Attribute-based encryption(ABE)is a technique used to encrypt data,it has the flexibility of access control,high security,and resistance to collusion attacks,and especially it is used in cloud security protection.Howe...Attribute-based encryption(ABE)is a technique used to encrypt data,it has the flexibility of access control,high security,and resistance to collusion attacks,and especially it is used in cloud security protection.However,a large number of bilinear mappings are used in ABE,and the calculation of bilinear pairing is time-consuming.So there is the problem of low efficiency.On the other hand,the decryption key is not uniquely associated with personal identification information,if the decryption key is maliciously sold,ABE is unable to achieve accountability for the user.In practical applications,shared message requires hierarchical sharing in most cases,in this paper,we present a message security hierarchy ABE scheme for this scenario.Firstly,attributes were grouped and weighted according to the importance of attributes,and then an access structure based on a threshold tree was constructed according to attribute weight.This method saved the computing time for decryption while ensuring security and on-demand access to information for users.In addition,with the help of computing power in the cloud,two-step decryption was used to complete the access,which relieved the computing and storage burden on the client side.Finally,we simulated and tested the scheme based on CP-ABE,and selected different security levels to test its performance.The security proof and the experimental simulation result showthat the proposed scheme has high efficiency and good performance,and the solution implements hierarchical access to the shared message.展开更多
建构在多属性决策序依赖Choquet积分模型之上的层次化多属性评价与决策方法（简称作TOYLC层次分析法）,并没有保证Choquet积分模型所要求的价值测度公度性.另外,它依赖MACBETH （measuring attractiveness by a categorical-based evalu...建构在多属性决策序依赖Choquet积分模型之上的层次化多属性评价与决策方法（简称作TOYLC层次分析法）,并没有保证Choquet积分模型所要求的价值测度公度性.另外,它依赖MACBETH （measuring attractiveness by a categorical-based evaluation technique）所给出的属性集容量判断方法,也存在着对抽象方案进行偏好比较的技术缺陷.针对上述问题,在引入规约性多属性决策属性价值公度方法的基础上,首先给出了类似于摆幅置权判断、能够使决策者进行有意义偏好比较的属性集容量判断赋值方法,然后给出了能够克服TOYLC层次分析法内在缺陷的目标导向序依赖层次分析法.基于案例应用的对比分析表明：在输入信息可比的条件下,目标导向序依赖层次分析法相对于TOYLC层次分析法具有更高的方案评价区分度,从而验证了前者相对于后者的相对科学合理性.展开更多
In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these meas...In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.展开更多
Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems...Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems. Moreover, such systems create security issues whileefficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT datamore secure and reliable in various cloud storage services. Cloud-assisted IoTssuffer from two privacy issues: access policies (public) and super polynomialdecryption times (attributed mainly to complex access structures). We havedeveloped a CP-ABE scheme in alignment with a Hidden HierarchyCiphertext-Policy Attribute-Based Encryption (HH-CP-ABE) access structure embedded within two policies, i.e., public policy and sensitive policy.In this proposed scheme, information is only revealed when the user’sinformation is satisfactory to the public policy. Furthermore, the proposedscheme applies to resource-constrained devices already contracted tasks totrusted servers (especially encryption/decryption/searching). Implementingthe method and keywords search resulted in higher access policy privacy andincreased security. The new scheme introduces superior storage in comparisonto existing systems (CP-ABE, H-CP-ABE), while also decreasing storage costsin HH-CP-ABE. Furthermore, a reduction in time for key generation canalso be noted.Moreover, the scheme proved secure, even in handling IoT datathreats in the Decisional Bilinear Diffie-Hellman (DBDH) case.展开更多
Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and ...Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.展开更多
基金funded by the Funding of Nanjing Institute of Technology No.JXGG2021017the National Natural Science Foundation of China No.61701221.
文摘Attribute-based encryption(ABE)is a technique used to encrypt data,it has the flexibility of access control,high security,and resistance to collusion attacks,and especially it is used in cloud security protection.However,a large number of bilinear mappings are used in ABE,and the calculation of bilinear pairing is time-consuming.So there is the problem of low efficiency.On the other hand,the decryption key is not uniquely associated with personal identification information,if the decryption key is maliciously sold,ABE is unable to achieve accountability for the user.In practical applications,shared message requires hierarchical sharing in most cases,in this paper,we present a message security hierarchy ABE scheme for this scenario.Firstly,attributes were grouped and weighted according to the importance of attributes,and then an access structure based on a threshold tree was constructed according to attribute weight.This method saved the computing time for decryption while ensuring security and on-demand access to information for users.In addition,with the help of computing power in the cloud,two-step decryption was used to complete the access,which relieved the computing and storage burden on the client side.Finally,we simulated and tested the scheme based on CP-ABE,and selected different security levels to test its performance.The security proof and the experimental simulation result showthat the proposed scheme has high efficiency and good performance,and the solution implements hierarchical access to the shared message.
文摘建构在多属性决策序依赖Choquet积分模型之上的层次化多属性评价与决策方法（简称作TOYLC层次分析法）,并没有保证Choquet积分模型所要求的价值测度公度性.另外,它依赖MACBETH （measuring attractiveness by a categorical-based evaluation technique）所给出的属性集容量判断方法,也存在着对抽象方案进行偏好比较的技术缺陷.针对上述问题,在引入规约性多属性决策属性价值公度方法的基础上,首先给出了类似于摆幅置权判断、能够使决策者进行有意义偏好比较的属性集容量判断赋值方法,然后给出了能够克服TOYLC层次分析法内在缺陷的目标导向序依赖层次分析法.基于案例应用的对比分析表明：在输入信息可比的条件下,目标导向序依赖层次分析法相对于TOYLC层次分析法具有更高的方案评价区分度,从而验证了前者相对于后者的相对科学合理性.
文摘In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.
文摘Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems. Moreover, such systems create security issues whileefficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT datamore secure and reliable in various cloud storage services. Cloud-assisted IoTssuffer from two privacy issues: access policies (public) and super polynomialdecryption times (attributed mainly to complex access structures). We havedeveloped a CP-ABE scheme in alignment with a Hidden HierarchyCiphertext-Policy Attribute-Based Encryption (HH-CP-ABE) access structure embedded within two policies, i.e., public policy and sensitive policy.In this proposed scheme, information is only revealed when the user’sinformation is satisfactory to the public policy. Furthermore, the proposedscheme applies to resource-constrained devices already contracted tasks totrusted servers (especially encryption/decryption/searching). Implementingthe method and keywords search resulted in higher access policy privacy andincreased security. The new scheme introduces superior storage in comparisonto existing systems (CP-ABE, H-CP-ABE), while also decreasing storage costsin HH-CP-ABE. Furthermore, a reduction in time for key generation canalso be noted.Moreover, the scheme proved secure, even in handling IoT datathreats in the Decisional Bilinear Diffie-Hellman (DBDH) case.
文摘Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.
