The object of this study is to propose a statistical model for predicting the Expected Path Length (expected number of steps the attacker will take, starting from the initial state to compromise the security goal—EPL...The object of this study is to propose a statistical model for predicting the Expected Path Length (expected number of steps the attacker will take, starting from the initial state to compromise the security goal—EPL) in a cyber-attack. The model we developed is based on utilizing vulnerability information along with having host centric attack graph. Utilizing the developed model, one can identify the interaction among the vulnerabilities and individual variables (risk factors) that drive the Expected Path Length. Gaining a better understanding of the relationship between vulnerabilities and their interactions can provide security administrators a better view and an understanding of their security status. In addition, we have also ranked the attributable variables and their contribution in estimating the subject length. Thus, one can utilize the ranking process to take precautions and actions to minimize Expected Path Length.展开更多
This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" ...This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" "=""><span style="font-family:Verdana;"> of the binomial distribution. Evidence in the literature indicates the standard Wald confidence interval for the binomial proportion is inaccurate, especially for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Even for moderately large sample sizes, the coverage probabilities of the Wald confidence interval prove to be erratic for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Three alternative confidence intervals, namely, Wilson confidence interval, Clopper-Pearson interval, and likelihood interval</span></span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> are compared to the Wald confidence interval on the basis of coverage probability and expected length by means of simulation.</span>展开更多
文摘The object of this study is to propose a statistical model for predicting the Expected Path Length (expected number of steps the attacker will take, starting from the initial state to compromise the security goal—EPL) in a cyber-attack. The model we developed is based on utilizing vulnerability information along with having host centric attack graph. Utilizing the developed model, one can identify the interaction among the vulnerabilities and individual variables (risk factors) that drive the Expected Path Length. Gaining a better understanding of the relationship between vulnerabilities and their interactions can provide security administrators a better view and an understanding of their security status. In addition, we have also ranked the attributable variables and their contribution in estimating the subject length. Thus, one can utilize the ranking process to take precautions and actions to minimize Expected Path Length.
文摘This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" "=""><span style="font-family:Verdana;"> of the binomial distribution. Evidence in the literature indicates the standard Wald confidence interval for the binomial proportion is inaccurate, especially for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Even for moderately large sample sizes, the coverage probabilities of the Wald confidence interval prove to be erratic for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Three alternative confidence intervals, namely, Wilson confidence interval, Clopper-Pearson interval, and likelihood interval</span></span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> are compared to the Wald confidence interval on the basis of coverage probability and expected length by means of simulation.</span>
