Homogeneous binary function products are frequently encountered in the sub-universes modeled by databases,spanning from genealogical trees and sports to education and healthcare,etc.Their properties must be discovered...Homogeneous binary function products are frequently encountered in the sub-universes modeled by databases,spanning from genealogical trees and sports to education and healthcare,etc.Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility.The(Elementary)Mathematical Data Model provides 17 types of dyadic-based homogeneous binary function product constraint categories.MatBase,an intelligent data and knowledge base management system prototype,allows database designers to simply declare them by only clicking corresponding checkboxes and automatically generates code for enforcing them.This paper describes the algorithms that MatBase uses for enforcing all 17 types of homogeneous binary function product constraint,which may also be employed by developers without access to MatBase.展开更多
Function secret sharing(FSS)is a secret sharing technique for functions in a specific function class,mainly including distributed point function(DPF)and distributed comparison function(DCF).As an important basis for f...Function secret sharing(FSS)is a secret sharing technique for functions in a specific function class,mainly including distributed point function(DPF)and distributed comparison function(DCF).As an important basis for function secret sharing,DPF and DCF are the foundation for the extension of this technique to other more general and complex function classes.However,the function classes corresponding to the current DPF and DCF schemes are almost all unary function classes,and there is no efficient construction for multivariate function classes.The applications of FSS can be extended with the development of a multivariate scheme,e.g.,a multi-keyword private information retrieval scheme can be constructed.To solve this problem,this paper presents a binary DCF scheme based on the“two-layer binary tree”structure.In a binary tree structure,each node computes the seed of its child nodes based on its own seed.The key technique is to realize the transition transfer of seeds by using oblivious transfer,to connect two unary structures.Theoretical analysis and experimental results show that our binary scheme changes from single-round communication in the original definition to multiround communication,and has great advantages in communication cost and computation efficiency.For the security parameterλand input length n,the key size is reduced from to O(λn^(2))to O(λn)In addition,we explore the extensions and applications of the above method.In the batch computation,this paper uses oblivious transfer(OT)extension to realize the one-time transmission of multiple pairs of seeds and optimize its communication efficiency.By extending the structure from“two-layer”to“multi-layer”,a secret sharing scheme of multivariate mixed basic function is proposed based on the serial thought.Furthermore,by employing the parallel thought,a general 2-layer FSS structure from OT for multivariate mixed basic functions is explored to enhance the efficiency,where the first layer is composed of d parallel binary trees with d representing the input dimension,and the second layer is one binary tree of depth d.And the applications of our schemes in multi-keyword private information retrieval are presented.展开更多
This paper presents a new method for recover- ing paleoporosity of sandstone reservoirs and quantita- tively defines the evolution process of porosity. This method is based on the principle that the present is the key...This paper presents a new method for recover- ing paleoporosity of sandstone reservoirs and quantita- tively defines the evolution process of porosity. This method is based on the principle that the present is the key to the past. We take the middle Es3 member in Niuzhuang Sag, Dongying Depression, and Bohai Bay Basin as an example. The method used in this study considers the present porosity as a constraint condition, and the influences of both constructive diagenesis and destructive diagenesis to divide the porosity evolution process into two independent processes, namely porosity increase and porosity decrease. An evolution model of sandstone porosity can be established by combining both the pore increase and pore decrease effects. Our study reveals that the porosity decrease model is a continuous function of burial depth and burial time, whereas the porosity increase model mainly occurs in an acidified window for paleo- temperature of 70℃ to 90℃. The porosity evolution process can be divided into the following phases： normal compaction, acidification and pore increase, and post- acidification compaction. Thus, the porosity evolution model becomes a piecewise function of three subsections. Examples show that the method can be applied effectively in recovering the paleoporosity of sandstone reservoirs and simulating the porosity evolution process.展开更多
文摘Homogeneous binary function products are frequently encountered in the sub-universes modeled by databases,spanning from genealogical trees and sports to education and healthcare,etc.Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility.The(Elementary)Mathematical Data Model provides 17 types of dyadic-based homogeneous binary function product constraint categories.MatBase,an intelligent data and knowledge base management system prototype,allows database designers to simply declare them by only clicking corresponding checkboxes and automatically generates code for enforcing them.This paper describes the algorithms that MatBase uses for enforcing all 17 types of homogeneous binary function product constraint,which may also be employed by developers without access to MatBase.
基金supported by National Key R&D Program of China(No.2022ZD0161901)the National Natural Science Foundation of China(Grant No.62072023)+3 种基金Beijing Natural Science Foundation(No.4242024)the Open Project Fund of the State Key Laboratory of Cryptology,China(No.MMKFKT202120)the Exploratory Optional Project Fund of the State Key Laboratory of Complex&Critical Software Environment(No.SKLCCSE-2025ZX-XX)the Fundamental Research Funds of Beihang University,China(Nos.YWF-21-BJ-J-1041 and YWF-23-L-1033).
文摘Function secret sharing(FSS)is a secret sharing technique for functions in a specific function class,mainly including distributed point function(DPF)and distributed comparison function(DCF).As an important basis for function secret sharing,DPF and DCF are the foundation for the extension of this technique to other more general and complex function classes.However,the function classes corresponding to the current DPF and DCF schemes are almost all unary function classes,and there is no efficient construction for multivariate function classes.The applications of FSS can be extended with the development of a multivariate scheme,e.g.,a multi-keyword private information retrieval scheme can be constructed.To solve this problem,this paper presents a binary DCF scheme based on the“two-layer binary tree”structure.In a binary tree structure,each node computes the seed of its child nodes based on its own seed.The key technique is to realize the transition transfer of seeds by using oblivious transfer,to connect two unary structures.Theoretical analysis and experimental results show that our binary scheme changes from single-round communication in the original definition to multiround communication,and has great advantages in communication cost and computation efficiency.For the security parameterλand input length n,the key size is reduced from to O(λn^(2))to O(λn)In addition,we explore the extensions and applications of the above method.In the batch computation,this paper uses oblivious transfer(OT)extension to realize the one-time transmission of multiple pairs of seeds and optimize its communication efficiency.By extending the structure from“two-layer”to“multi-layer”,a secret sharing scheme of multivariate mixed basic function is proposed based on the serial thought.Furthermore,by employing the parallel thought,a general 2-layer FSS structure from OT for multivariate mixed basic functions is explored to enhance the efficiency,where the first layer is composed of d parallel binary trees with d representing the input dimension,and the second layer is one binary tree of depth d.And the applications of our schemes in multi-keyword private information retrieval are presented.
文摘This paper presents a new method for recover- ing paleoporosity of sandstone reservoirs and quantita- tively defines the evolution process of porosity. This method is based on the principle that the present is the key to the past. We take the middle Es3 member in Niuzhuang Sag, Dongying Depression, and Bohai Bay Basin as an example. The method used in this study considers the present porosity as a constraint condition, and the influences of both constructive diagenesis and destructive diagenesis to divide the porosity evolution process into two independent processes, namely porosity increase and porosity decrease. An evolution model of sandstone porosity can be established by combining both the pore increase and pore decrease effects. Our study reveals that the porosity decrease model is a continuous function of burial depth and burial time, whereas the porosity increase model mainly occurs in an acidified window for paleo- temperature of 70℃ to 90℃. The porosity evolution process can be divided into the following phases： normal compaction, acidification and pore increase, and post- acidification compaction. Thus, the porosity evolution model becomes a piecewise function of three subsections. Examples show that the method can be applied effectively in recovering the paleoporosity of sandstone reservoirs and simulating the porosity evolution process.
