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Recent studies have shown that router misconfigurations are common and can have dramatic consequences to the operations of a network. Misconfigurations can compromise the security of an entire network or even cause global disruptions to Internet connectivity. Several solutions have been proposed. They can detect a number of problems in real configuration files. However, these solutions share a common limitation: they are based on rules which need to be known beforehand. Violations of these rules are deemed misconfigurations. As policies typically differ among networks, these approaches are limited in the scope of mistakes they can detect. In this paper, the authors address the problem of router misconfigurations using data mining.
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