Software vulnerability is always an enormous threat to software security. Quantitative analysis of software vulnerabilities is necessary to the evaluation and improvement of software security. Current vulnerability pr...Software vulnerability is always an enormous threat to software security. Quantitative analysis of software vulnerabilities is necessary to the evaluation and improvement of software security. Current vulnerability prediction models mainly focus on predicting the number of vulnerabilities regardless of the seriousness of vulnerabilities, therefore these models are unable to reflect the security level of software accurately. Starting from this, we propose a vulnerability prediction model based on probit regression in this paper. Unlike traditional ones, we measure the seriousness of vulnerability by the loss it causes and aim at predicting the accumulative vulnerability loss rather than the number of vulnerabilities. To validate our model, experiment is carried out on two soft- ware -- OpenSSL and Xpdf, and the experimental result shows a good performance of our model.展开更多
On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration...On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration with the method of Ordered Probit Regression.As is shown in the results,variables under peasants' personal endowment group and resource of the development group have little impact on peasants' SWB.The variables with observable impact are concentrated in the living condition group and the public atmosphere group.展开更多
基金Supported by the Nuclear High Base Major Special(2012zx01039-004-46)the National Development and Reform Commission Information Security Special(2012-1424)
文摘Software vulnerability is always an enormous threat to software security. Quantitative analysis of software vulnerabilities is necessary to the evaluation and improvement of software security. Current vulnerability prediction models mainly focus on predicting the number of vulnerabilities regardless of the seriousness of vulnerabilities, therefore these models are unable to reflect the security level of software accurately. Starting from this, we propose a vulnerability prediction model based on probit regression in this paper. Unlike traditional ones, we measure the seriousness of vulnerability by the loss it causes and aim at predicting the accumulative vulnerability loss rather than the number of vulnerabilities. To validate our model, experiment is carried out on two soft- ware -- OpenSSL and Xpdf, and the experimental result shows a good performance of our model.
基金supported by the Natural Science Foundation of China(NSFC)[Grant No.71263042],Evaluation of Farmer Development Capability in Poverty-Ridden Areas Liupanshan
文摘On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration with the method of Ordered Probit Regression.As is shown in the results,variables under peasants' personal endowment group and resource of the development group have little impact on peasants' SWB.The variables with observable impact are concentrated in the living condition group and the public atmosphere group.
