This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication...This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues,therefore the basic and importance of trust management in quantum communication networks should be taken more seriously.Compared with other theories and techniques in quantum communication,the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage.In this paper,the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized,and the trends of each direction in trust management of quantum communication network are discussed in depth.展开更多
In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only de...In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only detect a single type of damage and they require pre-processing operations.This tends to cause a large amount of calculation and low detection precision.To solve these problems,in the work described in this paper a belt tear detection method based on a multi-class conditional deep convolutional generative adversarial network(CDCGAN)was designed.In the traditional DCGAN,the image generated by the generator has a certain degree of randomness.Here,a small number of labeled belt images are taken as conditions and added them to the generator and discriminator,so the generator can generate images with the characteristics of belt damage under the aforementioned conditions.Moreover,because the discriminator cannot identify multiple types of damage,the multi-class softmax function is used as the output function of the discriminator to output a vector of class probabilities,and it can accurately classify cracks,scratches,and tears.To avoid the features learned incompletely,skiplayer connection is adopted in the generator and discriminator.This not only can minimize the loss of features,but also improves the convergence speed.Compared with other algorithms,experimental results show that the loss value of the generator and discriminator is the least.Moreover,its convergence speed is faster,and the mean average precision of the proposed algorithm is up to 96.2%,which is at least 6%higher than that of other algorithms.展开更多
In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-A...In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-Authority(PoA)consensus mechanism,as a lightweight consensus mechanism,is more efficient than traditional Proof-of-Work(PoW)and Proof-of-Stake(PoS),it suffers from the problem of centralization.To this end,on account of analyzing the shortcomings of existing consensus mechanisms,this paper proposes a dynamic reputation-based consensus mechanism for blockchain.This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node,which can monitor the behavior of validators in case that validators with excessive power cause harm to the blockchain network.At the same time,the reputation evaluation algorithm is also introduced to select nodes with high reputation to become validators in the network,thus increasing the cost of malicious behavior.In each consensus cycle,validators and monitoring nodes are dynamically updated according to the reputation value.Through security analysis,it is demonstrated that the scheme can resist the attacks of malicious nodes in the blockchain network.By simulation experiments and analysis of the scheme,the result verifies that the mechanism can effectively improve the fault tolerance of the consensus mechanism,reduce the time of consensus to guarantee the security of the system.展开更多
In the existing Electronic Health Records(EHRs),the medical information of patients is completely controlled by various medical institutions.As such,patients have no dominant power over their own EHRs.These personal d...In the existing Electronic Health Records(EHRs),the medical information of patients is completely controlled by various medical institutions.As such,patients have no dominant power over their own EHRs.These personal data are not only inconvenient to access and share,but are also prone to cause privacy disclosure.The blockchain technology provides a new development direction in the medical field.Blockchain-based EHRs are characterized by decentralization,openness and non-tampering of records,which enable patients to better manage their own EHRs.In order to better protect the privacy of patients,only designated receivers can access EHRs,and receivers can authenticate the sharer to ensure that the EHRs are real and effective.In this study,we propose an identity-based signcryption scheme with multiple authorities for multiple receivers,which can resist N-1 collusion attacks among N authorities.In addition,the identity information of receivers is anonymous,so the relationship between them and the sharer is not disclosed.Under the random oracle model,it was proved that our scheme was secure and met the unforgeability and confidentiality requirements of signcryption.Moreover,we evaluated the performance of the scheme and found that it had the moderate signcryption efficiency and excellent signcryption attributes.展开更多
Under the co-promotion of the wave of urbanization and the rise of data science,smart cities have become the new concept and new practice of urban development.Smart cities are the combination of information technology...Under the co-promotion of the wave of urbanization and the rise of data science,smart cities have become the new concept and new practice of urban development.Smart cities are the combination of information technology represented by the Internet of Things,cloud computing,mobile networks and big data,and urbanization.How to effectively achieve the long-term preservation of massive,heterogeneous,and multi-source digital electronic records in smart cities is a key issue thatmust be solved.Digital continuity can ensure the accessibility,integrity and availability of information.The quality management of electronic record,like the quality management of product,will run through every phase of the urban lifecycle.Based on data quality management,this paper constructs digital continuity of smart city electronic records.Furthermore,thework in this paper ensures the authenticity,integrity,availability and timeliness of electronic documents by quality management of electronic record.This paper elaborates on the overall technical architecture of electronic record,as well as the various technical means needed to protect its four characteristics.展开更多
Access control is one of the core problems in data management system.In this paper,the system requirements were described in three aspects:the traditional access control model,the access control model in the Internet ...Access control is one of the core problems in data management system.In this paper,the system requirements were described in three aspects:the traditional access control model,the access control model in the Internet era and the access control model in the cloud computing environment.Meanwhile,the corresponding major models were listed and their characteristics and problems were analyzed.Finally,the development trend of the corresponding model was proposed.展开更多
The application field of the Internet of Things(IoT)involves all aspects,and its application in the fields of industry,agriculture,environment,transportation,logistics,security and other infrastructure has effectively...The application field of the Internet of Things(IoT)involves all aspects,and its application in the fields of industry,agriculture,environment,transportation,logistics,security and other infrastructure has effectively promoted the intelligent development of these aspects.Although the IoT has gradually grown in recent years,there are still many problems that need to be overcome in terms of technology,management,cost,policy,and security.We need to constantly weigh the benefits of trusting IoT products and the risk of leaking private data.To avoid the leakage and loss of various user data,this paper developed a hybrid algorithm of kernel function and random perturbation method based on the algorithm of non-negative matrix factorization,which realizes personalized recommendation and solves the problem of user privacy data protection in the process of personalized recommendation.Compared to non-negative matrix factorization privacy-preserving algorithm,the new algorithm does not need to know the detailed information of the data,only need to know the connection between each data;and the new algorithm can process the data points with negative characteristics.Experiments show that the new algorithm can produce recommendation results with certain accuracy under the premise of preserving users’personal privacy.展开更多
In view of the low accuracy of traditional ground nephogram recognition model,the authors put forward a k-means algorithm-acquired neural network ensemble method,which takes BP neural network ensemble model as the bas...In view of the low accuracy of traditional ground nephogram recognition model,the authors put forward a k-means algorithm-acquired neural network ensemble method,which takes BP neural network ensemble model as the basis,uses k-means algorithm to choose the individual neural networks with partial diversities for integration,and builds the cloud form classification model.Through simulation experiments on ground nephogram samples,the results show that the algorithm proposed in the article can effectively improve the Classification accuracy of ground nephogram recognition in comparison with applying single BP neural network and traditional BP AdaBoost ensemble algorithm on classification of ground nephogram.展开更多
In this paper,we propose two new attack algorithms on RSA implementations with CRT(Chinese remainder theorem).To improve the attack efficiency considerably,a clustering collision power attack on RSA with CRT is introd...In this paper,we propose two new attack algorithms on RSA implementations with CRT(Chinese remainder theorem).To improve the attack efficiency considerably,a clustering collision power attack on RSA with CRT is introduced via chosen-message pairs.This attack method is that the key parameters dp and dq are segmented by byte,and the modular multiplication collisions are identified by k-means clustering.The exponents dp and dq were recovered by 12 power traces of six groups of the specific message pairs,and the exponent d was obtained.We also propose a second order clustering collision power analysis attack against RSA implementation with CRT,which applies double blinding exponentiation.To reduce noise and artificial participation,we analyze the power points of interest by preprocessing and k-means clustering with horizontal correlation collisions.Thus,we recovered approximately 91%of the secret exponents manipulated with a single power curve on RSA-CRT with countermeasures of double blinding methods.展开更多
In order to solve the problem that real-time face recognition is susceptible to illumination changes,this paper proposes a face recognition method that combines Local Binary Patterns(LBP)and Embedded Hidden Markov Mod...In order to solve the problem that real-time face recognition is susceptible to illumination changes,this paper proposes a face recognition method that combines Local Binary Patterns(LBP)and Embedded Hidden Markov Model(EHMM).Face recognition method.The method firstly performs LBP preprocessing on the input face image,then extracts the feature vector,and finally sends the extracted feature observation vector to the EHMM for training or recognition.Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate.展开更多
Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures.It offers tremendous advantages for enterprises and service providers.It is anticipated tha...Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures.It offers tremendous advantages for enterprises and service providers.It is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a service.To realize access control in a multi-tenant cloud computing environment,this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among tenants.The model consists of three sub-models,which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application scenarios.With an established trust relation in MT-UCON(Multi-tenant Usage Access Control),the trustee can precisely authorize cross-tenant accesses to the trustor’s resources consistent with constraints over the trust relation and other components designated by the trustor.In addition,the security of the model is analyzed by an information flow method.The model adapts to the characteristics of a dynamic and open multi-tenant cloud computing environment and achieves fine-grained access control within and between tenants.展开更多
Lung rehabilitation is safe and feasible,and it has positive benefits in weaning the machine as soon as possible,shortening the time of hospitalization and improving the prognosis of children with mechanical ventilati...Lung rehabilitation is safe and feasible,and it has positive benefits in weaning the machine as soon as possible,shortening the time of hospitalization and improving the prognosis of children with mechanical ventilation.However,at present,the traditional medical concept is deep-rooted,and doctors'understanding of early rehabilitation is inadequate.It is necessary to make in-depth exploration in the relevant guidelines and expert consensus to formulate standardized early rehabilitation diagnosis and treatment procedures and standards for mechanically ventilated children.In the paper,a structured graded lung rehabilitation program is constructed for children with mechanical ventilation to improve their respiratory function,shorten the time of mechanical ventilation and pediatric intensive care unit(PICU)hospitalization,and reduce their anxiety,based on the principal component analysis of functional pneumonia data.Scientific evaluation and dynamic monitoring ensure the safety of the implementation of the program and promote the prognosis and prognosis of the disease.The proposed lung reha-bilitation program provides a reference basis for the formulation of lung rehabilitation guidelines for children with mechanical ventilation.And It has important reference significance for clinical pulmonary rehabilitation to alleviate the concerns of clinicians and lay the foundation for the large-scale promotion of early lung rehabilitation.展开更多
With the diversification of electronic devices,cloud-based services have become the link between different devices.As a cryptosystem with secure conversion function,proxy re-encryption enables secure sharing of data i...With the diversification of electronic devices,cloud-based services have become the link between different devices.As a cryptosystem with secure conversion function,proxy re-encryption enables secure sharing of data in a cloud environment.Proxy re-encryption is a public key encryption system with ciphertext security conversion function.A semi-trusted agent plays the role of ciphertext conversion,which can convert the user ciphertext into the same plaintext encrypted by the principal’s public key.Proxy re-encryption has been a hotspot in the field of information security since it was proposed by Blaze et al.[Blaze,Bleumer and Strauss(1998)].After 20 years of development,proxy re-encryption has evolved into many forms been widely used.This paper elaborates on the definition,characteristics and development status of proxy re-encryption,and classifies proxy re-encryption from the perspectives of user identity,conversion condition,conversion hop count and conversion direction.The aspects of the existing program were compared and briefly reviewed from the aspects of features,performance,and security.Finally,this paper looks forward to the possible development direction of proxy re-encryption in the future.展开更多
Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to...Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.展开更多
In order to enable two parties to exchange their secret information equally,we propose a controlled quantum dialogue protocol based on quantum walks,which implements the equal exchange of secret information between th...In order to enable two parties to exchange their secret information equally,we propose a controlled quantum dialogue protocol based on quantum walks,which implements the equal exchange of secret information between the two parties with the help of the controller TP.The secret information is transmitted via quantum walks,by using this method,the previously required entangled particles do not need to be prepared in the initial phase,and the entangled particles can be produced spontaneously via quantum walks.Furthermore,to resist TP’s dishonest behavior,we use a hash function to verify the correctness of the secret information.The protocol analysis shows that it is safe and reliable facing some attacks,including intercept-measure-resend attack,entanglement attack,dishonest controller’s attack and participant attack.And has a slightly increasing efficiency comparing with the previous protocols.Note that the proposed protocol may be feasible because quantum walks prove to be implemented in different physical systems and experiments.展开更多
Outlier detection is a key research area in data mining technologies,as outlier detection can identify data inconsistent within a data set.Outlier detection aims to find an abnormal data size from a large data size an...Outlier detection is a key research area in data mining technologies,as outlier detection can identify data inconsistent within a data set.Outlier detection aims to find an abnormal data size from a large data size and has been applied in many fields including fraud detection,network intrusion detection,disaster prediction,medical diagnosis,public security,and image processing.While outlier detection has been widely applied in real systems,its effectiveness is challenged by higher dimensions and redundant data attributes,leading to detection errors and complicated calculations.The prevalence of mixed data is a current issue for outlier detection algorithms.An outlier detection method of mixed data based on neighborhood combinatorial entropy is studied to improve outlier detection performance by reducing data dimension using an attribute reduction algorithm.The significance of attributes is determined,and fewer influencing attributes are removed based on neighborhood combinatorial entropy.Outlier detection is conducted using the algorithm of local outlier factor.The proposed outlier detection method can be applied effectively in numerical and mixed multidimensional data using neighborhood combinatorial entropy.In the experimental part of this paper,we give a comparison on outlier detection before and after attribute reduction.In a comparative analysis,we give results of the enhanced outlier detection accuracy by removing the fewer influencing attributes in numerical and mixed multidimensional data.展开更多
With the rapid development of the economy,China’s environment has been damaged severely,which has attracted much attention from scholars and the local government.The concept of green development has been an underlyin...With the rapid development of the economy,China’s environment has been damaged severely,which has attracted much attention from scholars and the local government.The concept of green development has been an underlying trend since 2012,and it is of great significance to explore the relationship between economic growth and environmental quality.Huzhou is a prefecture-level city under the jurisdiction of Zhejiang Province,and it is one of the 27 cities in the central area of the Yangtze River Delta.In recent years,this city develops well not only in economic development but also in maintaining a green environment.In the paper,the back propagation neural network is used to evaluate the local environmental quality.Meanwhile,the panel model is exploited to analyze the relationship between economic growth and environmental quality.All the data presented in the paper range from the year 2008 to 2018.Theoretical analysis indicates that the evaluation value of environmental quality,the emissions of industrial SO2,and waste water exhibit an inverted U-shaped relationship with economic growth.As for the regression results,the inflection point of income in the environmental Kuznets curve of the model which takes the evaluation value of the environmental quality as a dependent variable is higher than that of the model which takes the SO2 emission as an independent variable.The research result would help the local government to take appropriate countermeasures to improve the environment and economy.展开更多
Children's fractures are very common,and many children's fractures need internal fixation.When the children are treated and recovered,it needs to be internally fixed and then taken out.With the development of ...Children's fractures are very common,and many children's fractures need internal fixation.When the children are treated and recovered,it needs to be internally fixed and then taken out.With the development of internal fixation materials,the research of surgical methods and the improvement of surgical skills,postoperative removal of orthopedic surgery patients has gradually been included in daytime surgery.While ensuring the safety of children's surgery,it is necessary to shorten the postoperative limb and joint function recovery time,promote the recovery of limb and joint function,the healing of wounds and bones,and reduce the occurrence of these complications.In order to reduce the occurrence of these complications,carry out early rehabilitation education and development early rehabilitation training is very necessary.This paper puts forward the concept of early rehabilitation based on shared decision model,in which doctors,nurses,children and family members participate in the treatment of children before,during and after operation.The effect of early rehabilitation education in the daytime ward after removal of internal fixation was examined.Moreover,through the analysis of the control trial also confirmed that the clinical effect of early rehabilitation in improving and optimizing the rehabilitation of fracture in children is significant.展开更多
With the rapidly developing of Internet of Things (IoT), the volume ofdata generated by IoT systems is increasing quickly. To release the pressure ofdata management and storage, more and more enterprises and individua...With the rapidly developing of Internet of Things (IoT), the volume ofdata generated by IoT systems is increasing quickly. To release the pressure ofdata management and storage, more and more enterprises and individuals preferto integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted,a variety of methods have been proposed to deal with the problem of data integritychecking. In traditional data integrity audition schemes, the task of data auditing isusually performed by Third Party Auditor (TPA) which is assumed to be trustful.However, in real-life TPA is not trusted as people thought. Therefore, theseschemes suffer from the underlying problem of single-point failure. Moreover,most of the traditional schemes are designed by RSA or bilinear map techniqueswhich consume heavy computation and communication cost. To overcome theseshortcomings, we propose a novel data integrity checking scheme for cloud-IoTdata based on blockchain technique and homomorphic hash. In our scheme, thetags of all data blocks are computed by a homomorphic hash function and storedin blockchain. Moreover, each step within the process of data integrity checking issigned by the performer, and the signatures are stored in blockchain through smartcontracts. As a result, each behavior for data integrity checking in our scheme canbe traced and audited which improves the security of the scheme greatly. Furthermore, batch-audition for multiple data challenges is also supported in our scheme.We formalize the system model of our scheme and give the concrete construction.Detailed performance analyses demonstrate that our proposed scheme is efficientand practical without the trust-assumption of TPA.展开更多
A Generative Adversarial Neural(GAN)network is designed based on deep learning for the Super-Resolution(SR)reconstruction task of temperaturefields(comparable to downscaling in the meteorologicalfield),which is limite...A Generative Adversarial Neural(GAN)network is designed based on deep learning for the Super-Resolution(SR)reconstruction task of temperaturefields(comparable to downscaling in the meteorologicalfield),which is limited by the small number of ground stations and the sparse distribution of observations,resulting in a lack offineness of data.To improve the network’s generalization performance,the residual structure,and batch normalization are used.Applying the nearest interpolation method to avoid over-smoothing of the climate element values instead of the conventional Bicubic interpolation in the computer visionfield.Sub-pixel convolution is used instead of transposed convolution or interpolation methods for up-sampling to speed up network inference.The experimental dataset is the European Centre for Medium-Range Weather Forecasts Reanalysis v5(ERA5)with a bidirectional resolution of 0:1°×0:1°.On the other hand,the task aims to scale up the size by a factor of 8,which is rare compared to conventional methods.The comparison methods include traditional interpolation methods and a more widely used GAN-based network such as the SRGAN.Thefinal experimental results show that the proposed scheme advances the performance of Root Mean Square Error(RMSE)by 37.25%,the Peak Signal-to-noise Ratio(PNSR)by 14.4%,and the Structural Similarity(SSIM)by 10.3%compared to the Bicubic Interpolation.For the traditional SRGAN network,a relatively obvious performance improvement is observed by experimental demonstration.Meanwhile,the GAN network can converge stably and reach the approximate Nash equilibrium for various initialization parameters to empirically illustrate the effectiveness of the method in the temperature fields.展开更多
基金This work is supported by the National Natural Science Foundation of China(No.61572086)the Innovation Team of Quantum Security Communication of Sichuan Province(No.17TD0009)+1 种基金the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(No.2016120080102643)the Application Foundation Project of Sichuan Province(No.2017JY0168).
文摘This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues,therefore the basic and importance of trust management in quantum communication networks should be taken more seriously.Compared with other theories and techniques in quantum communication,the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage.In this paper,the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized,and the trends of each direction in trust management of quantum communication network are discussed in depth.
基金This work was supported by the Shanxi Province Applied Basic Research Project,China(Grant No.201901D111100).Xiaoli Hao received the grant,and the URL of the sponsors’website is http://kjt.shanxi.gov.cn/.
文摘In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only detect a single type of damage and they require pre-processing operations.This tends to cause a large amount of calculation and low detection precision.To solve these problems,in the work described in this paper a belt tear detection method based on a multi-class conditional deep convolutional generative adversarial network(CDCGAN)was designed.In the traditional DCGAN,the image generated by the generator has a certain degree of randomness.Here,a small number of labeled belt images are taken as conditions and added them to the generator and discriminator,so the generator can generate images with the characteristics of belt damage under the aforementioned conditions.Moreover,because the discriminator cannot identify multiple types of damage,the multi-class softmax function is used as the output function of the discriminator to output a vector of class probabilities,and it can accurately classify cracks,scratches,and tears.To avoid the features learned incompletely,skiplayer connection is adopted in the generator and discriminator.This not only can minimize the loss of features,but also improves the convergence speed.Compared with other algorithms,experimental results show that the loss value of the generator and discriminator is the least.Moreover,its convergence speed is faster,and the mean average precision of the proposed algorithm is up to 96.2%,which is at least 6%higher than that of other algorithms.
基金This work is supported by the Key Research and Development Project of Sichuan Province(No.2021YFSY0012,No.2020YFG0307,No.2021YFG0332)the Key Research and Development Project of Chengdu(No.2019-YF05-02028-GX)+1 种基金the Innovation Team of Quantum Security Communication of Sichuan Province(No.17TD0009)the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(No.2016120080102643).
文摘In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-Authority(PoA)consensus mechanism,as a lightweight consensus mechanism,is more efficient than traditional Proof-of-Work(PoW)and Proof-of-Stake(PoS),it suffers from the problem of centralization.To this end,on account of analyzing the shortcomings of existing consensus mechanisms,this paper proposes a dynamic reputation-based consensus mechanism for blockchain.This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node,which can monitor the behavior of validators in case that validators with excessive power cause harm to the blockchain network.At the same time,the reputation evaluation algorithm is also introduced to select nodes with high reputation to become validators in the network,thus increasing the cost of malicious behavior.In each consensus cycle,validators and monitoring nodes are dynamically updated according to the reputation value.Through security analysis,it is demonstrated that the scheme can resist the attacks of malicious nodes in the blockchain network.By simulation experiments and analysis of the scheme,the result verifies that the mechanism can effectively improve the fault tolerance of the consensus mechanism,reduce the time of consensus to guarantee the security of the system.
基金This work was supported by the National Key Research and Development Project of China(Grant No.2017YFB0802302)the Science and Technology Support Project of Sichuan Province(Grant Nos.2016FZ0112,2017GZ0314,and 2018GZ0204)+2 种基金the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(Grant No.2016120080102643)the Application Foundation Project of Sichuan Province(Grant No.2017JY0168)the Science and Technology Project of Chengdu(Grant Nos.2017-RK00-00103-ZF,and 2016-HM01-00217-SF).
文摘In the existing Electronic Health Records(EHRs),the medical information of patients is completely controlled by various medical institutions.As such,patients have no dominant power over their own EHRs.These personal data are not only inconvenient to access and share,but are also prone to cause privacy disclosure.The blockchain technology provides a new development direction in the medical field.Blockchain-based EHRs are characterized by decentralization,openness and non-tampering of records,which enable patients to better manage their own EHRs.In order to better protect the privacy of patients,only designated receivers can access EHRs,and receivers can authenticate the sharer to ensure that the EHRs are real and effective.In this study,we propose an identity-based signcryption scheme with multiple authorities for multiple receivers,which can resist N-1 collusion attacks among N authorities.In addition,the identity information of receivers is anonymous,so the relationship between them and the sharer is not disclosed.Under the random oracle model,it was proved that our scheme was secure and met the unforgeability and confidentiality requirements of signcryption.Moreover,we evaluated the performance of the scheme and found that it had the moderate signcryption efficiency and excellent signcryption attributes.
基金the NSFC (Nos. 61772280, 62072249)the AIrecognition scoring system of weather map (No. SYCX202011)+1 种基金the national training programsof innovation and entrepreneurship for undergraduates (Nos. 201910300123Y, 202010300200)the PAPD fund from NUIST. Jinyue Xia is the corresponding author.
文摘Under the co-promotion of the wave of urbanization and the rise of data science,smart cities have become the new concept and new practice of urban development.Smart cities are the combination of information technology represented by the Internet of Things,cloud computing,mobile networks and big data,and urbanization.How to effectively achieve the long-term preservation of massive,heterogeneous,and multi-source digital electronic records in smart cities is a key issue thatmust be solved.Digital continuity can ensure the accessibility,integrity and availability of information.The quality management of electronic record,like the quality management of product,will run through every phase of the urban lifecycle.Based on data quality management,this paper constructs digital continuity of smart city electronic records.Furthermore,thework in this paper ensures the authenticity,integrity,availability and timeliness of electronic documents by quality management of electronic record.This paper elaborates on the overall technical architecture of electronic record,as well as the various technical means needed to protect its four characteristics.
文摘Access control is one of the core problems in data management system.In this paper,the system requirements were described in three aspects:the traditional access control model,the access control model in the Internet era and the access control model in the cloud computing environment.Meanwhile,the corresponding major models were listed and their characteristics and problems were analyzed.Finally,the development trend of the corresponding model was proposed.
基金the National Natural Science Foundation of Chinaunder Grant No.61772280by the China Special Fund for Meteorological Research in the Public Interestunder Grant GYHY201306070by the Jiangsu Province Innovation and Entrepreneurship TrainingProgram for College Students under Grant No.201910300122Y.
文摘The application field of the Internet of Things(IoT)involves all aspects,and its application in the fields of industry,agriculture,environment,transportation,logistics,security and other infrastructure has effectively promoted the intelligent development of these aspects.Although the IoT has gradually grown in recent years,there are still many problems that need to be overcome in terms of technology,management,cost,policy,and security.We need to constantly weigh the benefits of trusting IoT products and the risk of leaking private data.To avoid the leakage and loss of various user data,this paper developed a hybrid algorithm of kernel function and random perturbation method based on the algorithm of non-negative matrix factorization,which realizes personalized recommendation and solves the problem of user privacy data protection in the process of personalized recommendation.Compared to non-negative matrix factorization privacy-preserving algorithm,the new algorithm does not need to know the detailed information of the data,only need to know the connection between each data;and the new algorithm can process the data points with negative characteristics.Experiments show that the new algorithm can produce recommendation results with certain accuracy under the premise of preserving users’personal privacy.
基金This research was supported by the National Natural Science Foundation of China under Grant No.61772280by the China Special Fund for Meteorological Research in the Public Interest under Grant GYHY201306070and by the Jiangsu Province Innovation and Entrepreneurship Training Program for College Students under Grant No.201810300079X。
文摘In view of the low accuracy of traditional ground nephogram recognition model,the authors put forward a k-means algorithm-acquired neural network ensemble method,which takes BP neural network ensemble model as the basis,uses k-means algorithm to choose the individual neural networks with partial diversities for integration,and builds the cloud form classification model.Through simulation experiments on ground nephogram samples,the results show that the algorithm proposed in the article can effectively improve the Classification accuracy of ground nephogram recognition in comparison with applying single BP neural network and traditional BP AdaBoost ensemble algorithm on classification of ground nephogram.
基金supported by the National Key R&D Program of China(No.2017YFB0802300)the Key Research and Development Project of Sichuan Province(No.2020YFG0307,No.2018TJPT0012)the Key Research and Development Project of Chengdu(No.2019-YF05-02028-GX).
文摘In this paper,we propose two new attack algorithms on RSA implementations with CRT(Chinese remainder theorem).To improve the attack efficiency considerably,a clustering collision power attack on RSA with CRT is introduced via chosen-message pairs.This attack method is that the key parameters dp and dq are segmented by byte,and the modular multiplication collisions are identified by k-means clustering.The exponents dp and dq were recovered by 12 power traces of six groups of the specific message pairs,and the exponent d was obtained.We also propose a second order clustering collision power analysis attack against RSA implementation with CRT,which applies double blinding exponentiation.To reduce noise and artificial participation,we analyze the power points of interest by preprocessing and k-means clustering with horizontal correlation collisions.Thus,we recovered approximately 91%of the secret exponents manipulated with a single power curve on RSA-CRT with countermeasures of double blinding methods.
文摘In order to solve the problem that real-time face recognition is susceptible to illumination changes,this paper proposes a face recognition method that combines Local Binary Patterns(LBP)and Embedded Hidden Markov Model(EHMM).Face recognition method.The method firstly performs LBP preprocessing on the input face image,then extracts the feature vector,and finally sends the extracted feature observation vector to the EHMM for training or recognition.Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate.
文摘Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures.It offers tremendous advantages for enterprises and service providers.It is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a service.To realize access control in a multi-tenant cloud computing environment,this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among tenants.The model consists of three sub-models,which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application scenarios.With an established trust relation in MT-UCON(Multi-tenant Usage Access Control),the trustee can precisely authorize cross-tenant accesses to the trustor’s resources consistent with constraints over the trust relation and other components designated by the trustor.In addition,the security of the model is analyzed by an information flow method.The model adapts to the characteristics of a dynamic and open multi-tenant cloud computing environment and achieves fine-grained access control within and between tenants.
基金This work is supported by Science and Technology Development Fund of Nanjing Medical University(No.NJMUB2019188).
文摘Lung rehabilitation is safe and feasible,and it has positive benefits in weaning the machine as soon as possible,shortening the time of hospitalization and improving the prognosis of children with mechanical ventilation.However,at present,the traditional medical concept is deep-rooted,and doctors'understanding of early rehabilitation is inadequate.It is necessary to make in-depth exploration in the relevant guidelines and expert consensus to formulate standardized early rehabilitation diagnosis and treatment procedures and standards for mechanically ventilated children.In the paper,a structured graded lung rehabilitation program is constructed for children with mechanical ventilation to improve their respiratory function,shorten the time of mechanical ventilation and pediatric intensive care unit(PICU)hospitalization,and reduce their anxiety,based on the principal component analysis of functional pneumonia data.Scientific evaluation and dynamic monitoring ensure the safety of the implementation of the program and promote the prognosis and prognosis of the disease.The proposed lung reha-bilitation program provides a reference basis for the formulation of lung rehabilitation guidelines for children with mechanical ventilation.And It has important reference significance for clinical pulmonary rehabilitation to alleviate the concerns of clinicians and lay the foundation for the large-scale promotion of early lung rehabilitation.
基金This work is supported by the NSFC(Nos.61772280,61702236)the Changzhou Sci&Tech Program(No.CJ20179027),and the PAPD fund from NUIST.Prof.
文摘With the diversification of electronic devices,cloud-based services have become the link between different devices.As a cryptosystem with secure conversion function,proxy re-encryption enables secure sharing of data in a cloud environment.Proxy re-encryption is a public key encryption system with ciphertext security conversion function.A semi-trusted agent plays the role of ciphertext conversion,which can convert the user ciphertext into the same plaintext encrypted by the principal’s public key.Proxy re-encryption has been a hotspot in the field of information security since it was proposed by Blaze et al.[Blaze,Bleumer and Strauss(1998)].After 20 years of development,proxy re-encryption has evolved into many forms been widely used.This paper elaborates on the definition,characteristics and development status of proxy re-encryption,and classifies proxy re-encryption from the perspectives of user identity,conversion condition,conversion hop count and conversion direction.The aspects of the existing program were compared and briefly reviewed from the aspects of features,performance,and security.Finally,this paper looks forward to the possible development direction of proxy re-encryption in the future.
基金This research was supported by the National Natural Science Foundation of China under Grant No.61772280by the China Special Fund for Meteorological Research in the Public Interest under Grant GYHY201306070by the Jiangsu Province Innovation and Entrepreneurship Training Program for College Students under Grant No.201810300079X.
文摘Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.
基金This work is supported by the National Natural Science Foundation of China(Nos.61572086 and 61402058)the Key Research and Development Project of Sichuan Province(Nos.20ZDYF2324,2019ZYD027 and 2018TJPT0012)+3 种基金the Innovation Team of Quantum Security Communication of Sichuan Province(No.17TD0009)the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(No.2016120080102643)the Application Foundation Project of Sichuan Province(No.2017JY0168)the Science and Technology Support Project of Sichuan Province(Nos.2018GZ0204 and 2016FZ0112).
文摘In order to enable two parties to exchange their secret information equally,we propose a controlled quantum dialogue protocol based on quantum walks,which implements the equal exchange of secret information between the two parties with the help of the controller TP.The secret information is transmitted via quantum walks,by using this method,the previously required entangled particles do not need to be prepared in the initial phase,and the entangled particles can be produced spontaneously via quantum walks.Furthermore,to resist TP’s dishonest behavior,we use a hash function to verify the correctness of the secret information.The protocol analysis shows that it is safe and reliable facing some attacks,including intercept-measure-resend attack,entanglement attack,dishonest controller’s attack and participant attack.And has a slightly increasing efficiency comparing with the previous protocols.Note that the proposed protocol may be feasible because quantum walks prove to be implemented in different physical systems and experiments.
基金The authors would like to acknowledge the support of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(SML2020SP007)The paper is supported under the National Natural Science Foundation of China(Nos.61772280 and 62072249).
文摘Outlier detection is a key research area in data mining technologies,as outlier detection can identify data inconsistent within a data set.Outlier detection aims to find an abnormal data size from a large data size and has been applied in many fields including fraud detection,network intrusion detection,disaster prediction,medical diagnosis,public security,and image processing.While outlier detection has been widely applied in real systems,its effectiveness is challenged by higher dimensions and redundant data attributes,leading to detection errors and complicated calculations.The prevalence of mixed data is a current issue for outlier detection algorithms.An outlier detection method of mixed data based on neighborhood combinatorial entropy is studied to improve outlier detection performance by reducing data dimension using an attribute reduction algorithm.The significance of attributes is determined,and fewer influencing attributes are removed based on neighborhood combinatorial entropy.Outlier detection is conducted using the algorithm of local outlier factor.The proposed outlier detection method can be applied effectively in numerical and mixed multidimensional data using neighborhood combinatorial entropy.In the experimental part of this paper,we give a comparison on outlier detection before and after attribute reduction.In a comparative analysis,we give results of the enhanced outlier detection accuracy by removing the fewer influencing attributes in numerical and mixed multidimensional data.
基金This work is supported by the project of Philosophy and Social Science Planning in Huzhou city(No.20hzghy079)Na Li received the grant,and the URL to the sponsor’s website is http://www.hzskw.net/.This work is supported by the project of School-enterprise Cooperation of Visiting engineers in Colleges and Universities in Zhejiang(No.FG 2020164)+1 种基金Baiqing Zhou received the grant,and the URL to sponsor’s websites is http://szpx.zjnu.edu.cn/2020/1225%20/c2150a342005/page.psp.This work is also supported by the project of the soft science research program of Zhejiang(No.2021C35007)Duan Lu received the grant,and the URL to the sponsor’s website is http://kjt.zj.gov.cn/art/2020/11/30/.
文摘With the rapid development of the economy,China’s environment has been damaged severely,which has attracted much attention from scholars and the local government.The concept of green development has been an underlying trend since 2012,and it is of great significance to explore the relationship between economic growth and environmental quality.Huzhou is a prefecture-level city under the jurisdiction of Zhejiang Province,and it is one of the 27 cities in the central area of the Yangtze River Delta.In recent years,this city develops well not only in economic development but also in maintaining a green environment.In the paper,the back propagation neural network is used to evaluate the local environmental quality.Meanwhile,the panel model is exploited to analyze the relationship between economic growth and environmental quality.All the data presented in the paper range from the year 2008 to 2018.Theoretical analysis indicates that the evaluation value of environmental quality,the emissions of industrial SO2,and waste water exhibit an inverted U-shaped relationship with economic growth.As for the regression results,the inflection point of income in the environmental Kuznets curve of the model which takes the evaluation value of the environmental quality as a dependent variable is higher than that of the model which takes the SO2 emission as an independent variable.The research result would help the local government to take appropriate countermeasures to improve the environment and economy.
基金supported by Nanjing Medical Science and Technology Development Project(No.YKK13138).
文摘Children's fractures are very common,and many children's fractures need internal fixation.When the children are treated and recovered,it needs to be internally fixed and then taken out.With the development of internal fixation materials,the research of surgical methods and the improvement of surgical skills,postoperative removal of orthopedic surgery patients has gradually been included in daytime surgery.While ensuring the safety of children's surgery,it is necessary to shorten the postoperative limb and joint function recovery time,promote the recovery of limb and joint function,the healing of wounds and bones,and reduce the occurrence of these complications.In order to reduce the occurrence of these complications,carry out early rehabilitation education and development early rehabilitation training is very necessary.This paper puts forward the concept of early rehabilitation based on shared decision model,in which doctors,nurses,children and family members participate in the treatment of children before,during and after operation.The effect of early rehabilitation education in the daytime ward after removal of internal fixation was examined.Moreover,through the analysis of the control trial also confirmed that the clinical effect of early rehabilitation in improving and optimizing the rehabilitation of fracture in children is significant.
基金supported by Program for Scientific Research Foundation for Talented Scholars of Jinling Institute of Technology(No.JIT-B-202031)H.Yan received it and the URLs is www.jit.edu.cn.H.Yan also received the Opening Foundation of Fujian Provincial Key Laboratory of Network Security and Cryptology Research Fund of Fujian Normal University(NSCL-KF2021-02)and the URLs is www.fjnu.edu.cn.Y.Liu received the funding of the National Natural Science Foundation of China(No.61902163,)the URLs is www.nsfc.gov.cn.S.Hu received the funding of the Science and Technology Project of Education Department in Jiangxi Province(No.GJJ201402)and the URLs is www.gnnu.cn.
文摘With the rapidly developing of Internet of Things (IoT), the volume ofdata generated by IoT systems is increasing quickly. To release the pressure ofdata management and storage, more and more enterprises and individuals preferto integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted,a variety of methods have been proposed to deal with the problem of data integritychecking. In traditional data integrity audition schemes, the task of data auditing isusually performed by Third Party Auditor (TPA) which is assumed to be trustful.However, in real-life TPA is not trusted as people thought. Therefore, theseschemes suffer from the underlying problem of single-point failure. Moreover,most of the traditional schemes are designed by RSA or bilinear map techniqueswhich consume heavy computation and communication cost. To overcome theseshortcomings, we propose a novel data integrity checking scheme for cloud-IoTdata based on blockchain technique and homomorphic hash. In our scheme, thetags of all data blocks are computed by a homomorphic hash function and storedin blockchain. Moreover, each step within the process of data integrity checking issigned by the performer, and the signatures are stored in blockchain through smartcontracts. As a result, each behavior for data integrity checking in our scheme canbe traced and audited which improves the security of the scheme greatly. Furthermore, batch-audition for multiple data challenges is also supported in our scheme.We formalize the system model of our scheme and give the concrete construction.Detailed performance analyses demonstrate that our proposed scheme is efficientand practical without the trust-assumption of TPA.
基金supported by the National Natural Science Foundation of China under Grant Nos.61772280 and 62072249.
文摘A Generative Adversarial Neural(GAN)network is designed based on deep learning for the Super-Resolution(SR)reconstruction task of temperaturefields(comparable to downscaling in the meteorologicalfield),which is limited by the small number of ground stations and the sparse distribution of observations,resulting in a lack offineness of data.To improve the network’s generalization performance,the residual structure,and batch normalization are used.Applying the nearest interpolation method to avoid over-smoothing of the climate element values instead of the conventional Bicubic interpolation in the computer visionfield.Sub-pixel convolution is used instead of transposed convolution or interpolation methods for up-sampling to speed up network inference.The experimental dataset is the European Centre for Medium-Range Weather Forecasts Reanalysis v5(ERA5)with a bidirectional resolution of 0:1°×0:1°.On the other hand,the task aims to scale up the size by a factor of 8,which is rare compared to conventional methods.The comparison methods include traditional interpolation methods and a more widely used GAN-based network such as the SRGAN.Thefinal experimental results show that the proposed scheme advances the performance of Root Mean Square Error(RMSE)by 37.25%,the Peak Signal-to-noise Ratio(PNSR)by 14.4%,and the Structural Similarity(SSIM)by 10.3%compared to the Bicubic Interpolation.For the traditional SRGAN network,a relatively obvious performance improvement is observed by experimental demonstration.Meanwhile,the GAN network can converge stably and reach the approximate Nash equilibrium for various initialization parameters to empirically illustrate the effectiveness of the method in the temperature fields.
