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
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
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
In traditional secret image sharing schemes,a secret image is shared among shareholders who have the same position.But if the shareholders have two different positions,essential and non‐essential,it is necessary to u...In traditional secret image sharing schemes,a secret image is shared among shareholders who have the same position.But if the shareholders have two different positions,essential and non‐essential,it is necessary to use essential secret image sharing schemes.In this article,a verifiable essential secret image sharing scheme based on HLRs is proposed.Shareholder's share consists of two parts.The first part is produced by the shareholders,which prevents the fraud of dealers.The second part is a shadow image that is produced by using HLRs and the first part of share.The verification of the first part of the shares is done for the first time by using multilinear and bilinear maps.Also,for verifying shadow images,Bloom Filters are used for the first time.The proposed scheme is more efficient than similar schemes,and for the first part of the shares,has formal security.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
Data outsourcing has become an important application of cloud computing.Driven by the growing security demands of data outsourcing applications,sensitive data have to be encrypted before outsourcing.Therefore,how to p...Data outsourcing has become an important application of cloud computing.Driven by the growing security demands of data outsourcing applications,sensitive data have to be encrypted before outsourcing.Therefore,how to properly encrypt data in a way that the encrypted and remotely stored data can still be queried has become a challenging issue.Searchable encryption scheme is proposed to allow users to search over encrypted data.However,most searchable encryption schemes do not consider search result diversification,resulting in information redundancy.In this paper,a verifiable diversity ranking search scheme over encrypted outsourced data is proposed while preserving privacy in cloud computing,which also supports search results verification.The goal is that the ranked documents concerning diversification instead of reading relevant documents that only deliver redundant information.Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is effective for the diversification of documents and verification.展开更多
A new scheme to verifiably redistribute a secret from the old to new shareholders without reconstruction of the secret is presented in this paper. The scheme allows redistribution between different access structures a...A new scheme to verifiably redistribute a secret from the old to new shareholders without reconstruction of the secret is presented in this paper. The scheme allows redistribution between different access structures and between different threshold schemes. A point worth mentioning is that this verifiable secret redistribution (VSR) scheme can identify dishonest old shareholders during redistribution without any assumption. A certain technique is adopted to verify the correctness of the old shares of the secret. As a result, the scheme is very efficient. It can be applied to proactive secret sharing (PSS) schemes to construct more flexible and practical proactive secret sharing schemes.展开更多
Internet of Things(IoT),which provides the solution of connecting things and devices,has increasingly developed as vital tools to realize intelligent life.Generally,source-limited IoT sensors outsource their data to t...Internet of Things(IoT),which provides the solution of connecting things and devices,has increasingly developed as vital tools to realize intelligent life.Generally,source-limited IoT sensors outsource their data to the cloud,which arises the concerns that the transmission of IoT data is happening without appropriate consideration of the profound security challenges involved.Though encryption technology can guarantee the confidentiality of private data,it hinders the usability of data.Searchable encryption(SE)has been proposed to achieve secure data sharing and searching.However,most of existing SE schemes are designed under conventional hardness assumptions and may be vulnerable to the adversary with quantum computers.Moreover,the untrusted cloud server may perform an unfaithful search execution.To address these problems,in this paper,we propose the first verifiable identity-based keyword search(VIBKS)scheme from lattice.In particular,a lattice-based delegation algorithm is adopted to help the data user to verify both the correctness and the integrity of the search results.Besides,in order to reduce the communication overhead,we refer to the identity-based mechanism.We conduct rigorous proof to demonstrate that the proposed VIBKS scheme is ciphertext indistinguishable secure against the semi-honestbut-curious adversary.In addition,we give the detailed computation and communication complexity of our VIBKS and conduct a series of experiments to validate its efficiency performance.展开更多
Outsnurcing computing allows users with resource-constrained devices tn outsnurce their complex computation wnrkloads to cloud servers that may not be honest. In this paper, we propose a new algorithm for securing the...Outsnurcing computing allows users with resource-constrained devices tn outsnurce their complex computation wnrkloads to cloud servers that may not be honest. In this paper, we propose a new algorithm for securing the outsourcing of composite modnlar exponentiation, which is one of the most complex computing tasks in discrete- log based cryptographic protocols. Unlike algorithms based on two untrusted servers, we outsnurce modular expnnentiation operation to only a single server, which eliminates the potential for a cnllusinn attack when using two servers. Moreover, our proposed algorithm can hide the base and exponent of the outsourced data, which prevents the exposure of sensitive information to clnud servers. In addition, compared with the state-of-the-art algorithms, our scheme has remarkably better checkability, The user could detect any misbehavior with a probability of one if the server returns a fault result.展开更多
Decentralized identity authentication is generally based on blockchain, with the protection of user privacy as the core appeal. But traditional decentralized credential system requires users to show all the informatio...Decentralized identity authentication is generally based on blockchain, with the protection of user privacy as the core appeal. But traditional decentralized credential system requires users to show all the information of the entire credential to the verifier, resulting in unnecessary overexposure of personal information. From the perspective of user privacy, this paper proposed a verifiable credential scheme with selective disclosure based on BLS (Bohen- Lynn-Shacham) aggregate signature. Instead of signing the credentials, we sign the claims in the credentials. When the user needs to present the credential to verifier, the user can select a part of but not all claims to be presented. To reduce the number of signatures of claims after selective disclosure, BLS aggregate signature is achieved to aggregate signatures of claims into one signature. In addition, our scheme also supports the aggregation of credentials from different users. As a result, verifier only needs to verify one signature in the credential to achieve the purpose of batch verification of credentials. We analyze the security of our aggregate signature scheme, which can effectively resist aggregate signature forgery attack and credential theft attack. The simulation results show that our selective disclosure scheme based on BLS aggregate signature is acceptable in terms of verification efficiency, and can reduce the storage cost and communication overhead. As a result, our scheme is suitable for blockchain, which is strict on bandwidth and storage overhead.展开更多
As a new computing paradigm, outsourcing computing provides inexpensive, on-demand, convenient storage and computing services for cloud clients. For the security of outsourcing databases to the cloud, it is important ...As a new computing paradigm, outsourcing computing provides inexpensive, on-demand, convenient storage and computing services for cloud clients. For the security of outsourcing databases to the cloud, it is important to allow the user to verify the query results returned by the cloud server. So far, tremendous efforts have been carried out to study secure outsourcing computing. The existing scheme supports that the user can detect the correctness and completeness of the query results even if the cloud server returns an empty set. However, since the data owner performs the database encryption operations and uploads the encrypted database to the cloud server, they require the user to request the data owner to decrypt the query results. In this paper, we propose a new scheme, which can accurately verify the search results. Meanwhile, the users can decrypt the query results independently. Furthermore, the proposed scheme supports a large number of data owners to upload their encrypted database to the cloud server, and it can efficiently verify the query results. Besides, we can prove that our proposed solution can achieve the desired security properties.展开更多
The well-known non-interactive and information-theoretic secure verifiable secret sharing scheme presented by Pedersen is over a large prime. In this paper, we construct a novel non-interactive and information-theoret...The well-known non-interactive and information-theoretic secure verifiable secret sharing scheme presented by Pedersen is over a large prime. In this paper, we construct a novel non-interactive and information-theoretic verifiable secret sharing over RSA （Rivest, Shamir, Adleman） modulus and give the rigorous security proof. It is shown how to distribute a secret among a group such that any set of k parties get no information about the secret. The presented scheme is generally applied to constructions of secure distributed multiplication and threshold or forward-secure signature protocols.展开更多
In blind quantum computation(BQC),a client with weak quantum computation capabilities is allowed to delegate its quantum computation tasks to a server with powerful quantum computation capabilities,and the inputs,algo...In blind quantum computation(BQC),a client with weak quantum computation capabilities is allowed to delegate its quantum computation tasks to a server with powerful quantum computation capabilities,and the inputs,algorithms and outputs of the quantum computation are confidential to the server.Verifiability refers to the ability of the client to verify with a certain probability whether the server has executed the protocol correctly and can be realized by introducing trap qubits into the computation graph state to detect server deception.The existing verifiable universal BQC protocols are analyzed and compared in detail.The XTH protocol(proposed by Xu Q S,Tan X Q,Huang R in 2020),a recent improvement protocol of verifiable universal BQC,uses a sandglass-like graph state to further decrease resource expenditure and enhance verification capability.However,the XTH protocol has two shortcomings:limitations in the coloring scheme and a high probability of accepting an incorrect computation result.In this paper,we present an improved version of the XTH protocol,which revises the limitations of the original coloring scheme and further improves the verification ability.The analysis demonstrates that the resource expenditure is the same as for the XTH protocol,while the probability of accepting the wrong computation result is reduced from the original minimum(0.866)^(d*)to(0.819)^(d^(*)),where d;is the number of repeated executions of the protocol.展开更多
In this present paper, we propose a new proxy blind signature scheme, which is publicly verifiable distributed. The algorithm uses the idea of secret sharing schemes to distribute original signer＇s ability and the po...In this present paper, we propose a new proxy blind signature scheme, which is publicly verifiable distributed. The algorithm uses the idea of secret sharing schemes to distribute original signer＇s ability and the power of the proxy signer, and ensure the property of publicly verifiable secret sharing schemes. A new concept ＂verifiable time period＂ is also introduced to reduce the time cost in the period of verifications and increases the efficiency of our scheme.展开更多
Blockchain is an emerging decentralized technology of electronic voting.The current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of consensus.F...Blockchain is an emerging decentralized technology of electronic voting.The current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of consensus.For practical implementation,the consensus based on random linear block code(RLBC)is proposed and applied to blockchain voting scheme.Along with achieving the record correctness and consistency among all nodes,the consensus method indicates the active and inactive consensus nodes.This ability can assist the management of consensus nodes and restrain the generating of chain forks.To achieve end-to-end verifiability,cast-or-audit and randomized partial checking(RPC)are used in the proposed scheme.The voter can verify the high probability of correctness in ballot encryption and decryption.The experiments illustrate that the efficiency of proposed consensus is suitable for blockchain.The proposed electronic voting scheme is adapted to practical implementation of voting.展开更多
Nowadays,the data that users need to calculate and process increases sharply,however,ordinary users usually lack the required capability.Therefore,resorting to outsourcing computation,they can delegate computing tasks...Nowadays,the data that users need to calculate and process increases sharply,however,ordinary users usually lack the required capability.Therefore,resorting to outsourcing computation,they can delegate computing tasks to high-performance nodes over the network to meet their needs.In order to ensure the correctness of outsourcing computations,a verifiable computing scheme based on the blockchain smart contract is proposed,where the primary node and the replica nodes complete the task calculation and verification respectively,and reach a final consensus on the results.Moreover,the computing resources and energy consumption of each node to make the consensus are analyzed,based on which an optimization of resources allocation is proposed to maximize the transaction throughput.The simulation results show the effectiveness of the proposed scheme built on distributed consensus and also the throughput improvement by optimizing.展开更多
An ([n/3]-1)-resilient Asynchronous Byzantine Agreement Protocol (ABAP) that combines verifiable signature sharing and random secret sharing is proposed. The protocol works in the asynchronous network environment and ...An ([n/3]-1)-resilient Asynchronous Byzantine Agreement Protocol (ABAP) that combines verifiable signature sharing and random secret sharing is proposed. The protocol works in the asynchronous network environment and produces Byzantine agreement within a fixed expected number of computational rounds. The correctness of the protocol is proved in theory.展开更多
Based on a number of sector mitigation policies for domestic systems, this paper demonstrates how measurable, reportable and verifiable （MRV） mechanisms are applied at the sector level in China. At the same time, th...Based on a number of sector mitigation policies for domestic systems, this paper demonstrates how measurable, reportable and verifiable （MRV） mechanisms are applied at the sector level in China. At the same time, these mitigation policies and methods are diverse in terms of the MRV approach and their mitigation effects. These characters should be regulated as part of case foundation in the international construction of MRV.展开更多
Verifiable secret sharing is a special kind of secret sharing. In this paper, A secure and efficient threshold secret sharing scheme is proposed by using the plane parametric curve on the basis of the principle of sec...Verifiable secret sharing is a special kind of secret sharing. In this paper, A secure and efficient threshold secret sharing scheme is proposed by using the plane parametric curve on the basis of the principle of secret sharing. And the performance of this threshold scheme is analyzed. The results reveal that the threshold scheme has its own advantage of one-parameter representation for a master key, and it is a perfect ideal secret sharing scheme. It can easily detect cheaters by single operation in the participants so that the probability of valid cheating is less than 1/p (where p is a large prime).展开更多
The widespread acceptance of machine learning,particularly of neural networks leads to great success in many areas,such as recommender systems,medical predictions,and recognition.It is becoming possible for any indivi...The widespread acceptance of machine learning,particularly of neural networks leads to great success in many areas,such as recommender systems,medical predictions,and recognition.It is becoming possible for any individual with a personal electronic device and Internet access to complete complex machine learning tasks using cloud servers.However,it must be taken into consideration that the data from clients may be exposed to cloud servers.Recent work to preserve data confidentiality has allowed for the outsourcing of services using homomorphic encryption schemes.But these architectures are based on honest but curious cloud servers,which are unable to tell whether cloud servers have completed the computation delegated to the cloud server.This paper proposes a verifiable neural network framework which focuses on solving the problem of data confidentiality and training integrity in machine learning.Specifically,we first leverage homomorphic encryption and extended diagonal packing method to realize a privacy-preserving neural network model efficiently,it enables the user training over encrypted data,thereby protecting the user’s private data.Then,considering the problem that malicious cloud servers are likely to return a wrong result for saving cost,we also integrate a training validation modular Proof-of-Learning,a strategy for verifying the correctness of computations performed during training.Moreover,we introduce practical byzantine fault tolerance to complete the verification progress without a verifiable center.Finally,we conduct a series of experiments to evaluate the performance of the proposed framework,the results show that our construction supports the verifiable training of PPNN based on HE without introducing much computational cost.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.
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.
文摘In traditional secret image sharing schemes,a secret image is shared among shareholders who have the same position.But if the shareholders have two different positions,essential and non‐essential,it is necessary to use essential secret image sharing schemes.In this article,a verifiable essential secret image sharing scheme based on HLRs is proposed.Shareholder's share consists of two parts.The first part is produced by the shareholders,which prevents the fraud of dealers.The second part is a shadow image that is produced by using HLRs and the first part of share.The verification of the first part of the shares is done for the first time by using multilinear and bilinear maps.Also,for verifying shadow images,Bloom Filters are used for the first time.The proposed scheme is more efficient than similar schemes,and for the first part of the shares,has formal security.
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.
基金This work is supported,in part,by the National Natural Science Foundation of China under grant numbers 61103215in part,by Hunan Provincial Natural Science Foundation of China.
文摘Data outsourcing has become an important application of cloud computing.Driven by the growing security demands of data outsourcing applications,sensitive data have to be encrypted before outsourcing.Therefore,how to properly encrypt data in a way that the encrypted and remotely stored data can still be queried has become a challenging issue.Searchable encryption scheme is proposed to allow users to search over encrypted data.However,most searchable encryption schemes do not consider search result diversification,resulting in information redundancy.In this paper,a verifiable diversity ranking search scheme over encrypted outsourced data is proposed while preserving privacy in cloud computing,which also supports search results verification.The goal is that the ranked documents concerning diversification instead of reading relevant documents that only deliver redundant information.Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is effective for the diversification of documents and verification.
文摘A new scheme to verifiably redistribute a secret from the old to new shareholders without reconstruction of the secret is presented in this paper. The scheme allows redistribution between different access structures and between different threshold schemes. A point worth mentioning is that this verifiable secret redistribution (VSR) scheme can identify dishonest old shareholders during redistribution without any assumption. A certain technique is adopted to verify the correctness of the old shares of the secret. As a result, the scheme is very efficient. It can be applied to proactive secret sharing (PSS) schemes to construct more flexible and practical proactive secret sharing schemes.
基金supported by the National Natural Science Foundation of China(No:62072240)the National Key Research and Development Program of China(No.2020YFB1804604).
文摘Internet of Things(IoT),which provides the solution of connecting things and devices,has increasingly developed as vital tools to realize intelligent life.Generally,source-limited IoT sensors outsource their data to the cloud,which arises the concerns that the transmission of IoT data is happening without appropriate consideration of the profound security challenges involved.Though encryption technology can guarantee the confidentiality of private data,it hinders the usability of data.Searchable encryption(SE)has been proposed to achieve secure data sharing and searching.However,most of existing SE schemes are designed under conventional hardness assumptions and may be vulnerable to the adversary with quantum computers.Moreover,the untrusted cloud server may perform an unfaithful search execution.To address these problems,in this paper,we propose the first verifiable identity-based keyword search(VIBKS)scheme from lattice.In particular,a lattice-based delegation algorithm is adopted to help the data user to verify both the correctness and the integrity of the search results.Besides,in order to reduce the communication overhead,we refer to the identity-based mechanism.We conduct rigorous proof to demonstrate that the proposed VIBKS scheme is ciphertext indistinguishable secure against the semi-honestbut-curious adversary.In addition,we give the detailed computation and communication complexity of our VIBKS and conduct a series of experiments to validate its efficiency performance.
文摘Outsnurcing computing allows users with resource-constrained devices tn outsnurce their complex computation wnrkloads to cloud servers that may not be honest. In this paper, we propose a new algorithm for securing the outsourcing of composite modnlar exponentiation, which is one of the most complex computing tasks in discrete- log based cryptographic protocols. Unlike algorithms based on two untrusted servers, we outsnurce modular expnnentiation operation to only a single server, which eliminates the potential for a cnllusinn attack when using two servers. Moreover, our proposed algorithm can hide the base and exponent of the outsourced data, which prevents the exposure of sensitive information to clnud servers. In addition, compared with the state-of-the-art algorithms, our scheme has remarkably better checkability, The user could detect any misbehavior with a probability of one if the server returns a fault result.
文摘Decentralized identity authentication is generally based on blockchain, with the protection of user privacy as the core appeal. But traditional decentralized credential system requires users to show all the information of the entire credential to the verifier, resulting in unnecessary overexposure of personal information. From the perspective of user privacy, this paper proposed a verifiable credential scheme with selective disclosure based on BLS (Bohen- Lynn-Shacham) aggregate signature. Instead of signing the credentials, we sign the claims in the credentials. When the user needs to present the credential to verifier, the user can select a part of but not all claims to be presented. To reduce the number of signatures of claims after selective disclosure, BLS aggregate signature is achieved to aggregate signatures of claims into one signature. In addition, our scheme also supports the aggregation of credentials from different users. As a result, verifier only needs to verify one signature in the credential to achieve the purpose of batch verification of credentials. We analyze the security of our aggregate signature scheme, which can effectively resist aggregate signature forgery attack and credential theft attack. The simulation results show that our selective disclosure scheme based on BLS aggregate signature is acceptable in terms of verification efficiency, and can reduce the storage cost and communication overhead. As a result, our scheme is suitable for blockchain, which is strict on bandwidth and storage overhead.
基金Supported by the National Key Research and Development Program of China(2017YFB0802000)the National Natural Science Foundation of China(61572390,U1736111)+1 种基金the Natural Science Foundation of Ningbo City(201601HJ-B01382)the Open Foundation of Key Laboratory of Cognitive Radio and Information Processing of Ministry of Education(Guilin University of Electronic Technology)(CRKL160202)
文摘As a new computing paradigm, outsourcing computing provides inexpensive, on-demand, convenient storage and computing services for cloud clients. For the security of outsourcing databases to the cloud, it is important to allow the user to verify the query results returned by the cloud server. So far, tremendous efforts have been carried out to study secure outsourcing computing. The existing scheme supports that the user can detect the correctness and completeness of the query results even if the cloud server returns an empty set. However, since the data owner performs the database encryption operations and uploads the encrypted database to the cloud server, they require the user to request the data owner to decrypt the query results. In this paper, we propose a new scheme, which can accurately verify the search results. Meanwhile, the users can decrypt the query results independently. Furthermore, the proposed scheme supports a large number of data owners to upload their encrypted database to the cloud server, and it can efficiently verify the query results. Besides, we can prove that our proposed solution can achieve the desired security properties.
基金Supported by the National Natural Science Foun-dation of China (60403005 ,60573026)
文摘The well-known non-interactive and information-theoretic secure verifiable secret sharing scheme presented by Pedersen is over a large prime. In this paper, we construct a novel non-interactive and information-theoretic verifiable secret sharing over RSA （Rivest, Shamir, Adleman） modulus and give the rigorous security proof. It is shown how to distribute a secret among a group such that any set of k parties get no information about the secret. The presented scheme is generally applied to constructions of secure distributed multiplication and threshold or forward-secure signature protocols.
文摘In blind quantum computation(BQC),a client with weak quantum computation capabilities is allowed to delegate its quantum computation tasks to a server with powerful quantum computation capabilities,and the inputs,algorithms and outputs of the quantum computation are confidential to the server.Verifiability refers to the ability of the client to verify with a certain probability whether the server has executed the protocol correctly and can be realized by introducing trap qubits into the computation graph state to detect server deception.The existing verifiable universal BQC protocols are analyzed and compared in detail.The XTH protocol(proposed by Xu Q S,Tan X Q,Huang R in 2020),a recent improvement protocol of verifiable universal BQC,uses a sandglass-like graph state to further decrease resource expenditure and enhance verification capability.However,the XTH protocol has two shortcomings:limitations in the coloring scheme and a high probability of accepting an incorrect computation result.In this paper,we present an improved version of the XTH protocol,which revises the limitations of the original coloring scheme and further improves the verification ability.The analysis demonstrates that the resource expenditure is the same as for the XTH protocol,while the probability of accepting the wrong computation result is reduced from the original minimum(0.866)^(d*)to(0.819)^(d^(*)),where d;is the number of repeated executions of the protocol.
基金Supported by the National Natural Science Foundation of China (90104035)
文摘In this present paper, we propose a new proxy blind signature scheme, which is publicly verifiable distributed. The algorithm uses the idea of secret sharing schemes to distribute original signer＇s ability and the power of the proxy signer, and ensure the property of publicly verifiable secret sharing schemes. A new concept ＂verifiable time period＂ is also introduced to reduce the time cost in the period of verifications and increases the efficiency of our scheme.
基金Supported by the National Natural Science Foundation of China(No.61501064)Sichuan Technology Support Program(No.2015GZ0088)Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis(No.HCIC201502,HCIC201701)。
文摘Blockchain is an emerging decentralized technology of electronic voting.The current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of consensus.For practical implementation,the consensus based on random linear block code(RLBC)is proposed and applied to blockchain voting scheme.Along with achieving the record correctness and consistency among all nodes,the consensus method indicates the active and inactive consensus nodes.This ability can assist the management of consensus nodes and restrain the generating of chain forks.To achieve end-to-end verifiability,cast-or-audit and randomized partial checking(RPC)are used in the proposed scheme.The voter can verify the high probability of correctness in ballot encryption and decryption.The experiments illustrate that the efficiency of proposed consensus is suitable for blockchain.The proposed electronic voting scheme is adapted to practical implementation of voting.
基金Supported by the National Natural Science Foundation of China(No.61671029)Foundation of Beijing Municipal Commission of Education(No.KM202010005017)Doctoral Fund of Ministry of Education of China(No.2018M640032).
文摘Nowadays,the data that users need to calculate and process increases sharply,however,ordinary users usually lack the required capability.Therefore,resorting to outsourcing computation,they can delegate computing tasks to high-performance nodes over the network to meet their needs.In order to ensure the correctness of outsourcing computations,a verifiable computing scheme based on the blockchain smart contract is proposed,where the primary node and the replica nodes complete the task calculation and verification respectively,and reach a final consensus on the results.Moreover,the computing resources and energy consumption of each node to make the consensus are analyzed,based on which an optimization of resources allocation is proposed to maximize the transaction throughput.The simulation results show the effectiveness of the proposed scheme built on distributed consensus and also the throughput improvement by optimizing.
基金Supported by National Natural Science Foundation of China (No. 60273029)
文摘An ([n/3]-1)-resilient Asynchronous Byzantine Agreement Protocol (ABAP) that combines verifiable signature sharing and random secret sharing is proposed. The protocol works in the asynchronous network environment and produces Byzantine agreement within a fixed expected number of computational rounds. The correctness of the protocol is proved in theory.
基金Ministry of Science and Technology 11th Technology Supporting Key Project 2007BAC03A03-04Ministry of Science and Technology project 2010CB955302
文摘Based on a number of sector mitigation policies for domestic systems, this paper demonstrates how measurable, reportable and verifiable （MRV） mechanisms are applied at the sector level in China. At the same time, these mitigation policies and methods are diverse in terms of the MRV approach and their mitigation effects. These characters should be regulated as part of case foundation in the international construction of MRV.
文摘Verifiable secret sharing is a special kind of secret sharing. In this paper, A secure and efficient threshold secret sharing scheme is proposed by using the plane parametric curve on the basis of the principle of secret sharing. And the performance of this threshold scheme is analyzed. The results reveal that the threshold scheme has its own advantage of one-parameter representation for a master key, and it is a perfect ideal secret sharing scheme. It can easily detect cheaters by single operation in the participants so that the probability of valid cheating is less than 1/p (where p is a large prime).
基金The work is supported by the National Natural Science Foundation of China(No.62072240)the National Natural Science Foundation of China(No.61902156)the Natural Science Foundation of Jiangsu Province under Grant BK20210330.
文摘The widespread acceptance of machine learning,particularly of neural networks leads to great success in many areas,such as recommender systems,medical predictions,and recognition.It is becoming possible for any individual with a personal electronic device and Internet access to complete complex machine learning tasks using cloud servers.However,it must be taken into consideration that the data from clients may be exposed to cloud servers.Recent work to preserve data confidentiality has allowed for the outsourcing of services using homomorphic encryption schemes.But these architectures are based on honest but curious cloud servers,which are unable to tell whether cloud servers have completed the computation delegated to the cloud server.This paper proposes a verifiable neural network framework which focuses on solving the problem of data confidentiality and training integrity in machine learning.Specifically,we first leverage homomorphic encryption and extended diagonal packing method to realize a privacy-preserving neural network model efficiently,it enables the user training over encrypted data,thereby protecting the user’s private data.Then,considering the problem that malicious cloud servers are likely to return a wrong result for saving cost,we also integrate a training validation modular Proof-of-Learning,a strategy for verifying the correctness of computations performed during training.Moreover,we introduce practical byzantine fault tolerance to complete the verification progress without a verifiable center.Finally,we conduct a series of experiments to evaluate the performance of the proposed framework,the results show that our construction supports the verifiable training of PPNN based on HE without introducing much computational cost.
