Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computat...Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computational overhead may result in a significant performance reduction compared with conventional TLS.In this paper,we present a systematic evaluation of PQ-TLS performance across diverse deployment scenarios to address the following critical research questions.(1)What is the performance behavior of PQ-TLS across different TLS modes?(2)How does PQ-TLS perform across varying client scales?(3)Which network topology is most suitable for PQ-TLS?(4)How does PQ-TLS perform on personal computers(PCs)compared to embedded IoT devices?To the best of our knowledge,this is the first work to comprehensively address these issues,offering implementers some insights into PQ-TLS performance and guidance for optimizing it across diverse scenarios.展开更多
针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒...针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒绝采样算法和追踪机制设计了一种可追踪环签名方案,签名算法中使用递归算法压缩了承诺的大小,进一步降低了签名尺寸,在随机预言机模型下证明方案满足可链接性、匿名性和抗陷害性。性能分析表明,签名尺寸与环成员数量为对数大小关系,在环成员数量较多时,公钥的存储开销和签名的通信开销具有明显优势。展开更多
Compared with the traditional crypto- graphy, visual cryptography （VC） decrypts secret images referring to the characteristics of human vision, rather than the cryptography knowledge or complex computations. Further...Compared with the traditional crypto- graphy, visual cryptography （VC） decrypts secret images referring to the characteristics of human vision, rather than the cryptography knowledge or complex computations. Furthermore, seeing to the freeness of the secret key, the whole process of encryption as well as deeryption for the visual cryptography meets a fast dealing course. As to the security concern, it is able to guarantee that no one can have access to any clues about the content of a secret image from individual cover images. Thus, owing to the studies on this area, the target of light-weighted cryptography is reached. Now the visual cryptography has been developed from the meaningless shadows to the meaningful ones. Seeing to the highly developed technique, some advanced VC techniques are introduced in this survey, respectively.展开更多
The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreser...The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.展开更多
The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently...The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.展开更多
Smart cities,as a typical application in the field of the Internet of Things,can combine cloud computing to realize the intelligent control of objects and process massive data.While cloud computing brings convenience ...Smart cities,as a typical application in the field of the Internet of Things,can combine cloud computing to realize the intelligent control of objects and process massive data.While cloud computing brings convenience to smart city services,a serious problem is ensuring that confidential data cannot be leaked to malicious adversaries.Considering the security and privacy of data,data owners transmit sensitive data in its encrypted form to cloud server,which seriously hinders the improvements of potential utilization and efficient sharing.Public key searchable encryption ensures that users can securely retrieve the encrypted data without decryption.However,most existing schemes cannot resist keyword guessing attacks or the size of trapdoors linearly increases with the number of data owners.In this work,by utilizing certificateless encryption and proxy re-encryption,we design an authenticated searchable encryption scheme with constant trapdoors.The designed scheme preserves the privacy of index ciphertexts and keyword trapdoors,and can resist keyword guessing attacks.In addition,data users can generate and upload trapdoors with lower computation and communication overheads.We show that the proposed scheme is suitable for smart city implementations and applications by experimentally evaluating its performance.展开更多
ABSTRACT:Federated Learning(FL)enables collaborative medical model training without sharing sensitive patient data.However,existing FL systems face increasing security risks from post quantum adversaries and often inc...ABSTRACT:Federated Learning(FL)enables collaborative medical model training without sharing sensitive patient data.However,existing FL systems face increasing security risks from post quantum adversaries and often incur nonnegligible computational and communication overhead when encryption is applied.At the same time,training high performance AI models requires large volumes of high quality data,while medical data such as patient information,clinical records,and diagnostic reports are highly sensitive and subject to strict privacy regulations,including HIPAA and GDPR.Traditional centralized machine learning approaches therefore pose significant challenges for cross institutional collaboration in healthcare.To address these limitations,Federated Learning was introduced to allow multiple institutions to jointly train a global model while keeping local data private.Nevertheless,conventional cryptographicmechanisms,such as RSA,are increasingly inadequate for privacy sensitive FL deployments,particularly in the presence of emerging quantum computing threats.Homomorphic encryption,which enables computations to be performed directly on encrypted data,provides an effective solution for preserving data privacy in federated learning systems.This capability allows healthcare institutions to securely perform collaborative model training while remaining compliant with regulatory requirements.Among homomorphic encryption techniques,NTRU,a lattice based cryptographic scheme defined over polynomial rings,offers strong resistance against quantum attacks by relying on the hardness of the Shortest Vector Problem(SVP).Moreover,NTRU supports limited homomorphic operations that are sufficient for secure aggregation in federated learning.In this work,we propose an NTRU enhanced federated learning framework specifically designed for medical and healthcare applications.Experimental results demonstrate that the proposed approach achieves classification performance comparable to standard federated learning,with final accuracy consistently exceeding 0.93.The framework introduces predictable encryption latency on the order of hundreds of milliseconds per training round and a fixed ciphertext communication overhead per client under practical deployment settings.In addition,the proposed systemeffectivelymitigatesmultiple security threats,including quantum computing attacks,by ensuring robust encryption throughout the training process.By integrating the security and homomorphic properties of NTRU,this study establishes a privacy preserving and quantumresistant federated learning framework that supports the secure,legal,and efficient deployment of AI technologies in healthcare,thereby laying a solid foundation for future intelligent healthcare systems.展开更多
TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,th...TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.展开更多
随着神经密码学的出现,越来越多研究使用神经网络来训练加解密算法,其中采用对抗网络可实现端到端的高安全加解密,但存在开销大、速度慢等问题。通过对运算单元核心、数据存储架构和数据流行为进行协同优化设计,提出一种面向神经网络的...随着神经密码学的出现,越来越多研究使用神经网络来训练加解密算法,其中采用对抗网络可实现端到端的高安全加解密,但存在开销大、速度慢等问题。通过对运算单元核心、数据存储架构和数据流行为进行协同优化设计,提出一种面向神经网络的可配置加解密硬件设计方案。该方案首先对加解密模型进行硬件友好型优化,完成网络训练和量化;然后,采用Winograd+DSP48的卷积加速方法,将所需96个乘法器降低到32个;最后,设计CPU控制与调度系统架构,结合动态控制加速器的操作模式,实现高性能可配置加解密硬件电路。实验结果表明,所提方案最高工作频率为133 MHz,功耗为32.4 m W,吞吐量为17.06 GOPs。加解密网络的正确率达100%,破解网络正确率接近50%,硬件电路具备可配置和高安全特性。展开更多
基金Special Fund for Key Technologies in Blockchain of Shanghai Scientific and Technological Committee(23511100300)。
文摘Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computational overhead may result in a significant performance reduction compared with conventional TLS.In this paper,we present a systematic evaluation of PQ-TLS performance across diverse deployment scenarios to address the following critical research questions.(1)What is the performance behavior of PQ-TLS across different TLS modes?(2)How does PQ-TLS perform across varying client scales?(3)Which network topology is most suitable for PQ-TLS?(4)How does PQ-TLS perform on personal computers(PCs)compared to embedded IoT devices?To the best of our knowledge,this is the first work to comprehensively address these issues,offering implementers some insights into PQ-TLS performance and guidance for optimizing it across diverse scenarios.
文摘针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒绝采样算法和追踪机制设计了一种可追踪环签名方案,签名算法中使用递归算法压缩了承诺的大小,进一步降低了签名尺寸,在随机预言机模型下证明方案满足可链接性、匿名性和抗陷害性。性能分析表明,签名尺寸与环成员数量为对数大小关系,在环成员数量较多时,公钥的存储开销和签名的通信开销具有明显优势。
基金supported by National Science Council under Grant No. NSC98-2218-E-035-001-MY3
文摘Compared with the traditional crypto- graphy, visual cryptography （VC） decrypts secret images referring to the characteristics of human vision, rather than the cryptography knowledge or complex computations. Furthermore, seeing to the freeness of the secret key, the whole process of encryption as well as deeryption for the visual cryptography meets a fast dealing course. As to the security concern, it is able to guarantee that no one can have access to any clues about the content of a secret image from individual cover images. Thus, owing to the studies on this area, the target of light-weighted cryptography is reached. Now the visual cryptography has been developed from the meaningless shadows to the meaningful ones. Seeing to the highly developed technique, some advanced VC techniques are introduced in this survey, respectively.
文摘The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.
文摘The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.
基金supported by the Shandong Provincial Key Research and Development Program(No.2021CXGC010107)the National Natural Science Foundation of China(Nos.U21A20466,62325209)+3 种基金the New 20 Project of Higher Education of Jinan(No.202228017)the Special Project on Science and Technology Program of Hubei Province(No.2021BAA025)the Fundamental Research Funds for the Central Universities(Nos.2042023kf0203,20420241013)the Researchers Supporting Project Number(RSP2024R509),King Saud University,Riyadh,Saudi Arabia。
文摘Smart cities,as a typical application in the field of the Internet of Things,can combine cloud computing to realize the intelligent control of objects and process massive data.While cloud computing brings convenience to smart city services,a serious problem is ensuring that confidential data cannot be leaked to malicious adversaries.Considering the security and privacy of data,data owners transmit sensitive data in its encrypted form to cloud server,which seriously hinders the improvements of potential utilization and efficient sharing.Public key searchable encryption ensures that users can securely retrieve the encrypted data without decryption.However,most existing schemes cannot resist keyword guessing attacks or the size of trapdoors linearly increases with the number of data owners.In this work,by utilizing certificateless encryption and proxy re-encryption,we design an authenticated searchable encryption scheme with constant trapdoors.The designed scheme preserves the privacy of index ciphertexts and keyword trapdoors,and can resist keyword guessing attacks.In addition,data users can generate and upload trapdoors with lower computation and communication overheads.We show that the proposed scheme is suitable for smart city implementations and applications by experimentally evaluating its performance.
文摘ABSTRACT:Federated Learning(FL)enables collaborative medical model training without sharing sensitive patient data.However,existing FL systems face increasing security risks from post quantum adversaries and often incur nonnegligible computational and communication overhead when encryption is applied.At the same time,training high performance AI models requires large volumes of high quality data,while medical data such as patient information,clinical records,and diagnostic reports are highly sensitive and subject to strict privacy regulations,including HIPAA and GDPR.Traditional centralized machine learning approaches therefore pose significant challenges for cross institutional collaboration in healthcare.To address these limitations,Federated Learning was introduced to allow multiple institutions to jointly train a global model while keeping local data private.Nevertheless,conventional cryptographicmechanisms,such as RSA,are increasingly inadequate for privacy sensitive FL deployments,particularly in the presence of emerging quantum computing threats.Homomorphic encryption,which enables computations to be performed directly on encrypted data,provides an effective solution for preserving data privacy in federated learning systems.This capability allows healthcare institutions to securely perform collaborative model training while remaining compliant with regulatory requirements.Among homomorphic encryption techniques,NTRU,a lattice based cryptographic scheme defined over polynomial rings,offers strong resistance against quantum attacks by relying on the hardness of the Shortest Vector Problem(SVP).Moreover,NTRU supports limited homomorphic operations that are sufficient for secure aggregation in federated learning.In this work,we propose an NTRU enhanced federated learning framework specifically designed for medical and healthcare applications.Experimental results demonstrate that the proposed approach achieves classification performance comparable to standard federated learning,with final accuracy consistently exceeding 0.93.The framework introduces predictable encryption latency on the order of hundreds of milliseconds per training round and a fixed ciphertext communication overhead per client under practical deployment settings.In addition,the proposed systemeffectivelymitigatesmultiple security threats,including quantum computing attacks,by ensuring robust encryption throughout the training process.By integrating the security and homomorphic properties of NTRU,this study establishes a privacy preserving and quantumresistant federated learning framework that supports the secure,legal,and efficient deployment of AI technologies in healthcare,thereby laying a solid foundation for future intelligent healthcare systems.
文摘TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.
文摘随着神经密码学的出现,越来越多研究使用神经网络来训练加解密算法,其中采用对抗网络可实现端到端的高安全加解密,但存在开销大、速度慢等问题。通过对运算单元核心、数据存储架构和数据流行为进行协同优化设计,提出一种面向神经网络的可配置加解密硬件设计方案。该方案首先对加解密模型进行硬件友好型优化,完成网络训练和量化;然后,采用Winograd+DSP48的卷积加速方法,将所需96个乘法器降低到32个;最后,设计CPU控制与调度系统架构,结合动态控制加速器的操作模式,实现高性能可配置加解密硬件电路。实验结果表明,所提方案最高工作频率为133 MHz,功耗为32.4 m W,吞吐量为17.06 GOPs。加解密网络的正确率达100%,破解网络正确率接近50%,硬件电路具备可配置和高安全特性。
