Beyond heuristics: learning to classify vulnerabilities and predict exploits

The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of software vulnerabilities that have the potential to compromise their systems in some way. Such vulnerabilities include buffer overflow errors, improperly validated inputs, and other unanticipated attack modalities. In 2008, over 7,400 new vulnerabilities were disclosed—well over 100 per week. While no enterprise is affected by all of these disclosures, administrators commonly face many outstanding vulnerabilities across the software systems they manage. A key question for systems administrators is which vulnerabilities to prioritize. From publicly available databases that document past vulnerabilities, we show how to train classifiers that predict whether and how soon a vulnerability is likely to be exploited. As input, our classifiers operate on high dimensional feature vectors that we extract from the tex...

• Type: Conference
• Year: 2010
• Where: KDD
• Authors: Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
• Keywords: Data Mining, KDD 2010, Software Vulnerabilities, Vulnerabilities, Vulnerabilities Include Buffer