ALICE@Home: Distributed Framework for Detecting Malicious Sites


Erete, I., Yegneswaran, V., Porras, P. (2009). ALICE@home: Distributed Framework for Detecting Malicious Sites. In: Kirda, E., Jha, S., Balzarotti, D. (eds) Recent Advances in Intrusion Detection. RAID 2009. Lecture Notes in Computer Science, vol 5758. Springer, Berlin, Heidelberg.


Malware silently infects millions of systems every year through drive-by downloads, i.e., client-side exploits against web browsers or browser helper objects that are triggered when unsuspecting users visit a page containing malicious content. Identifying and blacklisting websites that distribute malicious content or redirect to a distributing page is an important part of our defense strategy against such attacks. However, building such lists is fraught with challenges of scale, timeliness and deception due to evasive strategies employed by adversaries. In this work, we describe alice@home, a distributed approach to overcoming these challenges and actively identifying malware distribution sites.

Keywords: Distribution Site, Document Object Model, USENIX Security Symposium, Malicious Content, Malicious Site

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