A metric for software vulnerabilities classification [article]

Gabriele Modena
<span title="2014-07-21">2014</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Vulnerability discovery and exploits detection are two wide areas of study in software engineering. This preliminary work tries to combine existing methods with machine learning techniques to define a metric classification of vulnerable computer programs. First a feature set has been defined and later two models have been tested against real world vulnerabilities. A relation between the classifier choice and the features has also been outlined.
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1212.3669v2">arXiv:1212.3669v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pcke667kbbhqxkxogebu43kh6m">fatcat:pcke667kbbhqxkxogebu43kh6m</a> </span>
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