Computer vulnerabilities are design flaws, implementation or configuration errors that provide a means of exploiting a system or network that would not be available otherwise. The recent growth in the number of vulnerability scanning (VS) tools and independent vulnerability databases points to an apparent need for further means to protect computer systems from compromise. It is important for these tools and databases to interpret, correlate and exchange a large amount of information about computer vulnerabilities in order to use them effectively. However, this goal is hard to achieve because the current VS products differ extensively both in the way that they can detect vulnerabilities and in the number of vulnerabilities that they can detect. Each tool or database represents, identifies and classifies vulnerabilities in its own way, thus making them difficult to study and compare. Although the list of Common Vulnerabilities and Exposures (CVE) provides a means of solving the disparity in vulnerability names used in the different VS products, it does not standardise vulnerability categories. This dissertation highlights the importance of having a standard vulnerability category set and outlines an approach towards achieving this goal by categorising the CVE repository using a data-clustering algorithm. Prototypes are presented to verify the concept of standardizing vulnerability categories and how this can be used as the basis for comparison of VS products and improving scan reports. / Dissertation (MSc (Computer Science))--University of Pretoria, 2008. / Computer Science / unrestricted