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Adam: Automated Detection And Attribution Of Malicious Webpages, Ahmed E. Kosba, Aziz Mohaisen, Andrew G. West, Trevor Tonn, Huy Kang Kim
Adam: Automated Detection And Attribution Of Malicious Webpages, Ahmed E. Kosba, Aziz Mohaisen, Andrew G. West, Trevor Tonn, Huy Kang Kim
Andrew G. West
Malicious webpages are a prevalent and severe threat in the Internet security landscape. This fact has motivated numerous static and dynamic techniques to alleviate such threats. Building on this existing literature, this work introduces the design and evaluation of ADAM, a system that uses machine-learning over network metadata derived from the sandboxed execution of webpage content. ADAM aims to detect malicious webpages and identify the nature of those vulnerabilities using a simple set of features. Machine-trained models are not novel in this problem space. Instead, it is the dynamic network artifacts (and their subsequent feature representations) collected during rendering that …