We define a new type cryptographical model called secure multi-party proof that allows any players and a verifier to securely compute a function : each of the players learns nothing about other players’ input and abo...We define a new type cryptographical model called secure multi-party proof that allows any players and a verifier to securely compute a function : each of the players learns nothing about other players’ input and about the value of , and the verifier obtains the value of and it’s validity but learns nothing about the input of any of the players. It is implemented by a protocol using oblivious transfer and Yao’s scrambled circuit. We prove that our protocol is secure if the players and the verifier are semi-honest (i.e. they follow the protocol) and polynomial time bounded. The main applications of our protocol are for electronic voting and electronic bidding.展开更多
We report on the verification of a multi-party contract signing protocol described by Baum-Waidner and Waidner （BW）. Based on Paulson＇s inductive approach, we give the protocol model that includes infinitely many s...We report on the verification of a multi-party contract signing protocol described by Baum-Waidner and Waidner （BW）. Based on Paulson＇s inductive approach, we give the protocol model that includes infinitely many signatories and contract texts signing simuhaneously. We consider composite attacks of the dishonest signatory and the external intruder, formalize cryptographic primitives and protocol arithmetic including attack model, show formal description of key distribution, and prove signature key secrecy theorems and fairness property theorems of the BW protocol using the interactive theorem prover Isabelle/HOL.展开更多
The rapid adoption of machine learning in sensitive domains,such as healthcare,finance,and government services,has heightened the need for robust,privacy-preserving techniques.Traditional machine learning approaches l...The rapid adoption of machine learning in sensitive domains,such as healthcare,finance,and government services,has heightened the need for robust,privacy-preserving techniques.Traditional machine learning approaches lack built-in privacy mechanisms,exposing sensitive data to risks,which motivates the development of Privacy-Preserving Machine Learning(PPML)methods.Despite significant advances in PPML,a comprehensive and focused exploration of Secure Multi-Party Computing(SMPC)within this context remains underdeveloped.This review aims to bridge this knowledge gap by systematically analyzing the role of SMPC in PPML,offering a structured overviewof current techniques,challenges,and future directions.Using a semi-systematicmapping studymethodology,this paper surveys recent literature spanning SMPC protocols,PPML frameworks,implementation approaches,threat models,and performance metrics.Emphasis is placed on identifying trends,technical limitations,and comparative strengths of leading SMPC-based methods.Our findings reveal thatwhile SMPCoffers strong cryptographic guarantees for privacy,challenges such as computational overhead,communication costs,and scalability persist.The paper also discusses critical vulnerabilities,practical deployment issues,and variations in protocol efficiency across use cases.展开更多
Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken us...Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken using component failure rate data to predict PTC for a full stroke test and a partial stroke test.Given the subjective and uncertain aspects of the FMEDA approach,specifically the selection of component failure rates and the determination of the probability of detecting failure modes,a Fuzzy Inference System(FIS)was proposed to manage the data,addressing the inherent uncertainties.Fuzzy inference systems have been used previously for various FMEA type assessments,but this is the first time an FIS has been employed for use with FMEDA.ESDV PTC values were generated from both the standard FMEDA and the fuzzy-FMEDA approaches using data provided by FMEDA experts.This work demonstrates that fuzzy inference systems can address the subjectivity inherent in FMEDA data,enabling reliable estimates of ESDV proof test coverage for both full and partial stroke tests.This facilitates optimized maintenance planning while ensuring safety is not compromised.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
In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic q...In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.展开更多
电影歌曲作为整部电影的有机组成部分,其重要性不可小觑,一首好的歌曲能达到锦上添花的观影效果。目前国内对电影歌词的研究,大多集中在音乐学、美学、文学等语言学之外的领域,从功能语言学的角度对电影歌曲的解读尚且不多。本文拟以系...电影歌曲作为整部电影的有机组成部分,其重要性不可小觑,一首好的歌曲能达到锦上添花的观影效果。目前国内对电影歌词的研究,大多集中在音乐学、美学、文学等语言学之外的领域,从功能语言学的角度对电影歌曲的解读尚且不多。本文拟以系统功能语法理论为指导,从语境、经验功能、人际功能着手解析电影《相助》片尾曲《The Living Proof》,以期丰富系统功能语法的研究内容,为电影歌词的分析提供新的视角,帮助观影者深度理解影片主题。展开更多
文摘We define a new type cryptographical model called secure multi-party proof that allows any players and a verifier to securely compute a function : each of the players learns nothing about other players’ input and about the value of , and the verifier obtains the value of and it’s validity but learns nothing about the input of any of the players. It is implemented by a protocol using oblivious transfer and Yao’s scrambled circuit. We prove that our protocol is secure if the players and the verifier are semi-honest (i.e. they follow the protocol) and polynomial time bounded. The main applications of our protocol are for electronic voting and electronic bidding.
基金Supported by the National Natural Science Foun-dation of China (60373068)
文摘We report on the verification of a multi-party contract signing protocol described by Baum-Waidner and Waidner （BW）. Based on Paulson＇s inductive approach, we give the protocol model that includes infinitely many signatories and contract texts signing simuhaneously. We consider composite attacks of the dishonest signatory and the external intruder, formalize cryptographic primitives and protocol arithmetic including attack model, show formal description of key distribution, and prove signature key secrecy theorems and fairness property theorems of the BW protocol using the interactive theorem prover Isabelle/HOL.
文摘The rapid adoption of machine learning in sensitive domains,such as healthcare,finance,and government services,has heightened the need for robust,privacy-preserving techniques.Traditional machine learning approaches lack built-in privacy mechanisms,exposing sensitive data to risks,which motivates the development of Privacy-Preserving Machine Learning(PPML)methods.Despite significant advances in PPML,a comprehensive and focused exploration of Secure Multi-Party Computing(SMPC)within this context remains underdeveloped.This review aims to bridge this knowledge gap by systematically analyzing the role of SMPC in PPML,offering a structured overviewof current techniques,challenges,and future directions.Using a semi-systematicmapping studymethodology,this paper surveys recent literature spanning SMPC protocols,PPML frameworks,implementation approaches,threat models,and performance metrics.Emphasis is placed on identifying trends,technical limitations,and comparative strengths of leading SMPC-based methods.Our findings reveal thatwhile SMPCoffers strong cryptographic guarantees for privacy,challenges such as computational overhead,communication costs,and scalability persist.The paper also discusses critical vulnerabilities,practical deployment issues,and variations in protocol efficiency across use cases.
文摘Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken using component failure rate data to predict PTC for a full stroke test and a partial stroke test.Given the subjective and uncertain aspects of the FMEDA approach,specifically the selection of component failure rates and the determination of the probability of detecting failure modes,a Fuzzy Inference System(FIS)was proposed to manage the data,addressing the inherent uncertainties.Fuzzy inference systems have been used previously for various FMEA type assessments,but this is the first time an FIS has been employed for use with FMEDA.ESDV PTC values were generated from both the standard FMEDA and the fuzzy-FMEDA approaches using data provided by FMEDA experts.This work demonstrates that fuzzy inference systems can address the subjectivity inherent in FMEDA data,enabling reliable estimates of ESDV proof test coverage for both full and partial stroke tests.This facilitates optimized maintenance planning while ensuring safety is not compromised.
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 in part by the National Natural Science Foundation of China under Grant 62262073in part by the Yunnan Provincial Ten Thousand People Program for Young Top Talents under Grant YNWR-QNBJ-2019-237in part by the Yunnan Provincial Major Science and Technology Special Program under Grant 202402AD080002.
文摘In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.
文摘电影歌曲作为整部电影的有机组成部分,其重要性不可小觑,一首好的歌曲能达到锦上添花的观影效果。目前国内对电影歌词的研究,大多集中在音乐学、美学、文学等语言学之外的领域,从功能语言学的角度对电影歌曲的解读尚且不多。本文拟以系统功能语法理论为指导,从语境、经验功能、人际功能着手解析电影《相助》片尾曲《The Living Proof》,以期丰富系统功能语法的研究内容,为电影歌词的分析提供新的视角,帮助观影者深度理解影片主题。
