Statistical models for predicting minimum number of step data of an attacker and reliability functions of a computer network system are described. The models are based on utilizing vulnerability information along with an attack graph. Using the model, it is possible to identify the interaction among vulnerabilities and individual variables or risk factors that drive the minimum number of step data. Gaining a better understanding of the relationship between the vulnerabilities and their interactions can provide security administrators with a better view and understanding of their security status.The reliability of a computer network is very crucial matter. Any attempt to hack into a network with stored information will place the system at substantial risk. Identifying the analytical form of the reliability function depends initially on knowing the failure times of a given product. In cybersecurity- computer network systems, there is no definition of what is meant by reliability in cybersecurity. Thus, researchers have introduced what they believe is a good definition of the subject matter. In the domain of reliability, the key entity is the failure times. In this innovation, researchers have used the available vulnerabilities of computer operating systems and used an existing statistical model to identify the minimum number of steps that will take a hacker to hack a given computer network. Once the computer network is hacked, it fails us, thus, our failure time is the minimum number of steps necessary to hack the subject network. In developing the analytical form of the reliability function of a given computer network. it is necessary to identify the probability distribution that characterizes probabilistically the behavior of n (the minimum number of steps to hack a given computer network). This proposed innovation addresses the question both parametric and nonparametric with a high degree of accuracy. Although this real data driven analytical model is for a specific computer network system, this method can be used to derive the model for any computer network system that a company desire.
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