajectories of tidal flats,ecosystem functioning,and sensitivity to physical drivers(wind and tides).Finally,we suggested how the SED and MDS indices may help to explore the future trajectories and climate resilience of intertidal habitats.展开更多
Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other...Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business envir-onments.However,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective information.Second,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass differences.These challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective information.To solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature images.Moreover,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature images.In addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of strokes.We respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification methods.This is more helpful to the task of signature authentication in justice and finance.展开更多
Identity verification using authenticity evaluation of handwritten signatures is an important issue.There have been several approaches for the verification of signatures using dynamics of the signing process.Most of t...Identity verification using authenticity evaluation of handwritten signatures is an important issue.There have been several approaches for the verification of signatures using dynamics of the signing process.Most of these approaches extract only global characteristics.With the aim of capturing both dynamic global and local features,this paper introduces a novel model for verifying handwritten dynamic signatures using neutrosophic rule-based verification system(NRVS)and Genetic NRVS(GNRVS)models.The neutrosophic Logic is structured to reflect multiple types of knowledge and relations among all features using three values:truth,indeterminacy,and falsity.These three values are determined by neutrosophic membership functions.The proposed model also is able to deal with all features without the need to select from them.In the GNRVS model,the neutrosophic rules are automatically chosen by Genetic Algorithms.The performance of the proposed system is tested on the MCYT-Signature-100 dataset.In terms of the accuracy,average error rate,false acceptance rate,and false rejection rate,the experimental results indicate that the proposed model has a significant advantage compared to different well-known models.展开更多
Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination da...Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination data and weighting method. By a specific case, i.e. vernier caliper, it is proved that the fit precision and forecast precision of the models are much higher, the cycles are obviously different under different working conditions, and the forecast result of the frequency sequence model is better than that of the time sequence model. Combining dynamic grey model and auto-manufacturing case the controlling and information subsystems of verification cycle and the lifecycle based on information integration, multi-sensor controlling and management controlling were given. The models can be used in production process to help enterprise reduce error, cost and flaw.展开更多
The paper proposes an on-line signature verification algorithm, through which test sample and template signatures can be optimizedly matched, based on evolutionary computation (EC). Firstly, the similarity of signatur...The paper proposes an on-line signature verification algorithm, through which test sample and template signatures can be optimizedly matched, based on evolutionary computation (EC). Firstly, the similarity of signature curve segment is defined, and shift and scale transforms are also introduced due to the randoness of on-line signature. Secondly, this paper puts forward signature verification matching algorithm after establishment of the mathematical model. Thirdly, the concrete realization of the algorithm based on EC is discussed as well. In addition, the influence of shift and scale on the matching result is fully considered in the algorithm. Finally, a computation example is given, and the matching results between the test sample curve and the template signature curve are analyzed in detail. The preliminary experiments reveal that the type of signature verification problem can be solved by EC.展开更多
A multi-proxy quantum group signature scheme with threshold shared verification is proposed.An original signer may authorize a proxy group as his proxy agent.Then only the cooperation of all the signers in the proxy g...A multi-proxy quantum group signature scheme with threshold shared verification is proposed.An original signer may authorize a proxy group as his proxy agent.Then only the cooperation of all the signers in the proxy group can generate the proxy signature on behalf of the original signer.In the scheme,any t or more of n receivers can verify the message and any t 1 or fewer receivers cannot verify the validity of the proxy signature.展开更多
In 2005, Bao, et al. [Appl. Math. and Comput., vol.169, No.2, 2005] showed that Tzeng, et al.’s nonrepudiable threshold multi-proxy multi-signature scheme with shared verification was insecure, and proposed an improv...In 2005, Bao, et al. [Appl. Math. and Comput., vol.169, No.2, 2005] showed that Tzeng, et al.’s nonrepudiable threshold multi-proxy multi-signature scheme with shared verification was insecure, and proposed an improved scheme with no Share Distribution Center (SDC). This paper shows that Bao, et al.’s scheme suffers from the proxy relationship inversion attack and forgery attack, and pro- poses an improvement of Bao, et al.’s scheme.展开更多
The short secret key characteristic of elliptic curve cryptosystem(ECC) are integrated with the(t,n) threshold method to create a practical threshold group signature scheme characterized by simultaneous signing.The sc...The short secret key characteristic of elliptic curve cryptosystem(ECC) are integrated with the(t,n) threshold method to create a practical threshold group signature scheme characterized by simultaneous signing.The scheme not only meets the requirements of anonymity and traceability of group signature but also can withstand Tseng and Wang's conspiracy attack.It allows the group manager to add new members and delete old members according to actual application,while the system parameters have a little change.Cryptanalysis result shows that the scheme is efficient and secure.展开更多
Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respira...Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respiratory motion platform;QUASAR phantom) and system log files. Methods: The QUASAR phantom was placed on a treatment couch. Measurement of the point dose and dose distribution was performed for conventional IMRT, with the QUASAR phantom static and moving;for DTT IMRT, this was performed with the phantom moving for pyramid shaped, prostate, paranasal sinus, and pancreas targets. The QUASAR phantom was driven by a sinusoidal signal in the superior-inferior direction. Furthermore, predicted positional errors induced by the Vero4DRT system and mechanical positional errors of the gimbal head, were calculated using the system log files. Results and Conclusion: For DTT IMRT, the dose at the evaluation point was within 3% compared with the verification plan, and the dose distribution in the passing rates of γ was 97.9%, with the criteria of 3% dose and 3 mm distance to agreement. The position error calculated from the log files was within 2 mm, suggesting the feasibility of employing DTT IMRT with high accuracy using the Vero4DRT system.展开更多
In January 2015,the first quantum homomorphic signature scheme was proposed creatively.However,only one verifier is allowed to verify a signature once in this scheme.In order to support repeatable verification for gen...In January 2015,the first quantum homomorphic signature scheme was proposed creatively.However,only one verifier is allowed to verify a signature once in this scheme.In order to support repeatable verification for general scenario,we propose a new quantum homomorphic signature scheme with repeatable verification by introducing serial verification model and parallel verification model.Serial verification model solves the problem of signature verification by combining key distribution and Bell measurement.Parallel verification model solves the problem of signature duplication by logically treating one particle of an EPR pair as a quantum signature and physically preparing a new EPR pair.These models will be beneficial to the signature verification of general scenarios.Scheme analysis shows that both intermediate verifiers and terminal verifiers can successfully verify signatures in the same operation with fewer resource consumption,and especially the verified signature in entangled states can be used repeatedly.展开更多
This paper presents an off-line handwritten signature verification system based on the Siamese network,where a hybrid architecture is used.The Residual neural Network(ResNet)is used to realize a powerful feature extra...This paper presents an off-line handwritten signature verification system based on the Siamese network,where a hybrid architecture is used.The Residual neural Network(ResNet)is used to realize a powerful feature extraction model such that Writer Independent(WI)features can be effectively learned.A single-layer Siamese Neural Network(NN)is used to realize a Writer Dependent(WD)classifier such that the storage space can be minimized.For the purpose of reducing the impact of the high intraclass variability of the signature and ensuring that the Siamese network can learn more effectively,we propose a method of selecting a reference signature as one of the inputs for the Siamese network.To take full advantage of the reference signature,we modify the conventional contrastive loss function to enhance the accuracy.By using the proposed techniques,the accuracy of the system can be increased by 5.9%.Based on the GPDS signature dataset,the proposed system is able to achieve an accuracy of 94.61%which is better than the accuracy achieved by the current state-of-the-art work.展开更多
The novel reinforcement to the data glove based dynamic signature verification system, using the Photometric measurement values collected simultaneously from photo plethysmography (PPG) during the signing process is t...The novel reinforcement to the data glove based dynamic signature verification system, using the Photometric measurement values collected simultaneously from photo plethysmography (PPG) during the signing process is the emerging technology. Skilled forgers try to attempt the genuine signatures in many numbers of trials. The wide gap in the Euclidian distances between forgers and the genuine template features prohibits them from successful forging. This has been proved by our repeated experiments on various subjects using the above combinational features. In addition the intra trial features captured during the forge attempts also differs widely in the case of forgers and are not consistent that of a genuine signature. This is caused by the pulse characteristics and degree of bilateral hand dimensional similarity, and the degrees of pulse delay. Since this economical and simple optical-based technology is offering an improved biometric security, it is essential to look for other reinforcements such the variability factor considerations which we proved of worth considering.展开更多
In this paper, a new dynamic group signature scheme is proposed. It allows the group manager to increase or delete group members flexibly. Furthermore, the length of group signatures, as well as the computational effo...In this paper, a new dynamic group signature scheme is proposed. It allows the group manager to increase or delete group members flexibly. Furthermore, the length of group signatures, as well as the computational effort for signing, verifying and opening are very small and independent of the number of group members and deleted group members. So it is efficient.展开更多
Valve train dynamic behaviors need to be considered at the beginning of the engine mechanical design,especially during choosing valve spring parameters.From parameter definition to simulation,the valve train parameter...Valve train dynamic behaviors need to be considered at the beginning of the engine mechanical design,especially during choosing valve spring parameters.From parameter definition to simulation,the valve train parameters around dynamic performance are determined step by step.The valve train dynamic test is done finally to verify the design result since it is a such important facet for valve train design.And reliability from mass production and product life view must be considered during whole design process too.展开更多
The bamboo scrimber is an anisotropic material.The elastic constant values of the bamboo scrimber specimens measured by the dynamic and static methods are consistent,and the dynamic test method has the advantages of r...The bamboo scrimber is an anisotropic material.The elastic constant values of the bamboo scrimber specimens measured by the dynamic and static methods are consistent,and the dynamic test method has the advantages of rapidity,simplicity,good repeatability,and high precision.Bamboo scrimber has strong potential as a building material,and its elastic constant is an important index to measure its mechanical properties.To quickly,simply,non-destructively,and accurately detect the elastic constant of the bamboo scrimber,they were dynamically tested by the free plate transient excitation method and cantilever plate torsional vibration method.The static four-point bending method was used to verify the accuracy and reliability of the dynamic elastic modulus,shear modulus,and Poisson’s ratio of the bamboo scrimber.The mechanism analysis and evaluation of the quality grade,homogeneity,and size effect of the bamboo scrimber whole board were carried out.The main results show that the dynamic elastic modulus,shear modulus,and Poisson’s ratio of the bamboo scrimber are 12 GPa,1500 MPa,and 0.31,respectively,which meet the requirements of GB/T 40247-2021 for structural bamboo scrimber.展开更多
文摘Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited number of signature samples are available to train these models in a real-world scenario.Several researchers have proposed models to augment new signature images by applying various transformations.Others,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature samples.Hence,augmenting a sufficient number of signatures with variations is still a challenging task.This study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature verification.The proposed model is capable of augmenting better quality signatures with diversity from a single signature image only.It is empirically evaluated on widely used public datasets;GPDSsyntheticSignature.The quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIM),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy rate.Experiment results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation methods.The improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.
文摘Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection.It is also a popular biometric authentication technology in forensic and commercial transactions due to its various advantages,including noninvasiveness,user-friendliness,and social and legal acceptability.According to the literature,extensive research has been conducted on signature verification systems in a variety of languages,including English,Hindi,Bangla,and Chinese.However,the Arabic Offline Signature Verification(OSV)system is still a challenging issue that has not been investigated as much by researchers due to the Arabic script being distinguished by changing letter shapes,diacritics,ligatures,and overlapping,making verification more difficult.Recently,signature verification systems have shown promising results for recognizing signatures that are genuine or forgeries;however,performance on skilled forgery detection is still unsatisfactory.Most existing methods require many learning samples to improve verification accuracy,which is a major drawback because the number of available signature samples is often limited in the practical application of signature verification systems.This study addresses these issues by presenting an OSV system based on multifeature fusion and discriminant feature selection using a genetic algorithm(GA).In contrast to existing methods,which use multiclass learning approaches,this study uses a oneclass learning strategy to address imbalanced signature data in the practical application of a signature verification system.The proposed approach is tested on three signature databases(SID)-Arabic handwriting signatures,CEDAR(Center of Excellence for Document Analysis and Recognition),and UTSIG(University of Tehran Persian Signature),and experimental results show that the proposed system outperforms existing systems in terms of reducing the False Acceptance Rate(FAR),False Rejection Rate(FRR),and Equal Error Rate(ERR).The proposed system achieved 5%improvement.
基金supported by the Royal Netherlands Academy of Arts and Sciences(KNAW)(Grant No.PSA-SA-E-02)the Province of Zeeland,the Netherlands(Grant No.CoE-Buitendijks)。
文摘Understanding the sensitivity of tidal flats to environmental changes is challenging.Currently,most studies rely on process-based models to systematically explain the morphodynamic evolution of tidal flats.In this study,we proposed an alternative empirical approach to explore tidal flat dynamics using statistical indices based on long-term time series of daily surface elevation development.Surface elevation dynamic(SED)indices focus on the magnitude and period of surface elevation changes,while morphodynamic signature(MDS)indices relate sediment dynamics to environmental drivers.The statistical analyses were applied to an intervention site in the Netherlands to determine the effect of recently constructed groynes on the tidal flat.Using these analyses,we were able to(1)detect a reduction in the daily SED and(2)determine that the changes in the daily SED were predominantly caused by the reduction in wave impact between the groynes rather than the reduction in tidal currents.Overall,the presented results showed that the combination of novel statistical indices provides new insights into the trajectories of tidal flats,ecosystem functioning,and sensitivity to physical drivers(wind and tides).Finally,we suggested how the SED and MDS indices may help to explore the future trajectories and climate resilience of intertidal habitats.
基金This work was supported,in part,by the National Nature Science Foundation of China under grant numbers 62272236in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20201136,BK20191401in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business envir-onments.However,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective information.Second,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass differences.These challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective information.To solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature images.Moreover,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature images.In addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of strokes.We respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification methods.This is more helpful to the task of signature authentication in justice and finance.
文摘Identity verification using authenticity evaluation of handwritten signatures is an important issue.There have been several approaches for the verification of signatures using dynamics of the signing process.Most of these approaches extract only global characteristics.With the aim of capturing both dynamic global and local features,this paper introduces a novel model for verifying handwritten dynamic signatures using neutrosophic rule-based verification system(NRVS)and Genetic NRVS(GNRVS)models.The neutrosophic Logic is structured to reflect multiple types of knowledge and relations among all features using three values:truth,indeterminacy,and falsity.These three values are determined by neutrosophic membership functions.The proposed model also is able to deal with all features without the need to select from them.In the GNRVS model,the neutrosophic rules are automatically chosen by Genetic Algorithms.The performance of the proposed system is tested on the MCYT-Signature-100 dataset.In terms of the accuracy,average error rate,false acceptance rate,and false rejection rate,the experimental results indicate that the proposed model has a significant advantage compared to different well-known models.
文摘Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination data and weighting method. By a specific case, i.e. vernier caliper, it is proved that the fit precision and forecast precision of the models are much higher, the cycles are obviously different under different working conditions, and the forecast result of the frequency sequence model is better than that of the time sequence model. Combining dynamic grey model and auto-manufacturing case the controlling and information subsystems of verification cycle and the lifecycle based on information integration, multi-sensor controlling and management controlling were given. The models can be used in production process to help enterprise reduce error, cost and flaw.
基金Supported by the National Natural Science Foun-dation of China (60496315)
文摘The paper proposes an on-line signature verification algorithm, through which test sample and template signatures can be optimizedly matched, based on evolutionary computation (EC). Firstly, the similarity of signature curve segment is defined, and shift and scale transforms are also introduced due to the randoness of on-line signature. Secondly, this paper puts forward signature verification matching algorithm after establishment of the mathematical model. Thirdly, the concrete realization of the algorithm based on EC is discussed as well. In addition, the influence of shift and scale on the matching result is fully considered in the algorithm. Finally, a computation example is given, and the matching results between the test sample curve and the template signature curve are analyzed in detail. The preliminary experiments reveal that the type of signature verification problem can be solved by EC.
基金Project supported by the National Basic Research Program of China (973 Program) (Grant No 2007CB311100)the National High Technology Research and Development Program of China (Grant Nos 2006AA01Z419 and 20060101Z4015)+4 种基金the Major Research plan of the National Natural Science Foundation of China (Grant No 90604023)2008 Scientific Research Common Program of Beijing Municipal Commission of Education The Scientific Research Foundation for the Youth of Beijing University of Technology (Grant No 97007016200701)the National Research Foundation for the Doctoral Program of Higher Educationof China (Grant No 20040013007)the National Laboratory for Modern Communications Science Foundation of China (GrantNo 9140C1101010601)the Doctor Scientific Research Activation Foundation of Beijing University of Technology (Grant No 52007016200702)
文摘A multi-proxy quantum group signature scheme with threshold shared verification is proposed.An original signer may authorize a proxy group as his proxy agent.Then only the cooperation of all the signers in the proxy group can generate the proxy signature on behalf of the original signer.In the scheme,any t or more of n receivers can verify the message and any t 1 or fewer receivers cannot verify the validity of the proxy signature.
基金Supported by the National Natural Science Foundation of China (No.10671051)the Natural Science Foundation of Zhejiang Province (No.Y105067).
文摘In 2005, Bao, et al. [Appl. Math. and Comput., vol.169, No.2, 2005] showed that Tzeng, et al.’s nonrepudiable threshold multi-proxy multi-signature scheme with shared verification was insecure, and proposed an improved scheme with no Share Distribution Center (SDC). This paper shows that Bao, et al.’s scheme suffers from the proxy relationship inversion attack and forgery attack, and pro- poses an improvement of Bao, et al.’s scheme.
基金The National Natural Science Foundation of China (No60403027)
文摘The short secret key characteristic of elliptic curve cryptosystem(ECC) are integrated with the(t,n) threshold method to create a practical threshold group signature scheme characterized by simultaneous signing.The scheme not only meets the requirements of anonymity and traceability of group signature but also can withstand Tseng and Wang's conspiracy attack.It allows the group manager to add new members and delete old members according to actual application,while the system parameters have a little change.Cryptanalysis result shows that the scheme is efficient and secure.
文摘Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respiratory motion platform;QUASAR phantom) and system log files. Methods: The QUASAR phantom was placed on a treatment couch. Measurement of the point dose and dose distribution was performed for conventional IMRT, with the QUASAR phantom static and moving;for DTT IMRT, this was performed with the phantom moving for pyramid shaped, prostate, paranasal sinus, and pancreas targets. The QUASAR phantom was driven by a sinusoidal signal in the superior-inferior direction. Furthermore, predicted positional errors induced by the Vero4DRT system and mechanical positional errors of the gimbal head, were calculated using the system log files. Results and Conclusion: For DTT IMRT, the dose at the evaluation point was within 3% compared with the verification plan, and the dose distribution in the passing rates of γ was 97.9%, with the criteria of 3% dose and 3 mm distance to agreement. The position error calculated from the log files was within 2 mm, suggesting the feasibility of employing DTT IMRT with high accuracy using the Vero4DRT system.
基金This project was supported by the National Natural Science Foundation of China(No.61571024)the National Key Research and Development Program of China(No.2016YFC1000307)for valuable helps.
文摘In January 2015,the first quantum homomorphic signature scheme was proposed creatively.However,only one verifier is allowed to verify a signature once in this scheme.In order to support repeatable verification for general scenario,we propose a new quantum homomorphic signature scheme with repeatable verification by introducing serial verification model and parallel verification model.Serial verification model solves the problem of signature verification by combining key distribution and Bell measurement.Parallel verification model solves the problem of signature duplication by logically treating one particle of an EPR pair as a quantum signature and physically preparing a new EPR pair.These models will be beneficial to the signature verification of general scenarios.Scheme analysis shows that both intermediate verifiers and terminal verifiers can successfully verify signatures in the same operation with fewer resource consumption,and especially the verified signature in entangled states can be used repeatedly.
文摘This paper presents an off-line handwritten signature verification system based on the Siamese network,where a hybrid architecture is used.The Residual neural Network(ResNet)is used to realize a powerful feature extraction model such that Writer Independent(WI)features can be effectively learned.A single-layer Siamese Neural Network(NN)is used to realize a Writer Dependent(WD)classifier such that the storage space can be minimized.For the purpose of reducing the impact of the high intraclass variability of the signature and ensuring that the Siamese network can learn more effectively,we propose a method of selecting a reference signature as one of the inputs for the Siamese network.To take full advantage of the reference signature,we modify the conventional contrastive loss function to enhance the accuracy.By using the proposed techniques,the accuracy of the system can be increased by 5.9%.Based on the GPDS signature dataset,the proposed system is able to achieve an accuracy of 94.61%which is better than the accuracy achieved by the current state-of-the-art work.
文摘The novel reinforcement to the data glove based dynamic signature verification system, using the Photometric measurement values collected simultaneously from photo plethysmography (PPG) during the signing process is the emerging technology. Skilled forgers try to attempt the genuine signatures in many numbers of trials. The wide gap in the Euclidian distances between forgers and the genuine template features prohibits them from successful forging. This has been proved by our repeated experiments on various subjects using the above combinational features. In addition the intra trial features captured during the forge attempts also differs widely in the case of forgers and are not consistent that of a genuine signature. This is caused by the pulse characteristics and degree of bilateral hand dimensional similarity, and the degrees of pulse delay. Since this economical and simple optical-based technology is offering an improved biometric security, it is essential to look for other reinforcements such the variability factor considerations which we proved of worth considering.
基金Supported by the Scientific Research Plan Projectof the Education Department of Shaanxi Province (06JK197)
文摘In this paper, a new dynamic group signature scheme is proposed. It allows the group manager to increase or delete group members flexibly. Furthermore, the length of group signatures, as well as the computational effort for signing, verifying and opening are very small and independent of the number of group members and deleted group members. So it is efficient.
文摘Valve train dynamic behaviors need to be considered at the beginning of the engine mechanical design,especially during choosing valve spring parameters.From parameter definition to simulation,the valve train parameters around dynamic performance are determined step by step.The valve train dynamic test is done finally to verify the design result since it is a such important facet for valve train design.And reliability from mass production and product life view must be considered during whole design process too.
文摘The bamboo scrimber is an anisotropic material.The elastic constant values of the bamboo scrimber specimens measured by the dynamic and static methods are consistent,and the dynamic test method has the advantages of rapidity,simplicity,good repeatability,and high precision.Bamboo scrimber has strong potential as a building material,and its elastic constant is an important index to measure its mechanical properties.To quickly,simply,non-destructively,and accurately detect the elastic constant of the bamboo scrimber,they were dynamically tested by the free plate transient excitation method and cantilever plate torsional vibration method.The static four-point bending method was used to verify the accuracy and reliability of the dynamic elastic modulus,shear modulus,and Poisson’s ratio of the bamboo scrimber.The mechanism analysis and evaluation of the quality grade,homogeneity,and size effect of the bamboo scrimber whole board were carried out.The main results show that the dynamic elastic modulus,shear modulus,and Poisson’s ratio of the bamboo scrimber are 12 GPa,1500 MPa,and 0.31,respectively,which meet the requirements of GB/T 40247-2021 for structural bamboo scrimber.
