Visible to the public CVSS Metric-Based Analysis, Classification and Assessment of Computer Network Threats and Vulnerabilities

TitleCVSS Metric-Based Analysis, Classification and Assessment of Computer Network Threats and Vulnerabilities
Publication TypeConference Paper
Year of Publication2018
AuthorsKebande, V. R., Kigwana, I., Venter, H. S., Karie, N. M., Wario, R. D.
Conference Name2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD)
ISBN Number978-1-5386-3060-0
KeywordsAnalysis, assessment, classification, CNSVT, common vulnerability scoring system metric-based technique, computer network security, computer network security vulnerabilities, computer network threats, computer networks, Computer science, computer security, computer-based networks, CVSS metric-based dynamic vulnerability analysis classification countermeasure criterion, CVSS metric-based VACC, CVSS-metric, Measurement, Metrics, Monitoring, Network, network security tools, probability, Protocols, pubcrawl, security metrics, threats, VACC, VSM, vulnerabilities, vulnerability Similarity Measure

This paper provides a Common Vulnerability Scoring System (CVSS) metric-based technique for classifying and analysing the prevailing Computer Network Security Vulnerabilities and Threats (CNSVT). The problem that is addressed in this paper, is that, at the time of writing this paper, there existed no effective approaches for analysing and classifying CNSVT for purposes of assessments based on CVSS metrics. The authors of this paper have achieved this by generating a CVSS metric-based dynamic Vulnerability Analysis Classification Countermeasure (VACC) criterion that is able to rank vulnerabilities. The CVSS metric-based VACC has allowed the computation of vulnerability Similarity Measure (VSM) using the Hamming and Euclidean distance metric functions. Nevertheless, the CVSS-metric based on VACC also enabled the random measuring of the VSM for a selected number of vulnerabilities based on the [Ma-Ma], [Ma-Mi], [Mi-Ci], [Ma-Ci] ranking score. This is a technique that is aimed at allowing security experts to be able to conduct proper vulnerability detection and assessments across computer-based networks based on the perceived occurrence by checking the probability that given threats will occur or not. The authors have also proposed high-level countermeasures of the vulnerabilities that have been listed. The authors have evaluated the CVSS-metric based VACC and the results are promising. Based on this technique, it is worth noting that these propositions can help in the development of stronger computer and network security tools.

Citation Keykebande_cvss_2018