Abstract
Vulnerability scanners (VSs) are information security tools able to detect security weaknesses on hosts in a network. VSs secure hosts in a proactive manner. A proactive approach is considered to be better than reactive approaches followed by, for example, intrusion detection systems, because prevention is better than cure. There are many problems and disadvantages of currently available VSs, such as hampering system resources while conducting scans. This paper introduces a conceptual model for vulnerability forecasting. The model uses intelligent techniques to improve on the efficiency of currently available VSs. The model aims to do vulnerability forecasting specifically by predicting the number of known vulnerabilities that will occur in the near future by using intelligent techniques and vulnerability history data. The model is tested by means of a prototype and an evaluation of the model's results is also provided in the paper.
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