The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,com...The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine(EVM)-based smart contract platforms due to their distributed security environment limitations.Existing off-chain methods often result in a significant reduction in contract execution efficiency,thus a platform software development kit interface implementation method has become a feasible way to reduce overheads,but this method cannot verify operation correctness and may leak sensitive user data.To solve the above problems,we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations,especially matrix operations,which can guarantee operation correctness and user privacy while ensuring computational efficiency.In this scheme,a verifiable interaction process is designed to verify the computation process and results,and a matrix blinding technology is introduced to protect sensitive user data in the calculation process.The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.展开更多
In recent years,the field of higher education in China has put forward clear requirements for the construction of ideological and political education in courses.Accounting English,as an important course for cultivatin...In recent years,the field of higher education in China has put forward clear requirements for the construction of ideological and political education in courses.Accounting English,as an important course for cultivating international accounting talents,urgently needs to integrate professional ethics and national consciousness into professional teaching[1].In response to the lack of a professional reference system for ideological and political education in accounting English courses,this paper,guided by the OBE educational concept,constructs a three-dimensional objective matrix model based on the international Certified Public Accountant(CPA)competency framework.By deconstructing the IFAC professional competence standards,a mapping mechanism of“professional competence-language carrier-ideological and political content”is proposed.展开更多
Distributed data fusion is essential for numerous applications,yet faces significant privacy security challenges.Federated learning(FL),as a distributed machine learning paradigm,offers enhanced data privacy protectio...Distributed data fusion is essential for numerous applications,yet faces significant privacy security challenges.Federated learning(FL),as a distributed machine learning paradigm,offers enhanced data privacy protection and has attracted widespread attention.Consequently,research increasingly focuses on developing more secure FL techniques.However,in real-world scenarios involving malicious entities,the accuracy of FL results is often compromised,particularly due to the threat of collusion between two servers.To address this challenge,this paper proposes an efficient and verifiable data aggregation protocol with enhanced privacy protection.After analyzing attack methods against prior schemes,we implement key improvements.Specifically,by incorporating cascaded random numbers and perturbation terms into gradients,we strengthen the privacy protection afforded by polynomial masking,effectively preventing information leakage.Furthermore,our protocol features an enhanced verification mechanism capable of detecting collusive behaviors between two servers.Accuracy testing on the MNIST and CIFAR-10 datasets demonstrates that our protocol maintains accuracy comparable to the Federated Averaging Algorithm.In scheme efficiency comparisons,while incurring only a marginal increase in verification overhead relative to the baseline scheme,our protocol achieves an average improvement of 93.13% in privacy protection and verification overhead compared to the state-of-the-art scheme.This result highlights its optimal balance between overall overhead and functionality.A current limitation is that the verificationmechanismcannot precisely pinpoint the source of anomalies within aggregated results when server-side malicious behavior occurs.Addressing this limitation will be a focus of future research.展开更多
The Internet of Things(IoT)has become an integral part of daily life,making the protection of user privacy increasingly important.In gateway-based IoT systems,user data is transmitted through gateways to platforms,pus...The Internet of Things(IoT)has become an integral part of daily life,making the protection of user privacy increasingly important.In gateway-based IoT systems,user data is transmitted through gateways to platforms,pushing the data to various applications,widely used in smart cities,industrial IoT,smart farms,healthcare IoT,and other fields.Threshold Public Key Encryption(TPKE)provides a method to distribute private keys for decryption,enabling joint decryption by multiple parties,thus ensuring data security during gateway transmission,platform storage,and application access.However,existing TPKE schemes face several limitations,including vulnerability to quantum attacks,failure to meet Simulation-Security(SS)requirements,lack of verifiability,and inefficiency,which results in gateway-based IoT systems still being not secure and efficient enough.To address these challenges,we propose a Verifiable Simulation-Secure Threshold PKE scheme based on standard Module-LWE(VSSTPM).Our scheme resists quantum attacks,achieves SS,and incorporates Non-Interactive ZeroKnowledge(NIZK)proofs.Implementation and performance evaluations demonstrate that VSSTPM offers 112-bit quantum security and outperforms existing TPKE schemes in terms of efficiency.Compared to the ECC-based TPKE scheme,our scheme reduces the time cost for decryption participants by 72.66%,and the decryption verification of their scheme is 11 times slower than ours.Compared with the latest lattice-based TPKE scheme,our scheme reduces the time overhead by 90%and 48.9%in system user encryption and decryption verification,respectively,and their scheme is 13 times slower than ours in terms of decryption participants.展开更多
To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data...To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data structure that is more suitable for streaming data to achieve efficient real-time verifiability for streaming data.Based on the notch gate hash function and vector commitment,an adaptive notch gate hash tree structure is constructed,and an efficient real-time verifiable data structure for on-chain and off-chain stream data is proposed.The structure binds dynamic root nodes sequentially to ordered leaf nodes in its child nodes.Only the vector commitment of the dynamic root node is stored on the chain,and the complete data structure is stored off-chain.This structure ensures tamperproofing against malicious off-chain cloud servers of off-chain cloud servers.Preserves storage scalability space,realizes the immediate verification of stream data upon arrival,and the computational overhead of on-chain and off-chain hybrid storage verification is only related to the current data volume,which is more practical when dealing with stream data with unpredictable data volume.We formalize this as an efficient real-time verification scheme for stream data in on-chain and off-chain hybrid storage.Finally,the technology’s security and performance were empirically validated through rigorous analysis.展开更多
Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server i...Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server introduces critical security vulnerabilities:malicious servers can infer private information from received local model updates or deliberately manipulate aggregation results.Consequently,achieving verifiable aggregation without compromising client privacy remains a critical challenge.To address these problem,we propose a reversible data hiding in encrypted domains(RDHED)scheme,which designs joint secret message embedding and extraction mechanism.This approach enables clients to embed secret messages into ciphertext redundancy spaces generated during model encryption.During the server aggregation process,the embedded messages from all clients fuse within the ciphertext space to form a joint embedding message.Subsequently,clients can decrypt the aggregated results and extract this joint embedding message for verification purposes.Building upon this foundation,we integrate the proposed RDHED scheme with linear homomorphic hash and digital signatures to design a verifiable privacy-preserving aggregation protocol for single-server architectures(VPAFL).Theoretical proofs and experimental analyses show that VPAFL can effectively protect user privacy,achieve lightweight computational and communication overhead of users for verification,and present significant advantages with increasing model dimension.展开更多
To prevent server compromise attack and password guessing attacks,an improved and efficient verifier-based key exchange protocol for three-party is proposed,which enables two clients to agree on a common session key w...To prevent server compromise attack and password guessing attacks,an improved and efficient verifier-based key exchange protocol for three-party is proposed,which enables two clients to agree on a common session key with the help of the server.In this protocol,the client stores a plaintext version of the password,while the server stores a verifier for the password.And the protocol uses verifiers to authenticate between clients and the server.The security analysis and performance comparison of the proposed protocol shows that the protocol can resist many familiar attacks including password guessing attacks,server compromise attacks,man-in-the-middle attacks and Denning-Sacco attacks,and it is more efficient.展开更多
Forest certification is considered to be complementary to forest management policies and takes a significant effect on forest product trade. In recent decade, it has been followed with interest and approved by governm...Forest certification is considered to be complementary to forest management policies and takes a significant effect on forest product trade. In recent decade, it has been followed with interest and approved by governments and forestry de-partments in the world. This paper analyzes the influence of forest certification on forest product trade in the world, including the interest in certification in exporting countries and importing countries, trade flow and business competition, and the demands for Certified Forest Products (CFPs) and also discusses the influence of forest certification on forest product trade in China.展开更多
为了解决不同管理域实体之间身份互认困难的问题,提出一种基于随机摆渡的跨链身份信息互认机制(Cross-block-chain Authenticating Mechanism based on Random Ferrying,CAMRF)。该机制首先通过改进的PageRank算法从普通节点中筛选高信...为了解决不同管理域实体之间身份互认困难的问题,提出一种基于随机摆渡的跨链身份信息互认机制(Cross-block-chain Authenticating Mechanism based on Random Ferrying,CAMRF)。该机制首先通过改进的PageRank算法从普通节点中筛选高信誉候选摆渡节点;然后基于可验证随机函数(VRF)生成共识随机数,动态选举摆渡节点组作为公证人组;最后,由该组节点转发、签名和认证跨域消息,并采用BLS(Boneh-Lynn-Shacham)轻量级聚合签名技术验证消息的真实性与有效性,克服了传统机制存在的中心化依赖强、安全性低的问题。理论分析和实验表明,CAMRF机制具有高互操作性,能有效提高跨域身份认证的安全性和可靠性,具有一定的理论意义和较高的实用价值。展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62272007,U23B2002in part by the Excellent Young Talents Project of the Beijing Municipal University Teacher Team Construction Support Plan under Grant BPHR202203031+1 种基金in part by the Yunnan Key Laboratory of Blockchain Application Technology under Grant 2021105AG070005(YNB202102)in part by the Open Topics of Key Laboratory of Blockchain Technology and Data Security,The Ministry of Industry and Information Technology of the People’s Republic of China under Grant 20243222。
文摘The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine(EVM)-based smart contract platforms due to their distributed security environment limitations.Existing off-chain methods often result in a significant reduction in contract execution efficiency,thus a platform software development kit interface implementation method has become a feasible way to reduce overheads,but this method cannot verify operation correctness and may leak sensitive user data.To solve the above problems,we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations,especially matrix operations,which can guarantee operation correctness and user privacy while ensuring computational efficiency.In this scheme,a verifiable interaction process is designed to verify the computation process and results,and a matrix blinding technology is introduced to protect sensitive user data in the calculation process.The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.
文摘In recent years,the field of higher education in China has put forward clear requirements for the construction of ideological and political education in courses.Accounting English,as an important course for cultivating international accounting talents,urgently needs to integrate professional ethics and national consciousness into professional teaching[1].In response to the lack of a professional reference system for ideological and political education in accounting English courses,this paper,guided by the OBE educational concept,constructs a three-dimensional objective matrix model based on the international Certified Public Accountant(CPA)competency framework.By deconstructing the IFAC professional competence standards,a mapping mechanism of“professional competence-language carrier-ideological and political content”is proposed.
基金supported by National Key R&D Program of China(2023YFB3106100)National Natural Science Foundation of China(62102452,62172436)Natural Science Foundation of Shaanxi Province(2023-JCYB-584).
文摘Distributed data fusion is essential for numerous applications,yet faces significant privacy security challenges.Federated learning(FL),as a distributed machine learning paradigm,offers enhanced data privacy protection and has attracted widespread attention.Consequently,research increasingly focuses on developing more secure FL techniques.However,in real-world scenarios involving malicious entities,the accuracy of FL results is often compromised,particularly due to the threat of collusion between two servers.To address this challenge,this paper proposes an efficient and verifiable data aggregation protocol with enhanced privacy protection.After analyzing attack methods against prior schemes,we implement key improvements.Specifically,by incorporating cascaded random numbers and perturbation terms into gradients,we strengthen the privacy protection afforded by polynomial masking,effectively preventing information leakage.Furthermore,our protocol features an enhanced verification mechanism capable of detecting collusive behaviors between two servers.Accuracy testing on the MNIST and CIFAR-10 datasets demonstrates that our protocol maintains accuracy comparable to the Federated Averaging Algorithm.In scheme efficiency comparisons,while incurring only a marginal increase in verification overhead relative to the baseline scheme,our protocol achieves an average improvement of 93.13% in privacy protection and verification overhead compared to the state-of-the-art scheme.This result highlights its optimal balance between overall overhead and functionality.A current limitation is that the verificationmechanismcannot precisely pinpoint the source of anomalies within aggregated results when server-side malicious behavior occurs.Addressing this limitation will be a focus of future research.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB4400701)the National Natural Science Foundation of China(Nos.62202490,62202339,62172307,U21A20466)。
文摘The Internet of Things(IoT)has become an integral part of daily life,making the protection of user privacy increasingly important.In gateway-based IoT systems,user data is transmitted through gateways to platforms,pushing the data to various applications,widely used in smart cities,industrial IoT,smart farms,healthcare IoT,and other fields.Threshold Public Key Encryption(TPKE)provides a method to distribute private keys for decryption,enabling joint decryption by multiple parties,thus ensuring data security during gateway transmission,platform storage,and application access.However,existing TPKE schemes face several limitations,including vulnerability to quantum attacks,failure to meet Simulation-Security(SS)requirements,lack of verifiability,and inefficiency,which results in gateway-based IoT systems still being not secure and efficient enough.To address these challenges,we propose a Verifiable Simulation-Secure Threshold PKE scheme based on standard Module-LWE(VSSTPM).Our scheme resists quantum attacks,achieves SS,and incorporates Non-Interactive ZeroKnowledge(NIZK)proofs.Implementation and performance evaluations demonstrate that VSSTPM offers 112-bit quantum security and outperforms existing TPKE schemes in terms of efficiency.Compared to the ECC-based TPKE scheme,our scheme reduces the time cost for decryption participants by 72.66%,and the decryption verification of their scheme is 11 times slower than ours.Compared with the latest lattice-based TPKE scheme,our scheme reduces the time overhead by 90%and 48.9%in system user encryption and decryption verification,respectively,and their scheme is 13 times slower than ours in terms of decryption participants.
基金supported by the National Cryptologic Science Fund of China(Grant No.2025NCSF02020)awarded to Yi Sunsupported by the Natural Science Foundation of Henan Province(Grant No.242300420297)awarded to Yi Sun。
文摘To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data structure that is more suitable for streaming data to achieve efficient real-time verifiability for streaming data.Based on the notch gate hash function and vector commitment,an adaptive notch gate hash tree structure is constructed,and an efficient real-time verifiable data structure for on-chain and off-chain stream data is proposed.The structure binds dynamic root nodes sequentially to ordered leaf nodes in its child nodes.Only the vector commitment of the dynamic root node is stored on the chain,and the complete data structure is stored off-chain.This structure ensures tamperproofing against malicious off-chain cloud servers of off-chain cloud servers.Preserves storage scalability space,realizes the immediate verification of stream data upon arrival,and the computational overhead of on-chain and off-chain hybrid storage verification is only related to the current data volume,which is more practical when dealing with stream data with unpredictable data volume.We formalize this as an efficient real-time verification scheme for stream data in on-chain and off-chain hybrid storage.Finally,the technology’s security and performance were empirically validated through rigorous analysis.
基金supported in part by the National Natural Science Foundation of China under Grants 62102450,62272478the Independent Research Project of a Certain Unit under Grant ZZKY20243127.
文摘Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server introduces critical security vulnerabilities:malicious servers can infer private information from received local model updates or deliberately manipulate aggregation results.Consequently,achieving verifiable aggregation without compromising client privacy remains a critical challenge.To address these problem,we propose a reversible data hiding in encrypted domains(RDHED)scheme,which designs joint secret message embedding and extraction mechanism.This approach enables clients to embed secret messages into ciphertext redundancy spaces generated during model encryption.During the server aggregation process,the embedded messages from all clients fuse within the ciphertext space to form a joint embedding message.Subsequently,clients can decrypt the aggregated results and extract this joint embedding message for verification purposes.Building upon this foundation,we integrate the proposed RDHED scheme with linear homomorphic hash and digital signatures to design a verifiable privacy-preserving aggregation protocol for single-server architectures(VPAFL).Theoretical proofs and experimental analyses show that VPAFL can effectively protect user privacy,achieve lightweight computational and communication overhead of users for verification,and present significant advantages with increasing model dimension.
基金The National High Technology Research and Development Program of China(863Program)(No.2001AA115300)the Natural Science Foundation of Liaoning Province(No.20031018,20062023)
文摘To prevent server compromise attack and password guessing attacks,an improved and efficient verifier-based key exchange protocol for three-party is proposed,which enables two clients to agree on a common session key with the help of the server.In this protocol,the client stores a plaintext version of the password,while the server stores a verifier for the password.And the protocol uses verifiers to authenticate between clients and the server.The security analysis and performance comparison of the proposed protocol shows that the protocol can resist many familiar attacks including password guessing attacks,server compromise attacks,man-in-the-middle attacks and Denning-Sacco attacks,and it is more efficient.
文摘Forest certification is considered to be complementary to forest management policies and takes a significant effect on forest product trade. In recent decade, it has been followed with interest and approved by governments and forestry de-partments in the world. This paper analyzes the influence of forest certification on forest product trade in the world, including the interest in certification in exporting countries and importing countries, trade flow and business competition, and the demands for Certified Forest Products (CFPs) and also discusses the influence of forest certification on forest product trade in China.
文摘为了解决不同管理域实体之间身份互认困难的问题,提出一种基于随机摆渡的跨链身份信息互认机制(Cross-block-chain Authenticating Mechanism based on Random Ferrying,CAMRF)。该机制首先通过改进的PageRank算法从普通节点中筛选高信誉候选摆渡节点;然后基于可验证随机函数(VRF)生成共识随机数,动态选举摆渡节点组作为公证人组;最后,由该组节点转发、签名和认证跨域消息,并采用BLS(Boneh-Lynn-Shacham)轻量级聚合签名技术验证消息的真实性与有效性,克服了传统机制存在的中心化依赖强、安全性低的问题。理论分析和实验表明,CAMRF机制具有高互操作性,能有效提高跨域身份认证的安全性和可靠性,具有一定的理论意义和较高的实用价值。
