In this study, we propose a two stage randomized response model. Improved unbiased estimators of the mean number of persons possessing a rare sensitive attribute under two different situations are proposed. The propos...In this study, we propose a two stage randomized response model. Improved unbiased estimators of the mean number of persons possessing a rare sensitive attribute under two different situations are proposed. The proposed estimators are evaluated using a relative efficiency comparison. It is shown that our estimators are efficient as compared to existing estimators when the parameter of rare unrelated attribute is known and in unknown case, depending on the probability of selecting a question.展开更多
Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility...Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.展开更多
Using a bottom simulating reflector(BSR)on a seismic profile to identify marine gas hydrate is a traditional seismic exploration method.However,owing to the abundance differences between the gas hydrate and free gas i...Using a bottom simulating reflector(BSR)on a seismic profile to identify marine gas hydrate is a traditional seismic exploration method.However,owing to the abundance differences between the gas hydrate and free gas in different regions,the BSR may be unremarkable on the seismic profile and invisible in certain cases.With the improvement of exploration precision,difficulty arises in meeting the requirements of distinguishing the abundance differences in the gas hydrate based on BSR.Hence,we studied other sensitive attributes to ascertain the existence of gas hydrate and its abundance variations,eventually improving the success rate of drilling and productivity.In this paper,we analyzed the contradiction between the seismic profile data and drilling sampling data from the Blake Ridge.We extracted different attributes and performed multi-parameter constraint analysis based on the prestack elastic wave impedance inversion.Then,we compared the analysis results with the drilling sampling data.Eventually,we determined five sensitive attributes that can better indicate the existence of gas hydrate and its abundance variations.This method overcomes the limitations of recognizing the gas hydrate methods based on BSR or single inversion attribute.Moreover,the conclusions can notably improve the identification accuracy of marine gas hydrate and provide excellent reference significance for the recognition of marine gas hydrate.Notably,the different geological features of reservoirs feature different sensitivities to the prestacking attributes when using the prestack elastic inversion in different areas.展开更多
Anonymized data publication has received considerable attention from the research community in recent years. For numerical sensitive attributes, most of the existing privacy-preserving data publishing techniques conce...Anonymized data publication has received considerable attention from the research community in recent years. For numerical sensitive attributes, most of the existing privacy-preserving data publishing techniques concentrate on microdata with multiple categorical sensitive attributes or only one numerical sensitive attribute. However, many real-world applications can contain multiple numerical sensitive attributes. Directly applying the existing privacy-preserving techniques for single-numerical-sensitive-attribute and multiple-categorical-sensitive- attributes often causes unexpected disclosure of private information. These techniques are particularly prone to the proximity breach, which is a privacy threat specific to numerical sensitive attributes in data publication, in this paper, we propose a privacy-preserving data publishing method, namely MNSACM, which uses the ideas of clustering and Multi-Sensitive Bucketization （MSB） to publish microdata with multiple numerical sensitive attributes. We use an example to show the effectiveness of this method in privacy protection when using multiple numerical sensitive attributes.展开更多
Although k-anonymity is a good way of publishing microdata for research purposes, it cannot resist severalcommon attacks, such as attribute disclosure and the similarity attack. To resist these attacks, many refinemen...Although k-anonymity is a good way of publishing microdata for research purposes, it cannot resist severalcommon attacks, such as attribute disclosure and the similarity attack. To resist these attacks, many refinements of k-anonymity have been proposed with t-closeness being one of the strictest privacy models. While most existing t-closenessmodels address the case in which the original data have only one single sensitive attribute, data with multiple sensitiveattributes are more common in practice. In this paper, we cover this gap with two proposed algorithms for multiple sensitiveattributes and make the published data satisfy t-closeness. Based on the observation that the values of the sensitive attributesin any equivalence class must be as spread as possible over the entire data to make the published data satisfy t-closeness,both of the algorithms use different methods to partition records into groups in terms of sensitive attributes. One uses aclustering method, while the other leverages the principal component analysis. Then, according to the similarity of quasi-identifier attributes, records are selected from different groups to construct an equivalence class, which will reduce the lossof information as much as possible during anonymization. Our proposed algorithms are evaluated using a real dataset. Theresults show that the average speed of the first proposed algorithm is slower than that of the second proposed algorithm butthe former can preserve more original information. In addition, compared with related approaches, both proposed algorithmscan achieve stronger protection of privacy and reduce less.展开更多
文摘In this study, we propose a two stage randomized response model. Improved unbiased estimators of the mean number of persons possessing a rare sensitive attribute under two different situations are proposed. The proposed estimators are evaluated using a relative efficiency comparison. It is shown that our estimators are efficient as compared to existing estimators when the parameter of rare unrelated attribute is known and in unknown case, depending on the probability of selecting a question.
基金National Natural Science Foundation of China Under Award Number 50878184National High Technology Research and Development Program (863 Program) of China Under Grant No. 2006AA04Z437Graduate Starting Seed Fund of Northwestern Polytechnical University Under the Grant No. Z2012059
文摘Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.
基金supported by the National Natural Science Foundation of China (No. 41230318)
文摘Using a bottom simulating reflector(BSR)on a seismic profile to identify marine gas hydrate is a traditional seismic exploration method.However,owing to the abundance differences between the gas hydrate and free gas in different regions,the BSR may be unremarkable on the seismic profile and invisible in certain cases.With the improvement of exploration precision,difficulty arises in meeting the requirements of distinguishing the abundance differences in the gas hydrate based on BSR.Hence,we studied other sensitive attributes to ascertain the existence of gas hydrate and its abundance variations,eventually improving the success rate of drilling and productivity.In this paper,we analyzed the contradiction between the seismic profile data and drilling sampling data from the Blake Ridge.We extracted different attributes and performed multi-parameter constraint analysis based on the prestack elastic wave impedance inversion.Then,we compared the analysis results with the drilling sampling data.Eventually,we determined five sensitive attributes that can better indicate the existence of gas hydrate and its abundance variations.This method overcomes the limitations of recognizing the gas hydrate methods based on BSR or single inversion attribute.Moreover,the conclusions can notably improve the identification accuracy of marine gas hydrate and provide excellent reference significance for the recognition of marine gas hydrate.Notably,the different geological features of reservoirs feature different sensitivities to the prestacking attributes when using the prestack elastic inversion in different areas.
基金supported by the National Natural Science Foundation of China (No. 61170232)the 985 Project Funding of Sun Yat-sen University+1 种基金State Key Laboratory of Rail Traffic Control and Safety Independent Research (No. RS2012K011)Ministry of Education Funds for Innovative Groups (No. 241147529)
文摘Anonymized data publication has received considerable attention from the research community in recent years. For numerical sensitive attributes, most of the existing privacy-preserving data publishing techniques concentrate on microdata with multiple categorical sensitive attributes or only one numerical sensitive attribute. However, many real-world applications can contain multiple numerical sensitive attributes. Directly applying the existing privacy-preserving techniques for single-numerical-sensitive-attribute and multiple-categorical-sensitive- attributes often causes unexpected disclosure of private information. These techniques are particularly prone to the proximity breach, which is a privacy threat specific to numerical sensitive attributes in data publication, in this paper, we propose a privacy-preserving data publishing method, namely MNSACM, which uses the ideas of clustering and Multi-Sensitive Bucketization （MSB） to publish microdata with multiple numerical sensitive attributes. We use an example to show the effectiveness of this method in privacy protection when using multiple numerical sensitive attributes.
文摘Although k-anonymity is a good way of publishing microdata for research purposes, it cannot resist severalcommon attacks, such as attribute disclosure and the similarity attack. To resist these attacks, many refinements of k-anonymity have been proposed with t-closeness being one of the strictest privacy models. While most existing t-closenessmodels address the case in which the original data have only one single sensitive attribute, data with multiple sensitiveattributes are more common in practice. In this paper, we cover this gap with two proposed algorithms for multiple sensitiveattributes and make the published data satisfy t-closeness. Based on the observation that the values of the sensitive attributesin any equivalence class must be as spread as possible over the entire data to make the published data satisfy t-closeness,both of the algorithms use different methods to partition records into groups in terms of sensitive attributes. One uses aclustering method, while the other leverages the principal component analysis. Then, according to the similarity of quasi-identifier attributes, records are selected from different groups to construct an equivalence class, which will reduce the lossof information as much as possible during anonymization. Our proposed algorithms are evaluated using a real dataset. Theresults show that the average speed of the first proposed algorithm is slower than that of the second proposed algorithm butthe former can preserve more original information. In addition, compared with related approaches, both proposed algorithmscan achieve stronger protection of privacy and reduce less.
