With expanding user demands, digital signature techniques are also being expanded greatly, from single signature and single verification techniques to techniques supporting multi-users. This paper presents a new digit...With expanding user demands, digital signature techniques are also being expanded greatly, from single signature and single verification techniques to techniques supporting multi-users. This paper presents a new digital signature scheme with shared verification based on the fiat-shamir signature scheme. This scheme is suitable not only for digital signatures of one public key, but also for situations where multiple public keys are required. In addition, the scheme can resist all kinds of collusion, making it more practicable and safer. Additionally it is more efficient than other schemes.展开更多
Distributed storage can store data in multiple devices or servers to improve data security.However,in today’s explosive growth of network data,traditional distributed storage scheme is faced with some severe challeng...Distributed storage can store data in multiple devices or servers to improve data security.However,in today’s explosive growth of network data,traditional distributed storage scheme is faced with some severe challenges such as insufficient performance,data tampering,and data lose.A distributed storage scheme based on blockchain has been proposed to improve security and efficiency of traditional distributed storage.Under this scheme,the following improvements have been made in this paper.This paper first analyzes the problems faced by distributed storage.Then proposed to build a new distributed storage blockchain scheme with sharding blockchain.The proposed scheme realizes the partitioning of the network and nodes by means of blockchain sharding technology,which can improve the efficiency of data verification between nodes.In addition,this paper uses polynomial commitment to construct a new verifiable secret share scheme called PolyVSS.This new scheme is one of the foundations for building our improved distributed storage blockchain scheme.Compared with the previous scheme,our new scheme does not require a trusted third party and has some new features such as homomorphic and batch opening.The security of VSS can be further improved.Experimental comparisons show that the proposed scheme significantly reduces storage and communication costs.展开更多
A secret sharing scheme permits a secret to be shared among participants in such a way that only qualified subsets of participants can recover the secret. Secret sharing is useful in management of cryptographic keys. ...A secret sharing scheme permits a secret to be shared among participants in such a way that only qualified subsets of participants can recover the secret. Secret sharing is useful in management of cryptographic keys. Based on identity, we analyze the secret sharing scheme among weighted participants. Then we present a dynamic scheme about secret sharing among weighted participants. At last, we analyze the secret sharing scheme among weighted participants, which can make all weighted participants verifiable and dynamic.展开更多
Federated learning for edge computing is a promising solution in the data booming era,which leverages the computation ability of each edge device to train local models and only shares the model gradients to the centra...Federated learning for edge computing is a promising solution in the data booming era,which leverages the computation ability of each edge device to train local models and only shares the model gradients to the central server.However,the frequently transmitted local gradients could also leak the participants’private data.To protect the privacy of local training data,lots of cryptographic-based Privacy-Preserving Federated Learning(PPFL)schemes have been proposed.However,due to the constrained resource nature of mobile devices and complex cryptographic operations,traditional PPFL schemes fail to provide efficient data confidentiality and lightweight integrity verification simultaneously.To tackle this problem,we propose a Verifiable Privacypreserving Federated Learning scheme(VPFL)for edge computing systems to prevent local gradients from leaking over the transmission stage.Firstly,we combine the Distributed Selective Stochastic Gradient Descent(DSSGD)method with Paillier homomorphic cryptosystem to achieve the distributed encryption functionality,so as to reduce the computation cost of the complex cryptosystem.Secondly,we further present an online/offline signature method to realize the lightweight gradients integrity verification,where the offline part can be securely outsourced to the edge server.Comprehensive security analysis demonstrates the proposed VPFL can achieve data confidentiality,authentication,and integrity.At last,we evaluate both communication overhead and computation cost of the proposed VPFL scheme,the experimental results have shown VPFL has low computation costs and communication overheads while maintaining high training accuracy.展开更多
文摘With expanding user demands, digital signature techniques are also being expanded greatly, from single signature and single verification techniques to techniques supporting multi-users. This paper presents a new digital signature scheme with shared verification based on the fiat-shamir signature scheme. This scheme is suitable not only for digital signatures of one public key, but also for situations where multiple public keys are required. In addition, the scheme can resist all kinds of collusion, making it more practicable and safer. Additionally it is more efficient than other schemes.
基金This work was supported by the National Natural Science Foundation of China under Grant 62072249,61772280,61772454,62072056.J.Wang and Y.Ren received the grants,and the URL of the sponsors’website is http://www.nsfc.gov.cn/This work was also supported by the Project of Transformation and Upgrading of Industries and Information Technologies of Jiangsu Province(No.JITC-1900AX2038/01).X.Yu received the grant,and the URL of the sponsors’website is http://gxt.jiangsu.gov.cn/.
文摘Distributed storage can store data in multiple devices or servers to improve data security.However,in today’s explosive growth of network data,traditional distributed storage scheme is faced with some severe challenges such as insufficient performance,data tampering,and data lose.A distributed storage scheme based on blockchain has been proposed to improve security and efficiency of traditional distributed storage.Under this scheme,the following improvements have been made in this paper.This paper first analyzes the problems faced by distributed storage.Then proposed to build a new distributed storage blockchain scheme with sharding blockchain.The proposed scheme realizes the partitioning of the network and nodes by means of blockchain sharding technology,which can improve the efficiency of data verification between nodes.In addition,this paper uses polynomial commitment to construct a new verifiable secret share scheme called PolyVSS.This new scheme is one of the foundations for building our improved distributed storage blockchain scheme.Compared with the previous scheme,our new scheme does not require a trusted third party and has some new features such as homomorphic and batch opening.The security of VSS can be further improved.Experimental comparisons show that the proposed scheme significantly reduces storage and communication costs.
基金The research is supported by Research Funds of Information Security and Secrecy Laboratory of Beijing Electronic Science ＆： Technology Institute under Grant No. YZDJ0712, partially by National Basic Research Program under Grant No. 2004CB318000, and Beijing Municipal Natural Science Foundation under Grant No. 406：3040.
文摘A secret sharing scheme permits a secret to be shared among participants in such a way that only qualified subsets of participants can recover the secret. Secret sharing is useful in management of cryptographic keys. Based on identity, we analyze the secret sharing scheme among weighted participants. Then we present a dynamic scheme about secret sharing among weighted participants. At last, we analyze the secret sharing scheme among weighted participants, which can make all weighted participants verifiable and dynamic.
基金supported by the National Natural Science Foundation of China(No.62206238)the Natural Science Foundation of Jiangsu Province(Grant No.BK20220562)the Natural Science Research Project of Universities in Jiangsu Province(No.22KJB520010).
文摘Federated learning for edge computing is a promising solution in the data booming era,which leverages the computation ability of each edge device to train local models and only shares the model gradients to the central server.However,the frequently transmitted local gradients could also leak the participants’private data.To protect the privacy of local training data,lots of cryptographic-based Privacy-Preserving Federated Learning(PPFL)schemes have been proposed.However,due to the constrained resource nature of mobile devices and complex cryptographic operations,traditional PPFL schemes fail to provide efficient data confidentiality and lightweight integrity verification simultaneously.To tackle this problem,we propose a Verifiable Privacypreserving Federated Learning scheme(VPFL)for edge computing systems to prevent local gradients from leaking over the transmission stage.Firstly,we combine the Distributed Selective Stochastic Gradient Descent(DSSGD)method with Paillier homomorphic cryptosystem to achieve the distributed encryption functionality,so as to reduce the computation cost of the complex cryptosystem.Secondly,we further present an online/offline signature method to realize the lightweight gradients integrity verification,where the offline part can be securely outsourced to the edge server.Comprehensive security analysis demonstrates the proposed VPFL can achieve data confidentiality,authentication,and integrity.At last,we evaluate both communication overhead and computation cost of the proposed VPFL scheme,the experimental results have shown VPFL has low computation costs and communication overheads while maintaining high training accuracy.
