Abstract
<p><em>Prioritizing on most critical weaknesses in a network system at the correct time is a very important role in network security administration. Due to the complexity and high unpredictability of exploitations it is hard to decide which vulnerabilities and which IP s are at the highest risk at a particular time. Present study proposes a new methodology that enables network administrators to rank vulnerabilities based on the probability of being exploited at a given time using the Markovian process. Markovian process allows us to iterate a transition probability matrix for a network system consisting identified or discovered vulnerabilities. This process result in a steady state with probabilities that a vulnerability will be exploited. Similar approach is used here to develop a risk rank model. Well known Google Page Rank Algorithm also uses a similar approach in estimating the probability of a web surfer reaching a particular webpage. Same concept can be used with several modifications to estimate and rank the risk level of each vulnerability in a network system. New methodology is presented with an example of a small network model with three vulnerabilities.</em></p>
Highlights
A Network systems could have numerous vulnerabilities
Well known Google Page Rank Algorithm uses a similar approach in estimating the probability of a web surfer reaching a particular webpage
Risk Rank Algorithm By developing the concept applied in Google Page Rank Algorithm here we introduce a ranking method for risk of vulnerabilities (Frei, 2009) in a network system
Summary
A Network systems could have numerous vulnerabilities. We understand the process of generating vulnerabilities is highly stochastic and outcomes are hard to predict. Vol 2, No 1, 2019 the discovered vulnerabilities the analysis must consider the dynamic nature of the effect of vulnerabilities over time. As we observed in our previous studies (Kaluarachchi, Tsokos, & Rajasooriya, 2016), the effect of the vulnerabilities vary with the time through their life cycle. It would be very useful to have analytical models to observe the behavior of the rank of vulnerabilities based on the magnitude of the threat with respect to time for a given network system. Such ranking distribution over time would empower the defenders by giving the priority directions to attend on fixing vulnerabilities.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
