2009 BeyondBlacklistsLearningtoDetec

• (Ma et al., 2009) ⇒ Justin Ma, Lawrence K. Saul, Stefan Savage, and Geoffrey M. Voelker. (2009). “Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557153

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%22Beyond+blacklists%3A+learning+to+detect+malicious+web+sites+from+suspicious+URLs%22+2009
• http://portal.acm.org/citation.cfm?doid=1557019.1557153&preflayout=flat#citedby

Quotes

Author Keywords

Supervised Learning, Malicious Web sites, L1-regularization

Abstract

Malicious Web sites are a cornerstone of Internet criminal activities. As a result, there has been broad interest in developing systems to prevent the end user from visiting such sites. In this paper, we describe an approach to this problem based on automated URL classification, using statistical methods to discover the tell-tale lexical and host-based properties of malicious Web site URLs. These methods are able to learn highly predictive models by extracting and automatically analyzing tens of thousands of features potentially indicative of suspicious URLs. The resulting classifiers obtain 95-99% accuracy, detecting large numbers of malicious Web sites from their URLs, with only modest false positives.

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References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 BeyondBlacklistsLearningtoDetec	Lawrence K. Saul Justin Ma Stefan Savage Geoffrey M. Voelker			Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs		KDD-2009 Proceedings		10.1145/1557019.1557153		2009