函数加密作为一种多功能的新型公钥加密原语,因其能实现细粒度的密文计算,在云存储中有着广阔的应用前景,受到研究者们的广泛研究.因此,将数据的访问权限控制有机地融合到加解密算法中,实现“部分加解密可控、按需安全计算”是一个非常...函数加密作为一种多功能的新型公钥加密原语,因其能实现细粒度的密文计算,在云存储中有着广阔的应用前景,受到研究者们的广泛研究.因此,将数据的访问权限控制有机地融合到加解密算法中,实现“部分加解密可控、按需安全计算”是一个非常有意义的探索方向.但现有函数加密方案无法精细控制发送者权限且使用了较复杂的理论工具(如不可区分性混淆、多线性映射等),难以满足一些特定应用场合需求.面对量子攻击挑战,如何设计抗量子攻击的特殊、高效的函数加密方案成为一个研究热点.内积函数加密是函数加密的特殊形式,不仅能够实现更复杂的访问控制策略和策略隐藏,而且可以有效地控制数据的“部分访问”,提供更细粒度的查询,在满足数据机密性的同时提高隐私保护.针对更加灵活可控按需安全计算的难点,该文基于格上Learning with errors困难问题提出一种基于身份的细粒度访问控制内积函数加密方案.该方案首先将内积函数与通过原像抽样算法产生的向量相关联,生成函数私钥以此控制接收方的计算能力.其次,引入一个第三方(访问控制中心)充当访问控制功能实施者,通过剩余哈希引理及矩阵的秩检验密文的随机性,完成对密文的重随机化以实现控制发送者权限的目的.最后,接收者将转换后的密文通过内积函数私钥解密,仅计算得到关于原始消息的内积值.理论分析与实验评估表明,所提方案在性能上有明显优势,不仅可以抵御量子攻击,而且能够控制接收者的计算权限与发送者的发送权限,在保护用户数据机密性的同时,有效实现开放环境下数据可用不可见、数据可算不可识的细粒度权限可控密文计算的目标.展开更多
The non-Hermitian skin effect has been applied in multiple fields.However,there are relatively few models in the field of thermal diffusion that utilize the non-Hermitian skin effect for achieving thermal regulation.H...The non-Hermitian skin effect has been applied in multiple fields.However,there are relatively few models in the field of thermal diffusion that utilize the non-Hermitian skin effect for achieving thermal regulation.Here,we propose two non-Hermitian Su-Schrieffer-Heeger(SSH)models for thermal regulation:one capable of achieving edge states,and the other capable of achieving corner states within the thermal field.By analyzing the energy band structures and the generalized Brillouin zone,we predict the appearance of the non-Hermitian skin effect in these two models.Furthermore,we analyze the time-dependent evolution results and assess the robustness of the models.The results indicate that the localized thermal effects of the models align with our predictions.In a word,this work presents two models based on the non-Hermitian skin effect for regulating the thermal field,injecting vitality into the design of non-Hermitian thermal diffusion systems.展开更多
In this paper,a two-step semi-regularized Hermitian and skew-Hermitian splitting(SHSS)iteration method is constructed by introducing a regularization matrix in the(1,1)-block of the first iteration step,to solve the s...In this paper,a two-step semi-regularized Hermitian and skew-Hermitian splitting(SHSS)iteration method is constructed by introducing a regularization matrix in the(1,1)-block of the first iteration step,to solve the saddle-point linear system.By carefully selecting two different regularization matrices,two kinds of SHSS preconditioners are proposed to accelerate the convergence rates of the Krylov subspace iteration methods.Theoretical analysis about the eigenvalue distribution demonstrates that the proposed SHSS preconditioners can make the eigenvalues of the corresponding preconditioned matrices be clustered around 1 and uniformly bounded away from 0.The eigenvector distribution and the upper bound on the degree of the minimal polynomial of the SHSS-preconditioned matrices indicate that the SHSS-preconditioned Krylov subspace iterative methods can converge to the true solution within finite steps in exact arithmetic.In addition,the numerical example derived from the optimal control problem shows that the SHSS preconditioners can significantly improve the convergence speeds of the Krylov subspace iteration methods,and their convergence rates are independent of the discrete mesh size.展开更多
文摘函数加密作为一种多功能的新型公钥加密原语,因其能实现细粒度的密文计算,在云存储中有着广阔的应用前景,受到研究者们的广泛研究.因此,将数据的访问权限控制有机地融合到加解密算法中,实现“部分加解密可控、按需安全计算”是一个非常有意义的探索方向.但现有函数加密方案无法精细控制发送者权限且使用了较复杂的理论工具(如不可区分性混淆、多线性映射等),难以满足一些特定应用场合需求.面对量子攻击挑战,如何设计抗量子攻击的特殊、高效的函数加密方案成为一个研究热点.内积函数加密是函数加密的特殊形式,不仅能够实现更复杂的访问控制策略和策略隐藏,而且可以有效地控制数据的“部分访问”,提供更细粒度的查询,在满足数据机密性的同时提高隐私保护.针对更加灵活可控按需安全计算的难点,该文基于格上Learning with errors困难问题提出一种基于身份的细粒度访问控制内积函数加密方案.该方案首先将内积函数与通过原像抽样算法产生的向量相关联,生成函数私钥以此控制接收方的计算能力.其次,引入一个第三方(访问控制中心)充当访问控制功能实施者,通过剩余哈希引理及矩阵的秩检验密文的随机性,完成对密文的重随机化以实现控制发送者权限的目的.最后,接收者将转换后的密文通过内积函数私钥解密,仅计算得到关于原始消息的内积值.理论分析与实验评估表明,所提方案在性能上有明显优势,不仅可以抵御量子攻击,而且能够控制接收者的计算权限与发送者的发送权限,在保护用户数据机密性的同时,有效实现开放环境下数据可用不可见、数据可算不可识的细粒度权限可控密文计算的目标.
基金supported by the Key Research and Development Program of China(Grant No.2022YFA1405200)the National Natural Science Foundation of China(Grant Nos.92163123 and 52250191)。
文摘The non-Hermitian skin effect has been applied in multiple fields.However,there are relatively few models in the field of thermal diffusion that utilize the non-Hermitian skin effect for achieving thermal regulation.Here,we propose two non-Hermitian Su-Schrieffer-Heeger(SSH)models for thermal regulation:one capable of achieving edge states,and the other capable of achieving corner states within the thermal field.By analyzing the energy band structures and the generalized Brillouin zone,we predict the appearance of the non-Hermitian skin effect in these two models.Furthermore,we analyze the time-dependent evolution results and assess the robustness of the models.The results indicate that the localized thermal effects of the models align with our predictions.In a word,this work presents two models based on the non-Hermitian skin effect for regulating the thermal field,injecting vitality into the design of non-Hermitian thermal diffusion systems.
基金the National Natural Science Foundation of China(No.12001048)R&D Program of Beijing Municipal Education Commission(No.KM202011232019),China.
文摘In this paper,a two-step semi-regularized Hermitian and skew-Hermitian splitting(SHSS)iteration method is constructed by introducing a regularization matrix in the(1,1)-block of the first iteration step,to solve the saddle-point linear system.By carefully selecting two different regularization matrices,two kinds of SHSS preconditioners are proposed to accelerate the convergence rates of the Krylov subspace iteration methods.Theoretical analysis about the eigenvalue distribution demonstrates that the proposed SHSS preconditioners can make the eigenvalues of the corresponding preconditioned matrices be clustered around 1 and uniformly bounded away from 0.The eigenvector distribution and the upper bound on the degree of the minimal polynomial of the SHSS-preconditioned matrices indicate that the SHSS-preconditioned Krylov subspace iterative methods can converge to the true solution within finite steps in exact arithmetic.In addition,the numerical example derived from the optimal control problem shows that the SHSS preconditioners can significantly improve the convergence speeds of the Krylov subspace iteration methods,and their convergence rates are independent of the discrete mesh size.
