Machine Learning in Vulnerability Databases
Zhechao Lin, Xiang Li, Xiaohui Kuang · 2017
We mainly introduce the application of machine learning in vulnerability databases. By analysing an existing open source vulnerability database, we extract relevant attributes and construct lists of the attributes, then mining the attribute lists using machine learning technology, hope to discover some knowledge which is novel, interesting and of value to researchers. We only mine the association rules in a vulnerability database in this paper. Through these association rules, we can discover some co-oocurring vulnerability attributes, which can be further inferred laws of vulnerabilities.