NDLI: Using uncleanliness to predict future botnet addresses

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Using uncleanliness to predict future botnet addresses

Content Provider	ACM Digital Library
Author	De Shon, Markus Shimeall, Timothy J. Janies, Jeff Kadane, Joseph Faber, Sidney Weaver, Rhiannon Collins, M. Patrick
Abstract	The increased use of botnets as an attack tool and the awareness attackers have of blocking lists leads to the question of whether we can effectively predict future bot locations. To that end, we introduce a network quality that we term uncleanliness: an indicator of the propensity for hosts in a network to be compromised by outside parties. We hypothesize that unclean networks will demonstrate two properties: spatial and temporal uncleanliness. Spatial uncleanliness is the tendency for compromised hosts to cluster within unclean networks. Temporal uncleanliness is the tendency for unclean networks to contain compromised hosts for extended periods. We test for these properties by collating data from multiple indicators (spamming, phishing, scanning and botnet IRC log monitoring). We demonstrate evidence for both spatial and temporal uncleanliness. We further show evidence for cross-relationship between the various datasets, showing that botnet activity predicts spamming and scanning, while phishing activity appears to be unrelated to the other indicators.
Starting Page	93
Ending Page	104
Page Count	12
File Format	PDF
ISBN	9781595939081
DOI	10.1145/1298306.1298319
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-10-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Blacklists Botnets Reputation management
Content Type	Text
Resource Type	Article

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